ISSN 0974 - 0996January - March | 2012 | Vol :: 05 | No :: 1

metering,monitoring andtargeting: The Gateway to

Efficient Energy Management

Utilizing your metered dataM&M – technologies that enable energy efficiency Energy meters and their reliabilityEnergy efficient computingWind power developments in Oceania

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Registered Office :Energy Press | SEEM Bhavan | KRA-A79Kannammoola | Thiruvananthapuram | Kerala | IndiaTel : +91 - 471 - 2557607 | 3242323E : energymanagerhq@gmail.comWeb: www.energyprofessional.in

dvances in energy metering and data collection technology have Aleft many energy users here in the UK with a problem: data flooding. The same is either happening already or will soon happen in many other countries including India, and the irony is that even if the flood of data were tamed, it would not necessarily provide information that is of real value for day-to-day management of energy. You might be able to see how much energy is being used, where, when, and for what; but you will not know whether the amount of energy you used was excessive or not. This is critical information because even in the best-run enterprise, things occasionally go wrong or are done incorrectly. From time controls being overridden to heat exchangers becoming fouled, from non-return valves failing to photocells being obscured, from air recirculation dampers sticking closed to employees stealing oil, your organisation is vulnerable to random energy waste which would be avoidable if somebody realised it had

ηoccurred. Inside this issue of energy manager magazine features a wealth of advice on how to measure consumption and collect the data. It would be a good idea to step back for a moment and consider how you can filter that data and turn it into information that actively supports your energy-saving efforts.

Now you will often hear the saying "you cannot manage what you do not measure" or words to that effect. Nobody knows who first said it or what they really said (which is why there are so many versions) but it does not matter, because in energy management that saying simply fails to tell the whole story. To manage energy you need two things: not just a measurement of actual consumption, but also an estimate of what it should have been. ISO 50001, the new management-systems standard for energy, puts it succinctly in section 4.6.1 (e) where it calls for "evaluation of actual versus expected consumption" (my italics). Meters give you actual consumption, but expected consumption must be calculated from other independent measurements. The process is not complex. Typically, a given stream of consumption will depend on things such as production throughputs, the outside air temperature, number of hours of darkness or other 'driving' factor-so called because their variation drives variation in consumption-and the trick is to establish, from historical patterns, what the normal relationship is between each metered consumption and its relevant driving factor or factors. The relationship can in each case be expressed as a mathematical formula. At the end of each week (say) the driving-factor values are entered into the formulae, and out come a set of expected consumptions.

Armed with both an actual and an expected consumption for each meter, you can evaluate the differences and (importantly) tabulate the financial costs of each of those differences. Now you can wave a

V.O. Vesma

Advisory Board

Dr. Bhaskar Natarajan | C-Quest Capital, India

Binu Parthan | REEEP, Vienna

Dr. Brahmanand Mohanty | Advisor, ADEMEM.C. Jain | President, SEEM, IndiaDr. B.G. Desai | Energy Expert, India

C. Jayaraman | SEEM, IndiaDr. Kinsuk Mitra | Winrock International, India

Dr. G. M. Pillai| WISE, India

Dr. N.P Singh | Advisor MNRE, India

Prof. P.R. Shukla | IIM Ahmedabad, India

Editorial Board

Prof. Ahamed Galal Abdo | Advisor Minister of

Higher Education, Egypt

Darshan Goswami | US Dept. of Energy, USA

Prof. (Dr.) Hab Jurgis Staniskis | Director, Institute

of Environmental Engg., Lithuania

Dr. R. Harikumar | General Secretary, SEEM, IndiaProf. P.A. Onwualu | DG, RMR&D Council, Nigeria

R.Paraman |Devki Energy Consultancy,India

Ramesh Babu Gupta | India

Dr. Rwaichi J.A. Minja | University of Dar Es

Salaam, Tanzania

Prof. (Dr.) R. Sethumadhavan | Anna University, India

Prof. Sujay Basu | CEEM, India

Editorial Consultant

Prof. (Dr.) K. K.Sasi |Amrita University, India

Guest Editor

Editor

K. Madhusoodanan|SEEM, India

Publishing Director

Santosh Goenka

Co-ordinating Editor

Sonia Jose | Energy Press, India

Book DesignBadusha Creatives

Translation Coordinator

R. Sudhir Kumar|CPRI, Bangalore

Financial ControllerK. K. Babu | Energy Press, India

Printed and Published by

G. Krishnakumar, Energy Press

for the Society of Energy Engineers and Managers

and printed at St Francis Press, Ernakulam, India

Disclaimer : The views expressed in the magazine

are those of the authors and the Editorial team |

SEEM | energy press | does not

take responsibility for the contents and opinions.

will not be responsible for errors,

omissions or comments made by writers,

interviewers or advertisers. Any part of this

publication may be reproduced with

acknowledgement to the author and magazine.

| Volume 05 | Number: 1

ISSN 0974 - 0996

Supported by::

V.O. Vesma

ηenergy manager

ηenergy manager

January - March 2012

...continued in page 62

After collection, comprehension

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Mr. Vilnis Vesma is a trainer and independent consultant in energy saving methods. He specializes in the analysis and interpretation of energy consumption data, and is a council member of the Energy Services and Technology Association, committee of the International Performance Measurement and Verification Protocol and served on the committee that wrote ISO 50001:2011. He is the author of two books on energy management and maintains a free web site providing information and advice for energy managers.

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Cover Feature

Best Practice

Opinion

Energy Management

Renewable Energy

Global Focus

Sustainable Living

Maximum utilisation of metered data 06Raviraj Kadiyala

Metering and monitoring - enabling technologies to deliver energy efficiency 12Jasjeet Singh Hanjrah

In-circuit reliability of energy meters 16Rajesh Nimare

Hot and cold running savings 22Fluke

Free cooling: an energy conservation measure 25Balbir Singh and V. K. Sethi

Impact of system load factor in transmission & distribution losses 30K. K. Babu

Energy efficient computing 37Soujanya Nemalikanti and Polavarupu Sindhura

Charring-briquetting : a novel cooking fuel technology 43B. P. Nema

Wind turbines for oceanic areas : innovations and developments 47Ron Steenbergen

Energy and environment symbiosis 54A. K. Jain

f all the investments that industrial units make to help Oreduce their energy spend, Energy Metering, Monitoring and Targeting System (MM&T) is undoubtedly the number one priority. Organisations implement monitoring and targeting systems from the Operational, Economic and Business perspectives. A recent study conducted by the Carbon Trust in over 1000 small businesses has concluded that on average an organisation could save 5% of its original energy expenses through M&T system. Other most recurrent benefits demonstrated through M&T programmes are better environmental performance, better production budgeting and provides support to environment management standards such as ISO 50001. It also helps in improving the prospects of obtaining financing for energy efficiency projects, better forecast of energy expenses leading to improved budgeting, and a diagnosis of energy waste in processes. It is true that at the industrial level (macro level), the key success factors for monitoring & targeting include process energy complexity, consistent production variables, significant energy costs and regulatory support, but the backbone of any successful energy monitoring and targeting programme, is advanced metering.

Advanced metering - a wise investment

Advanced metering is the most essential energy efficiency investment that any unit wishing to control its energy costs must make. The increased granularity of data provided by an advanced meter will assist units to implement a highly effective energy management programme. The accurate and regular consumption data derived from the advanced metering system mainly allows units to realize Base load reductions - for example by identifying unnecessary constant energy use, Process optimisation -as in the case of limiting the duration of high-energy use at the start and end of working schedules, and Peak usage reduction - analyzing timings and frequencies to establish the causes of peaks in energy usage, and understanding the causes in terms of specific activities or equipment.

Saving opportunities identified from advanced meter data can be pursued in several ways, including Information-based (behavioural) energy savings, Process-based energy savings as well as Investment-based energy savings. Combined with an understanding of how employees use energy across the business, possible information based/ behavioral savings can be identified and relevant behavioral changes can be targeted via a motivational programme. Advanced metering data can identify and quantify the effect of implementing these measures and monitor their impact over time. Typically costing nothing to implement, such savings foster a best practice approach to energy consumption within the organization. As mentioned before, data from advanced meters can also identify where processes can be optimised and quantify their impact. Energy savings can be achieved by changing the start-up and shutdown times of specific systems or by altering their power usage and temperature settings.

Advanced metering data can identify inefficiencies in equipment and infrastructure as well. The energy consumption of specific systems can be rated against manufacturers' specifications and more efficient equivalents, which can make or break a business case for an equipment upgrade or replacement. Though investment-based energy savings involve significant capital costs, the improvements have higher persistence levels than information-based or process based savings.

Though there are a variety of advanced metering solutions in the market, including the Fiscal meter, Clip-on, Secondary meter, Comms and HH, the half-hourly (HH) meters have become the most commonly used instruments for advanced metering systems. The half-hourly data can also be aggregated for billing purposes, avoiding the requirement for estimated bills.

Barriers to advanced metering, monitoring and targeting

Advanced metering for generating energy consumption information is only half of the story. What is more important is the analysis of data to relate consumption data with the production to evolve a meaningful benchmark to see whether it is a good, poor or an average performance. The interpretation needs to look at many factors such as capacity utilization level, ambient conditions, physics and chemistry of the process involved etc.

Although energy metering, monitoring and targeting is considered to be the most essential feature of energy management system, the key pillars for its successful implementation are people, system and technology.

The senior management needs to be committed for a culture change, moving the organization from one that considers energy consumption as a necessary cost to one which views energy as a resource that needs to be managed as effectively as the organization manages its raw materials or its workforce.

The organisation should ensure that managers responsible for energy consumption are accountable for it, one way to do this is to allocate energy budget to the individual production departments. The energy budget should be given as much emphasis as all other aspects of the production budget and energy performance should be included in the regular performance review and reward systems.

With the organisation motivated to identify energy saving ideas, the organisation needs to be in a position to implement the energy saving projects. Unlike other areas of production management, energy saving will tend to involve a large number of very small projects, hence the organisation requires the capability to identify, evaluate, design, engineer and manage the implementation of such projects.

Studies have demonstrated that SMEs using advanced metering can identify an average of 12% carbon savings and implement an average of 5% carbon savings through reduced utility consumption. But given the potential benefits of advanced metering, this technology definitely faces barriers, especially in gaining grounds among the SME community. And these emerge from both ends - from the customer as well as the supplier. Barriers from the Customer-side include a less than desirable level of awareness of advanced metering, linking energy use to costs and their transparency, availability of metering services, understanding of available service options and of course limited time and resources, those from the Supply-side point to the capacity of metering service providers, insufficient incentives for suppliers and concerns of stranded asset.

A small number of advanced metering service providers currently offer a range of different commercial services for business users, varying from remote collection of data from existing half-hourly meters to installing new advanced meters or providing 'clip-on' meter reading devices for existing

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The road to efficient energy metering,monitoring and targeting

meters where compatible. However, there is currently a lack of full end-to-end metering services for the SME market. The smaller service providers tend to specialise in either data collection or meter installation and sometimes form strategic alliances with companies providing complementary services.

In light of the significant savings achievable through metering, it is essential that the potential benefits of advanced metering is widely understood. There is also a need to stimulate market demand by developing case studies that demonstrate the reduction in energy consumption and costs made possible using this technology. Also, steps to introduce a mandatory roll out of advanced meters for SMEs will ensure that a significant cost effective carbon saving opportunity is not missed.

K. Madhusoodanan

Editor

(Please contribute your articles and case studies to reach the editor at madhukoovaprath@gmail.com or energymanagerhq@gmail.com)

edit

or'

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ote

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Cover Feature

Best Practice

Opinion

Energy Management

Renewable Energy

Global Focus

Sustainable Living

Maximum utilisation of metered data 06Raviraj Kadiyala

Metering and monitoring - enabling technologies to deliver energy efficiency 12Jasjeet Singh Hanjrah

In-circuit reliability of energy meters 16Rajesh Nimare

Hot and cold running savings 22Fluke

Free cooling: an energy conservation measure 25Balbir Singh and V. K. Sethi

Impact of system load factor in transmission & distribution losses 30K. K. Babu

Energy efficient computing 37Soujanya Nemalikanti and Polavarupu Sindhura

Charring-briquetting : a novel cooking fuel technology 43B. P. Nema

Wind turbines for oceanic areas : innovations and developments 47Ron Steenbergen

Energy and environment symbiosis 54A. K. Jain

f all the investments that industrial units make to help Oreduce their energy spend, Energy Metering, Monitoring and Targeting System (MM&T) is undoubtedly the number one priority. Organisations implement monitoring and targeting systems from the Operational, Economic and Business perspectives. A recent study conducted by the Carbon Trust in over 1000 small businesses has concluded that on average an organisation could save 5% of its original energy expenses through M&T system. Other most recurrent benefits demonstrated through M&T programmes are better environmental performance, better production budgeting and provides support to environment management standards such as ISO 50001. It also helps in improving the prospects of obtaining financing for energy efficiency projects, better forecast of energy expenses leading to improved budgeting, and a diagnosis of energy waste in processes. It is true that at the industrial level (macro level), the key success factors for monitoring & targeting include process energy complexity, consistent production variables, significant energy costs and regulatory support, but the backbone of any successful energy monitoring and targeting programme, is advanced metering.

Advanced metering - a wise investment

Advanced metering is the most essential energy efficiency investment that any unit wishing to control its energy costs must make. The increased granularity of data provided by an advanced meter will assist units to implement a highly effective energy management programme. The accurate and regular consumption data derived from the advanced metering system mainly allows units to realize Base load reductions - for example by identifying unnecessary constant energy use, Process optimisation -as in the case of limiting the duration of high-energy use at the start and end of working schedules, and Peak usage reduction - analyzing timings and frequencies to establish the causes of peaks in energy usage, and understanding the causes in terms of specific activities or equipment.

Saving opportunities identified from advanced meter data can be pursued in several ways, including Information-based (behavioural) energy savings, Process-based energy savings as well as Investment-based energy savings. Combined with an understanding of how employees use energy across the business, possible information based/ behavioral savings can be identified and relevant behavioral changes can be targeted via a motivational programme. Advanced metering data can identify and quantify the effect of implementing these measures and monitor their impact over time. Typically costing nothing to implement, such savings foster a best practice approach to energy consumption within the organization. As mentioned before, data from advanced meters can also identify where processes can be optimised and quantify their impact. Energy savings can be achieved by changing the start-up and shutdown times of specific systems or by altering their power usage and temperature settings.

Advanced metering data can identify inefficiencies in equipment and infrastructure as well. The energy consumption of specific systems can be rated against manufacturers' specifications and more efficient equivalents, which can make or break a business case for an equipment upgrade or replacement. Though investment-based energy savings involve significant capital costs, the improvements have higher persistence levels than information-based or process based savings.

Though there are a variety of advanced metering solutions in the market, including the Fiscal meter, Clip-on, Secondary meter, Comms and HH, the half-hourly (HH) meters have become the most commonly used instruments for advanced metering systems. The half-hourly data can also be aggregated for billing purposes, avoiding the requirement for estimated bills.

Barriers to advanced metering, monitoring and targeting

Advanced metering for generating energy consumption information is only half of the story. What is more important is the analysis of data to relate consumption data with the production to evolve a meaningful benchmark to see whether it is a good, poor or an average performance. The interpretation needs to look at many factors such as capacity utilization level, ambient conditions, physics and chemistry of the process involved etc.

Although energy metering, monitoring and targeting is considered to be the most essential feature of energy management system, the key pillars for its successful implementation are people, system and technology.

The senior management needs to be committed for a culture change, moving the organization from one that considers energy consumption as a necessary cost to one which views energy as a resource that needs to be managed as effectively as the organization manages its raw materials or its workforce.

The organisation should ensure that managers responsible for energy consumption are accountable for it, one way to do this is to allocate energy budget to the individual production departments. The energy budget should be given as much emphasis as all other aspects of the production budget and energy performance should be included in the regular performance review and reward systems.

With the organisation motivated to identify energy saving ideas, the organisation needs to be in a position to implement the energy saving projects. Unlike other areas of production management, energy saving will tend to involve a large number of very small projects, hence the organisation requires the capability to identify, evaluate, design, engineer and manage the implementation of such projects.

Studies have demonstrated that SMEs using advanced metering can identify an average of 12% carbon savings and implement an average of 5% carbon savings through reduced utility consumption. But given the potential benefits of advanced metering, this technology definitely faces barriers, especially in gaining grounds among the SME community. And these emerge from both ends - from the customer as well as the supplier. Barriers from the Customer-side include a less than desirable level of awareness of advanced metering, linking energy use to costs and their transparency, availability of metering services, understanding of available service options and of course limited time and resources, those from the Supply-side point to the capacity of metering service providers, insufficient incentives for suppliers and concerns of stranded asset.

A small number of advanced metering service providers currently offer a range of different commercial services for business users, varying from remote collection of data from existing half-hourly meters to installing new advanced meters or providing 'clip-on' meter reading devices for existing

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The road to efficient energy metering,monitoring and targeting

meters where compatible. However, there is currently a lack of full end-to-end metering services for the SME market. The smaller service providers tend to specialise in either data collection or meter installation and sometimes form strategic alliances with companies providing complementary services.

In light of the significant savings achievable through metering, it is essential that the potential benefits of advanced metering is widely understood. There is also a need to stimulate market demand by developing case studies that demonstrate the reduction in energy consumption and costs made possible using this technology. Also, steps to introduce a mandatory roll out of advanced meters for SMEs will ensure that a significant cost effective carbon saving opportunity is not missed.

K. Madhusoodanan

Editor

(Please contribute your articles and case studies to reach the editor at madhukoovaprath@gmail.com or energymanagerhq@gmail.com)

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maximum utilisationof metered data

Raviraj Kadiyala

A successful metering strategy

requires more than installing

the meters. This article explains

how to derive maximum use of

metered data, especially from

interval metering and sub-

metering of energy

consumption in an

organization. While metered

data gives a direct view of the

energy consumption at each of

the facilities, it also acts as the

fundamental piece of

information in computing

appropriate efficiency metrics.

One of the significant merits of

having metered data over long

periods of time is in enabling

prediction of energy

consumption. Metered data

monitored through a central

system not only provide

auditable data, but also

dramatically reduce the time

required for data collection and

report preparation.

lmost all organizations acknowledge energy metering or sub-metering as a crucial element of energy Aefficiency in their facilities. With the maxim 'measure to save', over 5% of energy cost saving is often

pegged to granular metering.

Depending on the objective and availability of funds, sub-metering may be

considered to provide load-wise energy consumption details. In addition, advanced

meters make it possible to get time series data at pre-determined intervals. Over a

period of time, these measures can generate a huge quantum of valuable data.

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maximum utilisationof metered data

Raviraj Kadiyala

A successful metering strategy

requires more than installing

the meters. This article explains

how to derive maximum use of

metered data, especially from

interval metering and sub-

metering of energy

consumption in an

organization. While metered

data gives a direct view of the

energy consumption at each of

the facilities, it also acts as the

fundamental piece of

information in computing

appropriate efficiency metrics.

One of the significant merits of

having metered data over long

periods of time is in enabling

prediction of energy

consumption. Metered data

monitored through a central

system not only provide

auditable data, but also

dramatically reduce the time

required for data collection and

report preparation.

lmost all organizations acknowledge energy metering or sub-metering as a crucial element of energy Aefficiency in their facilities. With the maxim 'measure to save', over 5% of energy cost saving is often

pegged to granular metering.

Depending on the objective and availability of funds, sub-metering may be

considered to provide load-wise energy consumption details. In addition, advanced

meters make it possible to get time series data at pre-determined intervals. Over a

period of time, these measures can generate a huge quantum of valuable data.

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Presently, energy consumption is tracked at least

once a month at facility level, if not more often. This

helps to compare the energy consumption of a facility

and track any anomalies. Depending on the objective

and availability of funds, sub-metering may be

considered to provide load-wise energy consumption

details. In addition, advanced meters make it possible

to get time series data at pre-determined intervals.

Over a period of time, these measures can generate a

huge quantum of valuable data.

A successful metering strategy requires more than

installing the meters. This article explains how to

derive maximum use of metered data, especially from

interval metering and sub-metering of energy

consumption in an organization.

Benchmarking

In multi-facility organizations, it becomes imperative

for management teams to know how each of the

different facilities perform in terms of energy

consumption and efficiency. While metered data give

a direct view of the energy consumption, it also acts

as the fundamental piece of information in computing

appropriate efficiency metrics. The metrics used

could be ones like energy usage intensity (EUI), which

is kilowatt-hours per square metres or square feet, or

power usage effectiveness (PUE) in the case of

computer data centres which is the quotient of total

facility energy divided by IT energy. Irrespective of the

magnitude of energy consumption, these metrics not

only enable determining which facility is efficient, but

also enables organizations to set efficiency goals by

comparing energy consumption levels between peer

facilities and industry benchmarks.

Schedule Mismatch

Most organizations fix schedules of operation based

on work hours of employees, varying

equipment/business loads in different shifts, off-

hour/holiday/weekend schedules and so on which

impact energy consumption. Analyzing metered data

helps identify compliance to these schedules. Any

deviation observed is a potential area for energy

savings (Figure 1). In a facility where working hours

are from 9 a.m. to 6 p.m, it may be unjustifiable if the

energy consumption data indicate that 70% to 80% of

work hour energy consumption continues till 8 p.m.

The situation should be investigated and appropriate

corrective action taken.

Base Load

Data collected during off-hour periods indicate the

base load of a facility. It is the energy requirement of

the facility irrespective of any active operations.

Hence, it is the minimum amount of energy used by

the facility and indicates the minimum energy cost

incurred (Figure 1). However, the observed base load

may not be justifiable in all cases. By identifying the

loads that are expected to be operational, the actual

energy consumption data could be verified, and it

may turn out to be more than expected. Any reduction

that is subsequently achieved in the base load will

bring about maximum savings for single-shift facilities

and progressively to a lesser extent for extended

hours or multi-shift facilities.

Seasonality and Weather Impact

Energy consumption of facilities could follow a

seasonal pattern based on weather, business cycles

or holidays/festival periods. Analyzing the data over

longer time horizons of at least a year helps identify

such patterns. Checking whether these are in line with

known events or cycles could identify energy-saving

opportunities (Figure 2). Comparison can also be

done of cycles across multiple years, which can bring

out differences in consumption pattern. Investigation

Analyzing energy consumption data over

longer time horizons of at least a year

helps identify seasonal patterns based on

various factors. Checking whether these

are in line with known events or cycles

could identify energy-saving opportunities.

into the root cause of such differences would help

better control of energy consumption. Typical

optimizations here relate to thermal insulation of

facilities and equipment energy efficiency.

Load Breakup

One of the primary reasons for or benefits of sub-

metering is that it leads to an insight into load

breakup and identify loads that are sub-optimal in

energy efficiency. This could be either based on

absolute consumption details or in relation to other

load values. For example, in a data centre (Figure 3),

what is the heating, ventilation and air conditioning

(HVAC) load with respect to the IT load? The load

relationship can also be studied for different time

periods to understand the way it is changing. For

example, how is it varying between day and night,

work and off day, summer and winter and so on?

Such insights would help justify or improve energy

consumption.

Analytics and Forecasting

One of the significant merits of having metered data

over long periods of time is in enabling prediction of

energy consumption with improved accuracy, enabled

through metering and monitoring of different key

parameters. In day-to-day operations, the forecasted

consumption can be used as a reference to control

energy consumption proactively rather than reactively.

In day-to-day operations, the forecasted

consumption can be used as a reference

to control energy consumption proactively

rather than reactively. Analysis of metered

data on an ongoing basis would enable

organizations to leverage maximum

potential at the earliest opportunity. For

example, it could highlight spikes,

anomalies in usage pattern, growth or

drop in energy consumption, changes in

key impacting parameters and so on.

Fig 1. Schedule Mismatch Fig 2. Seasonal Consumption Pattern Fig 3. Load Distribution

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Presently, energy consumption is tracked at least

once a month at facility level, if not more often. This

helps to compare the energy consumption of a facility

and track any anomalies. Depending on the objective

and availability of funds, sub-metering may be

considered to provide load-wise energy consumption

details. In addition, advanced meters make it possible

to get time series data at pre-determined intervals.

Over a period of time, these measures can generate a

huge quantum of valuable data.

A successful metering strategy requires more than

installing the meters. This article explains how to

derive maximum use of metered data, especially from

interval metering and sub-metering of energy

consumption in an organization.

Benchmarking

In multi-facility organizations, it becomes imperative

for management teams to know how each of the

different facilities perform in terms of energy

consumption and efficiency. While metered data give

a direct view of the energy consumption, it also acts

as the fundamental piece of information in computing

appropriate efficiency metrics. The metrics used

could be ones like energy usage intensity (EUI), which

is kilowatt-hours per square metres or square feet, or

power usage effectiveness (PUE) in the case of

computer data centres which is the quotient of total

facility energy divided by IT energy. Irrespective of the

magnitude of energy consumption, these metrics not

only enable determining which facility is efficient, but

also enables organizations to set efficiency goals by

comparing energy consumption levels between peer

facilities and industry benchmarks.

Schedule Mismatch

Most organizations fix schedules of operation based

on work hours of employees, varying

equipment/business loads in different shifts, off-

hour/holiday/weekend schedules and so on which

impact energy consumption. Analyzing metered data

helps identify compliance to these schedules. Any

deviation observed is a potential area for energy

savings (Figure 1). In a facility where working hours

are from 9 a.m. to 6 p.m, it may be unjustifiable if the

energy consumption data indicate that 70% to 80% of

work hour energy consumption continues till 8 p.m.

The situation should be investigated and appropriate

corrective action taken.

Base Load

Data collected during off-hour periods indicate the

base load of a facility. It is the energy requirement of

the facility irrespective of any active operations.

Hence, it is the minimum amount of energy used by

the facility and indicates the minimum energy cost

incurred (Figure 1). However, the observed base load

may not be justifiable in all cases. By identifying the

loads that are expected to be operational, the actual

energy consumption data could be verified, and it

may turn out to be more than expected. Any reduction

that is subsequently achieved in the base load will

bring about maximum savings for single-shift facilities

and progressively to a lesser extent for extended

hours or multi-shift facilities.

Seasonality and Weather Impact

Energy consumption of facilities could follow a

seasonal pattern based on weather, business cycles

or holidays/festival periods. Analyzing the data over

longer time horizons of at least a year helps identify

such patterns. Checking whether these are in line with

known events or cycles could identify energy-saving

opportunities (Figure 2). Comparison can also be

done of cycles across multiple years, which can bring

out differences in consumption pattern. Investigation

Analyzing energy consumption data over

longer time horizons of at least a year

helps identify seasonal patterns based on

various factors. Checking whether these

are in line with known events or cycles

could identify energy-saving opportunities.

into the root cause of such differences would help

better control of energy consumption. Typical

optimizations here relate to thermal insulation of

facilities and equipment energy efficiency.

Load Breakup

One of the primary reasons for or benefits of sub-

metering is that it leads to an insight into load

breakup and identify loads that are sub-optimal in

energy efficiency. This could be either based on

absolute consumption details or in relation to other

load values. For example, in a data centre (Figure 3),

what is the heating, ventilation and air conditioning

(HVAC) load with respect to the IT load? The load

relationship can also be studied for different time

periods to understand the way it is changing. For

example, how is it varying between day and night,

work and off day, summer and winter and so on?

Such insights would help justify or improve energy

consumption.

Analytics and Forecasting

One of the significant merits of having metered data

over long periods of time is in enabling prediction of

energy consumption with improved accuracy, enabled

through metering and monitoring of different key

parameters. In day-to-day operations, the forecasted

consumption can be used as a reference to control

energy consumption proactively rather than reactively.

In day-to-day operations, the forecasted

consumption can be used as a reference

to control energy consumption proactively

rather than reactively. Analysis of metered

data on an ongoing basis would enable

organizations to leverage maximum

potential at the earliest opportunity. For

example, it could highlight spikes,

anomalies in usage pattern, growth or

drop in energy consumption, changes in

key impacting parameters and so on.

Fig 1. Schedule Mismatch Fig 2. Seasonal Consumption Pattern Fig 3. Load Distribution

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10

Mr. Raviraj Kadiyala is a senior

consultant at Wipro EcoEnergy,

working in the field of energy

management services. His field of

work involves providing solutions to

organizations in sectors like

telecom, data centers and

commercial buildings across the

world to reduce and maintain

energy consumption/costs at

optimal levels.

max

imum

util

isat

ion

of m

eter

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ata

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

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the

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of e

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y en

gin

eers

and

man

ager

s / I

ndia

11Dynamic operating environments can provide energy-

saving opportunities on a continuous basis. Analysis

of metered data on an ongoing basis would enable

organizations to leverage maximum potential at the

earliest opportunity (Figure 4). For example, it could

highlight spikes, anomalies in usage pattern, growth

or drop in energy consumption, changes in key

impacting parameters and so on.

be possible to determine the efficiencies of

equipment like UPS and computer room air

conditioning (CRAC) units using sub-metered data.

However, metrics like energy efficiency ratio (EER)

used for CRAC units would require monitoring of

other associated parameters as well.

Peak Shaving/Shifting

Metered data can help in the classification of peak

loads into critical and non-critical. This insight can

then be used to determine if any of the peak loads

can be shifted to non-peak hours or if non-critical

loads can be reduced (Figure 5) thereby helping in

decreasing peak load charges. With the demand for

energy increasing and supply lagging behind, utility

companies face the challenge of meeting peak

demand requirements. While augmenting their peak

supply capacity, some utility companies offer demand

response programmes that incentivize end users to

reduce their demand. Analysis of metered data and

peak shaving/shifting would also make facilities

eligible to claim incentives from such programmes.

Contract Demand

It is typical of organizations to forecast their business

growth and the associated energy requirements while

applying for a contract demand from utilities. And the

projected demand would be much more than what is

required presently. This unutilized capacity comes at

an additional recurring cost, which is justified by

many to be worth the hassle/risk of getting additional

capacity at short notice. However, it would be a

worthwhile exercise to periodically review the

predicted business growth and energy requirement. It

may so happen that, due to business decisions or

turbulent market conditions, the actual energy

requirement will be much lower than the predicted

figures. Even considering the lead time for procuring

additional capacity, such instances may warrant

releasing of excess capacity and make the exercise

cash positive. Metered data provides a strong basis

for analyzing the peak demand requirement and the

demand growth that has actually been seen over a

period of time to make this call.

Loss Reduction

Quality of power has a bearing on performance

reliability, efficiency and life of equipment. Many

It may so happen that, due to business

decisions or turbulent market conditions,

the actual energy requirement will be

much lower than the figures predicted

while applying for a contract demand.

Even considering the lead time for

procuring additional capacity, such

instances may warrant releasing of excess

capacity and make the exercise cash

positive.

meters allow monitoring of data points that enable

determination of power quality, like power factor and

harmonics. Enabling them could highlight problem

areas which could then be addressed appropriately.

Utility Meter Faults and Billing Errors

The availability of sub-metering on main lines enables

one to detect any fault in the main utility meters.

Though rare, a faulty utility meter could go

undetected especially if it has been so over a period

of time. Installation of sub-meters enables one to

detect existing problems as well any new ones that

may arise. With a granular view into consumption,

metered data can be used to compute utility charges

independently. This can then be used to verify the

correctness of received invoices and reconcile with

utility companies.

Billing at Multi-tenanted Sites

In multi-tenanted facilities, contracts could be in place

that charge based on occupied area and not

necessarily on energy consumption. Metered data

can be used by organizations to renegotiate for

contracts that either do billing more in line with their

actual consumption or restructure them so that the

tenants are charged based on actuals.

Emissions Reporting

One of the big challenges in reporting emissions is

collecting reliable data on energy consumption.

Metered data monitored through a central system not

only provide auditable data, but also dramatically

reduce the time required for data collection and

report preparation.

Metering and monitoring requires investment. And, at

times, it becomes difficult to justify it. Moreover, it has

also been seen that at places where investments

have already been made, the use of data is restricted

only to a limited subset. It is the author's hope that

readers of this article would be able to tap the full

value of benefits realizable from their metered data.

Acknowledgements

The author acknowledges with gratitude the guidance

of Mr. Ravi Meghani in writing this article.

Equipment Efficiency

With appropriate levels of sub-metering, it is possible

to determine the actual performing efficiency of

equipment. This not only tells whether the units are

performing at expected levels, but also brings to

attention any maintenance needs when efficiency

drops unexpectedly. This prevents avoidable losses in

terms of energy as well as cost. For example, it would

Fig 4. Actual vs Predicted Consumption

Fig 5a. Pre Peak Load Shaving

Fig 5b. Post Peak Load Shaving

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uary

- M

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qua

rterly

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e of

the

soci

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of e

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y en

gin

eers

and

man

ager

s / I

ndia

10

Mr. Raviraj Kadiyala is a senior

consultant at Wipro EcoEnergy,

working in the field of energy

management services. His field of

work involves providing solutions to

organizations in sectors like

telecom, data centers and

commercial buildings across the

world to reduce and maintain

energy consumption/costs at

optimal levels.

max

imum

util

isat

ion

of m

eter

ed d

ata

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

11Dynamic operating environments can provide energy-

saving opportunities on a continuous basis. Analysis

of metered data on an ongoing basis would enable

organizations to leverage maximum potential at the

earliest opportunity (Figure 4). For example, it could

highlight spikes, anomalies in usage pattern, growth

or drop in energy consumption, changes in key

impacting parameters and so on.

be possible to determine the efficiencies of

equipment like UPS and computer room air

conditioning (CRAC) units using sub-metered data.

However, metrics like energy efficiency ratio (EER)

used for CRAC units would require monitoring of

other associated parameters as well.

Peak Shaving/Shifting

Metered data can help in the classification of peak

loads into critical and non-critical. This insight can

then be used to determine if any of the peak loads

can be shifted to non-peak hours or if non-critical

loads can be reduced (Figure 5) thereby helping in

decreasing peak load charges. With the demand for

energy increasing and supply lagging behind, utility

companies face the challenge of meeting peak

demand requirements. While augmenting their peak

supply capacity, some utility companies offer demand

response programmes that incentivize end users to

reduce their demand. Analysis of metered data and

peak shaving/shifting would also make facilities

eligible to claim incentives from such programmes.

Contract Demand

It is typical of organizations to forecast their business

growth and the associated energy requirements while

applying for a contract demand from utilities. And the

projected demand would be much more than what is

required presently. This unutilized capacity comes at

an additional recurring cost, which is justified by

many to be worth the hassle/risk of getting additional

capacity at short notice. However, it would be a

worthwhile exercise to periodically review the

predicted business growth and energy requirement. It

may so happen that, due to business decisions or

turbulent market conditions, the actual energy

requirement will be much lower than the predicted

figures. Even considering the lead time for procuring

additional capacity, such instances may warrant

releasing of excess capacity and make the exercise

cash positive. Metered data provides a strong basis

for analyzing the peak demand requirement and the

demand growth that has actually been seen over a

period of time to make this call.

Loss Reduction

Quality of power has a bearing on performance

reliability, efficiency and life of equipment. Many

It may so happen that, due to business

decisions or turbulent market conditions,

the actual energy requirement will be

much lower than the figures predicted

while applying for a contract demand.

Even considering the lead time for

procuring additional capacity, such

instances may warrant releasing of excess

capacity and make the exercise cash

positive.

meters allow monitoring of data points that enable

determination of power quality, like power factor and

harmonics. Enabling them could highlight problem

areas which could then be addressed appropriately.

Utility Meter Faults and Billing Errors

The availability of sub-metering on main lines enables

one to detect any fault in the main utility meters.

Though rare, a faulty utility meter could go

undetected especially if it has been so over a period

of time. Installation of sub-meters enables one to

detect existing problems as well any new ones that

may arise. With a granular view into consumption,

metered data can be used to compute utility charges

independently. This can then be used to verify the

correctness of received invoices and reconcile with

utility companies.

Billing at Multi-tenanted Sites

In multi-tenanted facilities, contracts could be in place

that charge based on occupied area and not

necessarily on energy consumption. Metered data

can be used by organizations to renegotiate for

contracts that either do billing more in line with their

actual consumption or restructure them so that the

tenants are charged based on actuals.

Emissions Reporting

One of the big challenges in reporting emissions is

collecting reliable data on energy consumption.

Metered data monitored through a central system not

only provide auditable data, but also dramatically

reduce the time required for data collection and

report preparation.

Metering and monitoring requires investment. And, at

times, it becomes difficult to justify it. Moreover, it has

also been seen that at places where investments

have already been made, the use of data is restricted

only to a limited subset. It is the author's hope that

readers of this article would be able to tap the full

value of benefits realizable from their metered data.

Acknowledgements

The author acknowledges with gratitude the guidance

of Mr. Ravi Meghani in writing this article.

Equipment Efficiency

With appropriate levels of sub-metering, it is possible

to determine the actual performing efficiency of

equipment. This not only tells whether the units are

performing at expected levels, but also brings to

attention any maintenance needs when efficiency

drops unexpectedly. This prevents avoidable losses in

terms of energy as well as cost. For example, it would

Fig 4. Actual vs Predicted Consumption

Fig 5a. Pre Peak Load Shaving

Fig 5b. Post Peak Load Shaving

met

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nd m

onito

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12 metering and monitoring -

enabling technologies to deliver energy efficiencyJasjeet Singh Hanjrah

Metering and monitoring are two key aspects

for measurement of energy consumption and

for the analysis of consumption behaviour.

While metering has a role in measuring

energy consumption, monitoring, as a first

step, helps to identify the key areas of

potential improvements. Data

analytics/business intelligence is another

area that tremendously helps distribution

utilities to perform data mining on metered

data and come up with consumer

consumption patterns. Based upon

measurements and analysis, remedial action

can be taken to achieve energy savings and

energy efficiency.

oday, our planet is trying hard to find solutions to Tsome of the most challenging environmental

problems like increasing carbon footprints and

concerns regarding sustainability and efficiency. The

most pressing need for any utility is to reduce the

carbon footprints while ensuring secure and reliable

supply of electricity. Moreover, the concern over

delivering energy with consistent reliability and

efficiency is not limited to a particular geographical

region. Such challenging environments re-emphasize

the norm 'what gets measured gets done' and

stresses upon the two key aspects for measuring

energy consumption and analyzing consumption

behaviour - Metering and Monitoring.

Monitoring is an integral area that contributes to

energy efficiency and is inevitably required to have

measurable results. This could be referred to as the

first step in pursuing the goal of saving kilo Watt

hours. Also, it is widely accepted that the energy

saved through optimization and efficient operation is

the greenest and cleanest energy 'produced', which is

referred to as 'negawatts'. Negawatts are known to

bring in significant amount of energy savings. A

recent IEE report found that rate payer-funded energy

efficiency and demand response programmes in the

United States in 2010 have saved enough negawatts

to power almost 10 million homes, representing

approximately 112 million Mega Watt hours (MWh) of

electricity.

A recent IEE report found that rate payer-

funded energy efficiency and demand

response programmes in the United

States in 2010 have saved enough

negawatts to power almost 10 million

homes, representing approximately 112

million MWh of electricity.

A close surveillance over domestic energy

usage can be done using an in-home

display (IHD), which helps to establish the

initial level of consumption and set a

target for achieving the negawatts. While

most appliances are marked with their

wattage, they rarely state how much

energy is getting wasted when they are in

the standby mode. Devices like the kill-a-

watt energy usage monitor lets you see

exactly where your electricity (and money)

is going and helps you focus on reducing

energy wastage at home.

A close surveillance over domestic energy usage can

be done using an in-home display (IHD). This not only

helps to establish the initial level of consumption, but

also helps to set up a target for achieving the

negawatts. This is applicable equally for domestic,

industrial and commercial consumers. There are

equipments that can continuously monitor the level of

consumption and can give us a beep sound if the

pre-defined usage limits are crossed. The HAN

(Home Automation) technology help consumers stay

aware of the energy consumption and also lends a

helping hand while making decisions from remote

locations (Smart home application interfaces help

through a web browser or smart phones).

There are devices available in the market, like the kill-

a-watt energy usage monitor, which help identify

energy wastage. While most appliances are marked

with their wattage, they rarely state how much energy

is getting wasted when they are in the standby mode.

The kill-a-watt lets you see exactly where your

electricity (and money) is going and helps you focus

on reducing energy wastage at home. Thus, it can be

concluded that while metering plays its own role in

measuring energy consumption, monitoring helps to

identify the key areas of potential improvements.

Metering is one of the key aspects for monitoring

energy consumption, discovering wastages or

met

erin

g a

nd m

onito

ring

– e

nab

ling

tech

nolo

gie

s to

del

iver

ene

rgy

effic

ienc

yJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

13

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

12 metering and monitoring -

enabling technologies to deliver energy efficiencyJasjeet Singh Hanjrah

Metering and monitoring are two key aspects

for measurement of energy consumption and

for the analysis of consumption behaviour.

While metering has a role in measuring

energy consumption, monitoring, as a first

step, helps to identify the key areas of

potential improvements. Data

analytics/business intelligence is another

area that tremendously helps distribution

utilities to perform data mining on metered

data and come up with consumer

consumption patterns. Based upon

measurements and analysis, remedial action

can be taken to achieve energy savings and

energy efficiency.

oday, our planet is trying hard to find solutions to Tsome of the most challenging environmental

problems like increasing carbon footprints and

concerns regarding sustainability and efficiency. The

most pressing need for any utility is to reduce the

carbon footprints while ensuring secure and reliable

supply of electricity. Moreover, the concern over

delivering energy with consistent reliability and

efficiency is not limited to a particular geographical

region. Such challenging environments re-emphasize

the norm 'what gets measured gets done' and

stresses upon the two key aspects for measuring

energy consumption and analyzing consumption

behaviour - Metering and Monitoring.

Monitoring is an integral area that contributes to

energy efficiency and is inevitably required to have

measurable results. This could be referred to as the

first step in pursuing the goal of saving kilo Watt

hours. Also, it is widely accepted that the energy

saved through optimization and efficient operation is

the greenest and cleanest energy 'produced', which is

referred to as 'negawatts'. Negawatts are known to

bring in significant amount of energy savings. A

recent IEE report found that rate payer-funded energy

efficiency and demand response programmes in the

United States in 2010 have saved enough negawatts

to power almost 10 million homes, representing

approximately 112 million Mega Watt hours (MWh) of

electricity.

A recent IEE report found that rate payer-

funded energy efficiency and demand

response programmes in the United

States in 2010 have saved enough

negawatts to power almost 10 million

homes, representing approximately 112

million MWh of electricity.

A close surveillance over domestic energy

usage can be done using an in-home

display (IHD), which helps to establish the

initial level of consumption and set a

target for achieving the negawatts. While

most appliances are marked with their

wattage, they rarely state how much

energy is getting wasted when they are in

the standby mode. Devices like the kill-a-

watt energy usage monitor lets you see

exactly where your electricity (and money)

is going and helps you focus on reducing

energy wastage at home.

A close surveillance over domestic energy usage can

be done using an in-home display (IHD). This not only

helps to establish the initial level of consumption, but

also helps to set up a target for achieving the

negawatts. This is applicable equally for domestic,

industrial and commercial consumers. There are

equipments that can continuously monitor the level of

consumption and can give us a beep sound if the

pre-defined usage limits are crossed. The HAN

(Home Automation) technology help consumers stay

aware of the energy consumption and also lends a

helping hand while making decisions from remote

locations (Smart home application interfaces help

through a web browser or smart phones).

There are devices available in the market, like the kill-

a-watt energy usage monitor, which help identify

energy wastage. While most appliances are marked

with their wattage, they rarely state how much energy

is getting wasted when they are in the standby mode.

The kill-a-watt lets you see exactly where your

electricity (and money) is going and helps you focus

on reducing energy wastage at home. Thus, it can be

concluded that while metering plays its own role in

measuring energy consumption, monitoring helps to

identify the key areas of potential improvements.

Metering is one of the key aspects for monitoring

energy consumption, discovering wastages or

met

erin

g a

nd m

onito

ring

– e

nab

ling

tech

nolo

gie

s to

del

iver

ene

rgy

effic

ienc

yJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

14

met

erin

g a

nd m

onito

ring

– e

nab

ling

tech

nolo

gie

s to

del

iver

ene

rgy

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ienc

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ary

- M

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h 2

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15

inefficiencies, detecting power theft and carving out

energy usage patterns as well as for measuring the

energy being produced at various generating stations.

While metering has been traditionally employed to

help distribution utilities in billing their consumers, the

concept of energy metering has taken a leap in the

world of smart metering and smart grids. In today's

era, there are various underlying enabling

technologies that help us to take corrective measures

and shift consumption patterns to realize energy

efficiency. A few of these enabling technologies would

be discussed here, but before we delve further into

this topic, the approach to achieve energy efficiency

should be defined.

The DMAIC approach (Figure 1) from the lean six

sigma methodology can be used to define the

approach towards realizing energy efficiency.

Define: Define your Negawatts - your target for

achieving energy savings.

Measure: Stay close to your meter/IHD to view daily

consumption. Smart meters help monitor

consumption data at every 15 min intervals.

Analyse: Look at your consumption patterns

(seasonal, holidays, weekdays and weekends) and

compare with previous months' and previous years'

patterns.

Improve: With the help of enabling technologies and

energy-efficient devices, improve on usage. Smart

meters help remote control of energy consumption.

Control: Stay in control for achieving positive results

and be responsive to demand response (DR) signals.

With constant feeding of remote signals, consumers

can achieve tight control over consumption.

Smart meters monitor consumption data

every 15/30/60 minute intervals and

facilitate identification of the heavy or

abrupt consumption time period. This also

enables distribution utilities to locate

energy theft by reconciling summated

register data with interval data of the smart

meters.

Enabling Technologies (Distribution and Retail)

Monitoring your consumption at the most granular

levels requires AMI or smart metering in place. As

mentioned before, smart meters monitor consumption

data every 15-/30-/60-minute intervals and facilitate

identification of the heavy or abrupt consumption time

period. This also enables distribution utilities to locate

energy theft by reconciling summated register data

with interval data of the smart meters.

Along with AMI, HAN and demand response help in

monitoring real-time consumption, and utilities can

reap the benefits by sending signals to reduce energy

consumption during peak periods. Consumers can

remote control (ON/OFF/DIM) home appliances with

the HAN application interface in their smart devices

such as cell phones. One can also limit energy usage

with pre-configured algorithms or by taking ad hoc

decisions.

Data analytics/business intelligence is another area

that tremendously helps distribution utilities to

perform data mining on metered data and come up

with consumer consumption patterns. Utilities can

compare the usage data of specific consumers with

those of their peers and find out anomalies, which

generally indicate theft. Smart analytics also help

individuals to identify their abnormal or heavy

consumption periods/patterns, for example, times of

the day, specific days (festivals, functions) and so on,

and take necessary measures to reduce the usage.

They can also replace inefficient or ageing appliances

to gain more savings on bills by achieving energy

efficiency, which is also made possible by smart data

analytics.

Distribution utilities can go a step further to make

consumers save energy by opening energy innovation

centres, wherein the public can take a close look at

the latest options in lighting, heating, ventilation and

air-conditioning. Utilities can also help commercial

and industrial (C&I) consumers to bring in energy

audit experts who can offer valuable tips and

feedback to reduce their energy consumption

significantly.

Taking a look at the corporate sector in India and

abroad, data centres are mammoth consumers of

electricity. Energy consumption is a critical concern

for IT organizations worldwide as the cost of

operating data centers increases due to the growing

use of computing devices and rising energy costs. To

compound these factors, data centers that were

considered state of the art just 5 years ago are now

lagging behind in energy-efficient technologies. The

PUE metric allows data centres to make decisions

Fig 1. The DMAIC approach towards energy efficiency

Mr. Jasjeet Singh Hanjrah is a senior

consultant with Capgemini's EUC

Centre of Excellence and a member

of the Global Smart Energy Services

team. He has more than 6 years of

experience in the fields of smart

metering, smart grids, sustainable

utilities and smart cities. He has

previously worked for many utility

industry majors including HCL,

Siemens, ABB and Ferranti.

that increase efficiency, helping to achieve optimum

data centre facility utilization. To collect PUE data,

various items can be monitored for potential energy

savings, which include UPS and distribution losses, IT

load electrical energy utilization, total electrical energy

utilization by PAC units in the data centre, electrical

energy utilization for running make-up air units for the

data centre, electrical energy utilization for cooling

the UPS room, electrical energy utilization at the

chiller plant and energy utilization with respect to data

centre usage and the lighting load.

Based upon measurements and analysis, remedial

action can be taken which may include paralleling the

UPS to increase utilization levels, thereby increasing

efficiency and reducing distribution losses; increasing

the PAC temperature set point from 20 to 24 °C;

implementing humidity controls as needed; managing

airflow inside the data centre and managing the load

spread across the data centre floor.

There is a compelling need to achieve energy

efficiency, for which smart metering and smart

monitoring are essential aspects not only for

distribution utilities but for individual consumers as

well. Enabling technologies might be at our disposal,

but action has to be triggered by the human brain.

Awareness is the key, and definite measures need to

be taken to reap the benefits of existing technologies

by utilizing the possibilities of various media to reach

out to the consumers.

Relevant Websites

1- The Institute for Energy Efficiency

http://iee.ucsb.edu/

2- Tata Power http://www.tatapower.com/

3- http://www.intel.com

Enabling technologies might be at our

disposal, but action has to be triggered by

the human brain. Awareness is the key,

and definite measures need to be taken to

reap the benefits of existing technologies.

met

erin

g a

nd m

onito

ring

– e

nab

ling

tech

nolo

gie

s to

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iver

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rgy

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- M

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14

met

erin

g a

nd m

onito

ring

– e

nab

ling

tech

nolo

gie

s to

del

iver

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rgy

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ienc

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nu

ary

- M

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h 2

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15

inefficiencies, detecting power theft and carving out

energy usage patterns as well as for measuring the

energy being produced at various generating stations.

While metering has been traditionally employed to

help distribution utilities in billing their consumers, the

concept of energy metering has taken a leap in the

world of smart metering and smart grids. In today's

era, there are various underlying enabling

technologies that help us to take corrective measures

and shift consumption patterns to realize energy

efficiency. A few of these enabling technologies would

be discussed here, but before we delve further into

this topic, the approach to achieve energy efficiency

should be defined.

The DMAIC approach (Figure 1) from the lean six

sigma methodology can be used to define the

approach towards realizing energy efficiency.

Define: Define your Negawatts - your target for

achieving energy savings.

Measure: Stay close to your meter/IHD to view daily

consumption. Smart meters help monitor

consumption data at every 15 min intervals.

Analyse: Look at your consumption patterns

(seasonal, holidays, weekdays and weekends) and

compare with previous months' and previous years'

patterns.

Improve: With the help of enabling technologies and

energy-efficient devices, improve on usage. Smart

meters help remote control of energy consumption.

Control: Stay in control for achieving positive results

and be responsive to demand response (DR) signals.

With constant feeding of remote signals, consumers

can achieve tight control over consumption.

Smart meters monitor consumption data

every 15/30/60 minute intervals and

facilitate identification of the heavy or

abrupt consumption time period. This also

enables distribution utilities to locate

energy theft by reconciling summated

register data with interval data of the smart

meters.

Enabling Technologies (Distribution and Retail)

Monitoring your consumption at the most granular

levels requires AMI or smart metering in place. As

mentioned before, smart meters monitor consumption

data every 15-/30-/60-minute intervals and facilitate

identification of the heavy or abrupt consumption time

period. This also enables distribution utilities to locate

energy theft by reconciling summated register data

with interval data of the smart meters.

Along with AMI, HAN and demand response help in

monitoring real-time consumption, and utilities can

reap the benefits by sending signals to reduce energy

consumption during peak periods. Consumers can

remote control (ON/OFF/DIM) home appliances with

the HAN application interface in their smart devices

such as cell phones. One can also limit energy usage

with pre-configured algorithms or by taking ad hoc

decisions.

Data analytics/business intelligence is another area

that tremendously helps distribution utilities to

perform data mining on metered data and come up

with consumer consumption patterns. Utilities can

compare the usage data of specific consumers with

those of their peers and find out anomalies, which

generally indicate theft. Smart analytics also help

individuals to identify their abnormal or heavy

consumption periods/patterns, for example, times of

the day, specific days (festivals, functions) and so on,

and take necessary measures to reduce the usage.

They can also replace inefficient or ageing appliances

to gain more savings on bills by achieving energy

efficiency, which is also made possible by smart data

analytics.

Distribution utilities can go a step further to make

consumers save energy by opening energy innovation

centres, wherein the public can take a close look at

the latest options in lighting, heating, ventilation and

air-conditioning. Utilities can also help commercial

and industrial (C&I) consumers to bring in energy

audit experts who can offer valuable tips and

feedback to reduce their energy consumption

significantly.

Taking a look at the corporate sector in India and

abroad, data centres are mammoth consumers of

electricity. Energy consumption is a critical concern

for IT organizations worldwide as the cost of

operating data centers increases due to the growing

use of computing devices and rising energy costs. To

compound these factors, data centers that were

considered state of the art just 5 years ago are now

lagging behind in energy-efficient technologies. The

PUE metric allows data centres to make decisions

Fig 1. The DMAIC approach towards energy efficiency

Mr. Jasjeet Singh Hanjrah is a senior

consultant with Capgemini's EUC

Centre of Excellence and a member

of the Global Smart Energy Services

team. He has more than 6 years of

experience in the fields of smart

metering, smart grids, sustainable

utilities and smart cities. He has

previously worked for many utility

industry majors including HCL,

Siemens, ABB and Ferranti.

that increase efficiency, helping to achieve optimum

data centre facility utilization. To collect PUE data,

various items can be monitored for potential energy

savings, which include UPS and distribution losses, IT

load electrical energy utilization, total electrical energy

utilization by PAC units in the data centre, electrical

energy utilization for running make-up air units for the

data centre, electrical energy utilization for cooling

the UPS room, electrical energy utilization at the

chiller plant and energy utilization with respect to data

centre usage and the lighting load.

Based upon measurements and analysis, remedial

action can be taken which may include paralleling the

UPS to increase utilization levels, thereby increasing

efficiency and reducing distribution losses; increasing

the PAC temperature set point from 20 to 24 °C;

implementing humidity controls as needed; managing

airflow inside the data centre and managing the load

spread across the data centre floor.

There is a compelling need to achieve energy

efficiency, for which smart metering and smart

monitoring are essential aspects not only for

distribution utilities but for individual consumers as

well. Enabling technologies might be at our disposal,

but action has to be triggered by the human brain.

Awareness is the key, and definite measures need to

be taken to reap the benefits of existing technologies

by utilizing the possibilities of various media to reach

out to the consumers.

Relevant Websites

1- The Institute for Energy Efficiency

http://iee.ucsb.edu/

2- Tata Power http://www.tatapower.com/

3- http://www.intel.com

Enabling technologies might be at our

disposal, but action has to be triggered by

the human brain. Awareness is the key,

and definite measures need to be taken to

reap the benefits of existing technologies.

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

17

Jan

uary

- M

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h 2

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16

in-circuit reliability of energy meters

Rajesh Nimare

Often, the root cause of poor reliability of

meters can be traced back to their poor

design or design with little or no head

room, compromise on component

selection and lack of controlled

manufacturing processes. The commonly

used procurement criterion of 'compliance

to metering standards', which prescribes

only the minimum requirements, does not

help in meter selection. This article

explains the impact of poor in-circuit

reliability of meters on customers and

utilit ies, explains the fundamentals of

reliability and concludes by helping

utilities to develop their own check list for

meter evaluation.

lectricity meters are ubiquitous in today's world Eand considering the importance of the electricity

they measure, it is absolutely necessary that they do

not fail. Unlike electro-mechanical meters, a well-

designed and well-manufactured electronic meter

generally does not wear out per se. But, in reality, the

percentage that fails exceeds 10% per year. Often,

the root cause of poor reliability of meters can be

traced back to their poor design or design with little

or no head room, compromise on component

selection and lack of controlled manufacturing

processes. The commonly used procurement criterion

of 'compliance to metering standards', which

prescribes only the minimum requirements, does not

help in meter selection. This article explains the

impact of poor in-circuit reliability of meters on

customers and the utility, explains the fundamentals

of reliability and concludes by helping utilities to

develop their own check list for meter evaluation.

Customer First

As an electricity customer, if you thought yourself

lucky if your meter is defective and you are getting a

zero-consumption or an average bill, think twice.

There is a bright chance that you will be levied a bill

in arrears to cover the billing based on average

consumption. This will be calculated based on the

maximum consumption measured in the 'window

months' after the meter is replaced. With consumption

increasing steadily, the arrears could run into several

tens of thousands of rupees. The duration for which

this charge would be levied will depend on whether

the new meter is installed after the 'season boundary'

and the time taken to change the meter. This leads to

a possibility of real-life disputes like, for example, if

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

17

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

16

in-circuit reliability of energy meters

Rajesh Nimare

Often, the root cause of poor reliability of

meters can be traced back to their poor

design or design with little or no head

room, compromise on component

selection and lack of controlled

manufacturing processes. The commonly

used procurement criterion of 'compliance

to metering standards', which prescribes

only the minimum requirements, does not

help in meter selection. This article

explains the impact of poor in-circuit

reliability of meters on customers and

utilit ies, explains the fundamentals of

reliability and concludes by helping

utilities to develop their own check list for

meter evaluation.

lectricity meters are ubiquitous in today's world Eand considering the importance of the electricity

they measure, it is absolutely necessary that they do

not fail. Unlike electro-mechanical meters, a well-

designed and well-manufactured electronic meter

generally does not wear out per se. But, in reality, the

percentage that fails exceeds 10% per year. Often,

the root cause of poor reliability of meters can be

traced back to their poor design or design with little

or no head room, compromise on component

selection and lack of controlled manufacturing

processes. The commonly used procurement criterion

of 'compliance to metering standards', which

prescribes only the minimum requirements, does not

help in meter selection. This article explains the

impact of poor in-circuit reliability of meters on

customers and the utility, explains the fundamentals

of reliability and concludes by helping utilities to

develop their own check list for meter evaluation.

Customer First

As an electricity customer, if you thought yourself

lucky if your meter is defective and you are getting a

zero-consumption or an average bill, think twice.

There is a bright chance that you will be levied a bill

in arrears to cover the billing based on average

consumption. This will be calculated based on the

maximum consumption measured in the 'window

months' after the meter is replaced. With consumption

increasing steadily, the arrears could run into several

tens of thousands of rupees. The duration for which

this charge would be levied will depend on whether

the new meter is installed after the 'season boundary'

and the time taken to change the meter. This leads to

a possibility of real-life disputes like, for example, if

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

18

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

19

you were away all the summer why should you pay

the hefty arrears and who will pay the arrears in case

of changed tenancy.

The Utility Too Suffers

On the flip side, the electricity distribution office in

your locality, whose primary job is to attend to outage

calls and line maintenance, with its aging workforce

and expanding customer base, has very few or no

resources for meter replacement. Replacing meters

involves a costly chain of back-office activities like

investment in meters; storage of meters under

standard, defined conditions; logistics; re-testing at

expensive meter test laboratories; warranty returns

and scrap management. At times, a meter defect like

a blown neutral results in a high voltage at the

customer's premises leading to burn-out of expensive

white goods. The aggrieved customer can sue the

utility and the already burdened utility engineers have

to attend court hearings, further worsening the

situation. Considering the present conservative

estimate of in-circuit meter failure of over 10% per

year, utilities are lucky if customers have thought of

improving meter reliability.

Who Loses?

What clearly emerges is that in-circuit failure of

electricity meters is a societal loss; its magnitude is

way higher than the cost of the meter or the electricity

it would have traded. Would you buy a local 'standard

compliant' music system or something of repute like

Sony when it is your money that is being spent?

Surely you would not want to build an electricity

infrastructure with unreliable meters that impact the

wider society. Utilities too realize the menace

associated with in-circuit failure of meters and try to

reduce their risk by a range of measures, for example,

demanding a prolonged warranty period (up to 10

years) to address the issue. However, such measures

have not yielded the expected results. Limited testing

facilities and technical specialists to establish the

cause of defects constrain utilities in making claims

At times, a meter defect like a blown

neutral results in a high voltage at the

customer's premises leading to burn-out

of expensive white goods. The aggrieved

customer can sue the utility and the

already burdened utility engineers have to

attend court hearings, further worsening

the situation.

under warranty. Therefore the question arises: can

utilities predict the performance of meters? Yes,

reliability engineering is all about that!

Need to Focus

Poor performance of meters causes customers to

lose trust in them and thus increases the liability a

utility faces. Hence, it is important that utilities create

a knowledge base on the reliability of metering assets

and use this knowledge for vendor evaluation and

meter procurement.

Utilities worldwide have identified in-circuit reliability

of meters as a key priority area (KPA) and have

created dedicated laboratories for evaluating

reliability, conducting failure analysis and running

sampling plans for meter procurement, a competitive

advantage. These plans are a well-kept secret.

The following sections review the fundamentals of

meter reliability, the vocabulary associated with it and

its measurement. Understanding an electronic meter's

block diagram should be a good starting point.

Components of an Energy Meter

The block diagram of an energy meter is shown in

Figure 1.

The key components of an energy meter that

determine its reliability are explained below:

Power supply

The power supply section comprises 35-40% of the

total component count in a meter, and its job is to

provide the regulated, low-voltage DC power needed

to drive the meter electronics. Being exposed to the

distribution network, the meter power supply has to

endure over/under voltage, sag/swell, transients,

resonance, switching surges and lightning impulses.

A meter reported 'dead' usually has the roots of its

failure in power supply failure, which accounts for

around 70% of all failures. Designers use high-

A meter reported 'dead' usually has the

roots of its failure in power supply failure,

which accounts for around 70% of all

cases. Designers use high-dissipation

resistors and voltage-clamping devices

such as pre-conditioners; however,

because they are costly and do not

directly add any value to compliance with

metering standards, this is often

neglected.

dissipation resistors and voltage-clamping devices

such as pre-conditioners; however, because they are

costly and do not directly add any value to

compliance with 'metering standards' (which define

the minimum criteria), this is often neglected.

Therefore, the entire power supply design continues

to be an area to examine while evaluating meter

reliability. There are two types of power supply used

in modern electronic meters: capacitor-based linear

power supply and switch mode power supply (SMPS).

Capacitor-based supplies use a capacitor divider

network to drop the input voltage (230 V) to a usable

value. An input capacitor, which experiences the

maximum stress, is the critical component in such

power supplies, and its rating (temperature, voltage)

determines the reliability of such meters. Utilities,

during procurement, should insist on the design

analysis of each component under stress.

Switch mode power supply (SMPS) is used in

advanced meters, which have higher power supply

requirements. In such designs, the supply voltage is

rectified, filtered and then switched to a high

frequency (to minimize transformer size) to create the

required low voltage which is further rectified and

filtered for powering up the meter. As the power

supply in the first stage is exposed to the electricity

supply, its endurance against voltage variation,

spikes, transients, dips and surges determines the

reliability of the energy meter.

Voltage transducer

Often a simple resistive divider is used to step down

the mains voltage to a measurable range. As the

long-term performance of the voltage divider depends

upon the selection of the resistor used, the utility

should critically examine this component to ensure

long-term performance.

Current transducer

Modern meters use either a miniature current

transformer or a shunt to step down the load current.

As the entire load current flows through the

transducer, the integrity of the current circuit is

important; it is important to take into consideration its

endurance during overload and short circuit. Often,

the no-power symbol appearing in a meter is due to

burning of the meter bus bar. As the current

transformer provides natural isolation between the

mains and the measurement circuit, its insulation

design should be examined for reliability. For designs

using a shunt as the current transducer, the method

of handling line surges and the transient load caused

by modern gadgets should be critically examined

during design evaluation.

Display

In modern meters, the display is invariably a liquid

crystal display (LCD); its performance depends upon

its specifications like tolerance to humidity and

temperature variation.

Real time clock (RTC)

The meter needs a battery backup to maintain the

clock running during transportation and power

outages. Usually the battery used for clock backup is

specified for performance during the off-power mode,

running to typically 2-4 years, and the shelf life of the

battery, which determines the product life. A utility

should evaluate the design of the RTC backup battery

to ensure that the meter is going to perform for the

committed duration. Derating the labelled

milliamperehour (mA-hr) of the battery is essential, as

there is a native variation of ±15% of its capacity

owing to the influence of ambient temperature.

Understanding Meter Performance: The 'Bathtub

Curve’

Over many years, and across a wide variety of

mechanical and electronic components and systems,

people have calculated empirical population failure

rates as the units age over time and have repeatedly

obtained a graph such as the one shown in Figure 2.

Because of the shape of this failure rate curve, it has

become widely known as the 'bathtub' curve.

Supply conditioning Power supply

Clock

Battery

Signal conditioning

Voltage transducer

Current transducer

Measurement

Display LCD

Storage (Memory)

Signal

Supply

conditioning

Fig 1. Block Diagram of an Energy Meter

in-c

ircui

t rel

iab

ility

of e

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y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

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azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

18

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

19

you were away all the summer why should you pay

the hefty arrears and who will pay the arrears in case

of changed tenancy.

The Utility Too Suffers

On the flip side, the electricity distribution office in

your locality, whose primary job is to attend to outage

calls and line maintenance, with its aging workforce

and expanding customer base, has very few or no

resources for meter replacement. Replacing meters

involves a costly chain of back-office activities like

investment in meters; storage of meters under

standard, defined conditions; logistics; re-testing at

expensive meter test laboratories; warranty returns

and scrap management. At times, a meter defect like

a blown neutral results in a high voltage at the

customer's premises leading to burn-out of expensive

white goods. The aggrieved customer can sue the

utility and the already burdened utility engineers have

to attend court hearings, further worsening the

situation. Considering the present conservative

estimate of in-circuit meter failure of over 10% per

year, utilities are lucky if customers have thought of

improving meter reliability.

Who Loses?

What clearly emerges is that in-circuit failure of

electricity meters is a societal loss; its magnitude is

way higher than the cost of the meter or the electricity

it would have traded. Would you buy a local 'standard

compliant' music system or something of repute like

Sony when it is your money that is being spent?

Surely you would not want to build an electricity

infrastructure with unreliable meters that impact the

wider society. Utilities too realize the menace

associated with in-circuit failure of meters and try to

reduce their risk by a range of measures, for example,

demanding a prolonged warranty period (up to 10

years) to address the issue. However, such measures

have not yielded the expected results. Limited testing

facilities and technical specialists to establish the

cause of defects constrain utilities in making claims

At times, a meter defect like a blown

neutral results in a high voltage at the

customer's premises leading to burn-out

of expensive white goods. The aggrieved

customer can sue the utility and the

already burdened utility engineers have to

attend court hearings, further worsening

the situation.

under warranty. Therefore the question arises: can

utilities predict the performance of meters? Yes,

reliability engineering is all about that!

Need to Focus

Poor performance of meters causes customers to

lose trust in them and thus increases the liability a

utility faces. Hence, it is important that utilities create

a knowledge base on the reliability of metering assets

and use this knowledge for vendor evaluation and

meter procurement.

Utilities worldwide have identified in-circuit reliability

of meters as a key priority area (KPA) and have

created dedicated laboratories for evaluating

reliability, conducting failure analysis and running

sampling plans for meter procurement, a competitive

advantage. These plans are a well-kept secret.

The following sections review the fundamentals of

meter reliability, the vocabulary associated with it and

its measurement. Understanding an electronic meter's

block diagram should be a good starting point.

Components of an Energy Meter

The block diagram of an energy meter is shown in

Figure 1.

The key components of an energy meter that

determine its reliability are explained below:

Power supply

The power supply section comprises 35-40% of the

total component count in a meter, and its job is to

provide the regulated, low-voltage DC power needed

to drive the meter electronics. Being exposed to the

distribution network, the meter power supply has to

endure over/under voltage, sag/swell, transients,

resonance, switching surges and lightning impulses.

A meter reported 'dead' usually has the roots of its

failure in power supply failure, which accounts for

around 70% of all failures. Designers use high-

A meter reported 'dead' usually has the

roots of its failure in power supply failure,

which accounts for around 70% of all

cases. Designers use high-dissipation

resistors and voltage-clamping devices

such as pre-conditioners; however,

because they are costly and do not

directly add any value to compliance with

metering standards, this is often

neglected.

dissipation resistors and voltage-clamping devices

such as pre-conditioners; however, because they are

costly and do not directly add any value to

compliance with 'metering standards' (which define

the minimum criteria), this is often neglected.

Therefore, the entire power supply design continues

to be an area to examine while evaluating meter

reliability. There are two types of power supply used

in modern electronic meters: capacitor-based linear

power supply and switch mode power supply (SMPS).

Capacitor-based supplies use a capacitor divider

network to drop the input voltage (230 V) to a usable

value. An input capacitor, which experiences the

maximum stress, is the critical component in such

power supplies, and its rating (temperature, voltage)

determines the reliability of such meters. Utilities,

during procurement, should insist on the design

analysis of each component under stress.

Switch mode power supply (SMPS) is used in

advanced meters, which have higher power supply

requirements. In such designs, the supply voltage is

rectified, filtered and then switched to a high

frequency (to minimize transformer size) to create the

required low voltage which is further rectified and

filtered for powering up the meter. As the power

supply in the first stage is exposed to the electricity

supply, its endurance against voltage variation,

spikes, transients, dips and surges determines the

reliability of the energy meter.

Voltage transducer

Often a simple resistive divider is used to step down

the mains voltage to a measurable range. As the

long-term performance of the voltage divider depends

upon the selection of the resistor used, the utility

should critically examine this component to ensure

long-term performance.

Current transducer

Modern meters use either a miniature current

transformer or a shunt to step down the load current.

As the entire load current flows through the

transducer, the integrity of the current circuit is

important; it is important to take into consideration its

endurance during overload and short circuit. Often,

the no-power symbol appearing in a meter is due to

burning of the meter bus bar. As the current

transformer provides natural isolation between the

mains and the measurement circuit, its insulation

design should be examined for reliability. For designs

using a shunt as the current transducer, the method

of handling line surges and the transient load caused

by modern gadgets should be critically examined

during design evaluation.

Display

In modern meters, the display is invariably a liquid

crystal display (LCD); its performance depends upon

its specifications like tolerance to humidity and

temperature variation.

Real time clock (RTC)

The meter needs a battery backup to maintain the

clock running during transportation and power

outages. Usually the battery used for clock backup is

specified for performance during the off-power mode,

running to typically 2-4 years, and the shelf life of the

battery, which determines the product life. A utility

should evaluate the design of the RTC backup battery

to ensure that the meter is going to perform for the

committed duration. Derating the labelled

milliamperehour (mA-hr) of the battery is essential, as

there is a native variation of ±15% of its capacity

owing to the influence of ambient temperature.

Understanding Meter Performance: The 'Bathtub

Curve’

Over many years, and across a wide variety of

mechanical and electronic components and systems,

people have calculated empirical population failure

rates as the units age over time and have repeatedly

obtained a graph such as the one shown in Figure 2.

Because of the shape of this failure rate curve, it has

become widely known as the 'bathtub' curve.

Supply conditioning Power supply

Clock

Battery

Signal conditioning

Voltage transducer

Current transducer

Measurement

Display LCD

Storage (Memory)

Signal

Supply

conditioning

Fig 1. Block Diagram of an Energy Meter

Zone I - the burn-in period

The rapidly declining part of the curve, referred to as

the burn-in period or infant mortality stage, is

characterized by failures due to inherent component

weaknesses and manufacturing defects. This relates

to the practical observations with new energy meters,

where there is a surge of complaints of meter failing

within a few months of meter installation. With the

passage of time, the failure rate drops. Given that this

is the predicted behaviour, quality meter

manufacturers follow 'burn-in' processes, where

selected components and circuit cards go through a

burn-in in the factory before they are integrated into

the product. In essence, the infant mortality, which is

inevitable, should be precipitated and created before

supply to the utilities to prevent expensive in-circuit

failure. Utilities should include an evaluation of the

manufacturing technique as part of their tender

evaluation programme.

Value-conscious utilities realize the importance of the

manufacturing process (which cannot be measured

by metering standard compliance alone); hence they

run a dedicated 'vendor manufacturing capability

evaluation programme'. A series of open-ended

questionnaires are sent to the prospective vendors.

The qualification based on the written statement is

followed by an inspection of the factory, where the

processes, facilities, quality of people, in-work quality

test plan and in-circuit failure figures (past) are

audited. Often utilities seek the assistance of industry

experts in the field of manufacturing, reliability and

QC to frame the entire vendor evaluation programme

so that society gets the bang for its buck.

Zone II - useful life stage

This stage is characterized by a constant failure rate

due to random failures. There are techniques

available to predict the constant failure rate, and

utilities should demand their prediction model from

meter vendors as part of their procurement process.

Before going for a large procurement, a utility should

verify the performance on a small pilot quantity. There

are third-party specialist companies that provide such

evaluation services; however, considering continuity

of business, it is important that utilities develop their

own reliability assessment facility.

Zone III - Wear out period

This stage is characterized by an increasing failure

rate because of meter aging and meter deterioration.

Because modern electronic meters are largely made

up of semiconductor devices that have no real short-

term wear-out mechanism, the existence of a Zone III

for electronic systems is a sort of grey area. Usually

this area refers to the failing of batteries and fading of

the LCD. For most electronic components, Zone III is

relatively flat.

Reliability Prediction Modeling

There is a variety of reliability prediction modeling

techniques, which are classified into five main

categories such as Similar Equipment Technique,

Similar Complexity Technique, Prediction by Function

Technique, Part Count Technique and Stress Analysis

Technique. Utilities should focus on the details of

each technique and its applicability during reliability

assessment.

Accelerated life cycle test

Highly accelerated life test (HALT) is a stress test for

assessing product reliability. It is commonly applied

to electronic equipment and is performed to identify

design weaknesses in equipment. Thus it reduces to

a large extent the probability of in-service failures.

Progressively more severe environmental stresses are

Progressively severe environmental

stresses are applied, building up to a level

significantly beyond what the equipment

will see in-service. By this method,

weaknesses can be identified using a

small number of samples in the shortest

possible time and at the least expense.

applied building up to a level significantly beyond

what the equipment will see in-service. By this

method, weaknesses can be identified using a small

number of samples (sometimes one or two, but

preferably at least five) in the shortest possible time

and at the least expense. A second function of HALT

is that it characterizes the equipment under test and

identifies the equipment's safe operating limits and

design margins. Data from HALT are therefore used

as a basis for the design of an optimal HASS or ESS

test, which is used to screen every piece of

production equipment for latent manufacturing

defects and defective components. HASS (or highly

accelerated stress screening) is an extension of HALT,

but is applied during production.

There are a number of reasons why the electricity

meter reliability is an important attribute for the utility,

including

A utility's reputation is very closely

related to the reliability of its installations. The more

reliable a meter is, the more likely the utility is to have

a favourable reputation.

High reliability is a

mandatory requirement for customer satisfaction.

While a reliable meter may not dramatically affect

customer satisfaction in a positive manner, an

unreliable meter is sure to affect customer

satisfaction negatively.

The replacement and repair costs

will negatively affect profits, as well as attracting

unwanted negative attention. Introducing reliability

analysis is an important step in taking corrective

action.

The life cycle cost analysis can prove

that even if one vendor's initial cost of purchase might

be higher, the overall lifetime cost is lower than a

competitor's because the former's meter requires

fewer repairs or less maintenance.

With competition in the

utility business, utilities worldwide publish their

predicted reliability numbers to help gain an

advantage over their competition who either do not

publish their numbers or have lower numbers.

Reputation:

Customer Satisfaction:

Warranty Costs:

Cost Analysis:

Competitive Advantage:

Mr. Rajesh Nimare is DGM,

Business Development with

Secure Meters Ltd. He is a

Certified Energy Auditor with

19+ years of experience in the

metering domain and has

closely involved in projects

like pre-payment electricity

metering system for Brunei

and AMI development project.

Fig 2. The 'Bathtub' Curve Depicting Failure Rate of Energy Meters over Time

Typical to a discussion of reliability is the concept of

the bathtub curve. As shown in Figure 2, the curve

can be broken up into three portions.

There is a surge of complaints of meter

failing within a few months of installation.

With the passage of time, the failure rate

drops. Given that this is the predicted

behaviour, quality meter manufacturers

follow 'burn-in' processes, where selected

components and circuit cards go through

a burn-in in the factory before they are

integrated into the product.

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

20

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

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ary

- M

arc

h 2

01

2a

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rterly

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azin

e of

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of e

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eers

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ndia

21

Zone I - the burn-in period

The rapidly declining part of the curve, referred to as

the burn-in period or infant mortality stage, is

characterized by failures due to inherent component

weaknesses and manufacturing defects. This relates

to the practical observations with new energy meters,

where there is a surge of complaints of meter failing

within a few months of meter installation. With the

passage of time, the failure rate drops. Given that this

is the predicted behaviour, quality meter

manufacturers follow 'burn-in' processes, where

selected components and circuit cards go through a

burn-in in the factory before they are integrated into

the product. In essence, the infant mortality, which is

inevitable, should be precipitated and created before

supply to the utilities to prevent expensive in-circuit

failure. Utilities should include an evaluation of the

manufacturing technique as part of their tender

evaluation programme.

Value-conscious utilities realize the importance of the

manufacturing process (which cannot be measured

by metering standard compliance alone); hence they

run a dedicated 'vendor manufacturing capability

evaluation programme'. A series of open-ended

questionnaires are sent to the prospective vendors.

The qualification based on the written statement is

followed by an inspection of the factory, where the

processes, facilities, quality of people, in-work quality

test plan and in-circuit failure figures (past) are

audited. Often utilities seek the assistance of industry

experts in the field of manufacturing, reliability and

QC to frame the entire vendor evaluation programme

so that society gets the bang for its buck.

Zone II - useful life stage

This stage is characterized by a constant failure rate

due to random failures. There are techniques

available to predict the constant failure rate, and

utilities should demand their prediction model from

meter vendors as part of their procurement process.

Before going for a large procurement, a utility should

verify the performance on a small pilot quantity. There

are third-party specialist companies that provide such

evaluation services; however, considering continuity

of business, it is important that utilities develop their

own reliability assessment facility.

Zone III - Wear out period

This stage is characterized by an increasing failure

rate because of meter aging and meter deterioration.

Because modern electronic meters are largely made

up of semiconductor devices that have no real short-

term wear-out mechanism, the existence of a Zone III

for electronic systems is a sort of grey area. Usually

this area refers to the failing of batteries and fading of

the LCD. For most electronic components, Zone III is

relatively flat.

Reliability Prediction Modeling

There is a variety of reliability prediction modeling

techniques, which are classified into five main

categories such as Similar Equipment Technique,

Similar Complexity Technique, Prediction by Function

Technique, Part Count Technique and Stress Analysis

Technique. Utilities should focus on the details of

each technique and its applicability during reliability

assessment.

Accelerated life cycle test

Highly accelerated life test (HALT) is a stress test for

assessing product reliability. It is commonly applied

to electronic equipment and is performed to identify

design weaknesses in equipment. Thus it reduces to

a large extent the probability of in-service failures.

Progressively more severe environmental stresses are

Progressively severe environmental

stresses are applied, building up to a level

significantly beyond what the equipment

will see in-service. By this method,

weaknesses can be identified using a

small number of samples in the shortest

possible time and at the least expense.

applied building up to a level significantly beyond

what the equipment will see in-service. By this

method, weaknesses can be identified using a small

number of samples (sometimes one or two, but

preferably at least five) in the shortest possible time

and at the least expense. A second function of HALT

is that it characterizes the equipment under test and

identifies the equipment's safe operating limits and

design margins. Data from HALT are therefore used

as a basis for the design of an optimal HASS or ESS

test, which is used to screen every piece of

production equipment for latent manufacturing

defects and defective components. HASS (or highly

accelerated stress screening) is an extension of HALT,

but is applied during production.

There are a number of reasons why the electricity

meter reliability is an important attribute for the utility,

including

A utility's reputation is very closely

related to the reliability of its installations. The more

reliable a meter is, the more likely the utility is to have

a favourable reputation.

High reliability is a

mandatory requirement for customer satisfaction.

While a reliable meter may not dramatically affect

customer satisfaction in a positive manner, an

unreliable meter is sure to affect customer

satisfaction negatively.

The replacement and repair costs

will negatively affect profits, as well as attracting

unwanted negative attention. Introducing reliability

analysis is an important step in taking corrective

action.

The life cycle cost analysis can prove

that even if one vendor's initial cost of purchase might

be higher, the overall lifetime cost is lower than a

competitor's because the former's meter requires

fewer repairs or less maintenance.

With competition in the

utility business, utilities worldwide publish their

predicted reliability numbers to help gain an

advantage over their competition who either do not

publish their numbers or have lower numbers.

Reputation:

Customer Satisfaction:

Warranty Costs:

Cost Analysis:

Competitive Advantage:

Mr. Rajesh Nimare is DGM,

Business Development with

Secure Meters Ltd. He is a

Certified Energy Auditor with

19+ years of experience in the

metering domain and has

closely involved in projects

like pre-payment electricity

metering system for Brunei

and AMI development project.

Fig 2. The 'Bathtub' Curve Depicting Failure Rate of Energy Meters over Time

Typical to a discussion of reliability is the concept of

the bathtub curve. As shown in Figure 2, the curve

can be broken up into three portions.

There is a surge of complaints of meter

failing within a few months of installation.

With the passage of time, the failure rate

drops. Given that this is the predicted

behaviour, quality meter manufacturers

follow 'burn-in' processes, where selected

components and circuit cards go through

a burn-in in the factory before they are

integrated into the product.

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

20

in-c

ircui

t rel

iab

ility

of e

nerg

y m

eter

sJa

nu

ary

- M

arc

h 2

01

2a

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azin

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ndia

21

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uary

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23

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uary

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22

hen Tektronix, a $1.1 billion global leader in Wtest, measurement and monitoring

instrumentation, scheduled a three-day energy audit,

Facilities and General Services Manager Joe Ohama

was pretty sure his groups would find opportunities to

save money. But he was surprised where they found

them. After participating in an energy audit at a sister

company that uncovered $365K in potential savings

from energy conservation and waste management

improvements, Ohama moved fast to schedule the

Tektronix audit.

"I looked at what it took to do the ‘kaizen,'" Ohama

said. "I had pretty much what I needed to do this in-

house and with Linc Facility Services, our facility

maintenance provider."

Tektronix had already been approached by Portland

General, its local utility, which was pulling together an

Industrial Energy Initiative through the Energy Trust of

Oregon, led by Strategic Energy Group. The goal was

to encourage 12 Oregon companies to come together

to share best practices related to industrial energy

usage. Ohama invited the group to be part of the

audit team, along with campus tenants.

In all, about 25 people assembled in Beaverton,

Oregon, for the three-day exercise. The group divided

into two teams-one to focus on electrical usage, one

hot and coldrunning savingsFluke

Energy audits do help in

finding opportunities to

save money, but it can

sometimes be surprising to

see where the audit team

finds these opportunities.

This article shows how

Tektronix, a global leader in

measurement and

monitoring instrumentation

discovered $510K in utility

savings in just three days.

The top areas of saving

included shutting down the

boiler in summer, foregoing

summer lawn watering,

turning off the fountain,

resetting chilled water to 45

°F and switching off PCs

during off hours.

charged with analyzing natural gas, water, waste and

everything else. Using a corporate energy audit

system for consistency, 72 hours later they had

identified $510K in estimated annual savings, with a

one-time investment of $233K. $378K of that annual

amount is possible in 2009. "We followed the audit

process, which breaks down all the different utilities,

and we focused in from there," Ohama says. "It's a

matter of looking at things on paper and going out

into the plant. It's a top down/bottom up approach."

Where they looked

This wasn't Tektronix's first energy audit, so some

easy areas of improvement that many companies find

had already been taken care of. "One of the biggest

things typically is lighting. We had done a lot of

lighting retrofits some time ago, so we didn't find as

much opportunity there." Even so, by updating a few

parts of their lighting management system and

hanging the settings, they still managed to identify an

additional $30K in annual savings. Where they did

find substantial savings was in their hot and chilled

water systems. "We're looking at actually shutting

down the boilers in the summertime," Ohama says.

"We have always run boilers and chillers 24/7. Now

we're doing some modifications that will allow us to

shut the boilers down in certain months, saving

Jan

uary

- M

arc

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01

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23

Jan

uary

- M

arc

h 2

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22

hen Tektronix, a $1.1 billion global leader in Wtest, measurement and monitoring

instrumentation, scheduled a three-day energy audit,

Facilities and General Services Manager Joe Ohama

was pretty sure his groups would find opportunities to

save money. But he was surprised where they found

them. After participating in an energy audit at a sister

company that uncovered $365K in potential savings

from energy conservation and waste management

improvements, Ohama moved fast to schedule the

Tektronix audit.

"I looked at what it took to do the ‘kaizen,'" Ohama

said. "I had pretty much what I needed to do this in-

house and with Linc Facility Services, our facility

maintenance provider."

Tektronix had already been approached by Portland

General, its local utility, which was pulling together an

Industrial Energy Initiative through the Energy Trust of

Oregon, led by Strategic Energy Group. The goal was

to encourage 12 Oregon companies to come together

to share best practices related to industrial energy

usage. Ohama invited the group to be part of the

audit team, along with campus tenants.

In all, about 25 people assembled in Beaverton,

Oregon, for the three-day exercise. The group divided

into two teams-one to focus on electrical usage, one

hot and coldrunning savingsFluke

Energy audits do help in

finding opportunities to

save money, but it can

sometimes be surprising to

see where the audit team

finds these opportunities.

This article shows how

Tektronix, a global leader in

measurement and

monitoring instrumentation

discovered $510K in utility

savings in just three days.

The top areas of saving

included shutting down the

boiler in summer, foregoing

summer lawn watering,

turning off the fountain,

resetting chilled water to 45

°F and switching off PCs

during off hours.

charged with analyzing natural gas, water, waste and

everything else. Using a corporate energy audit

system for consistency, 72 hours later they had

identified $510K in estimated annual savings, with a

one-time investment of $233K. $378K of that annual

amount is possible in 2009. "We followed the audit

process, which breaks down all the different utilities,

and we focused in from there," Ohama says. "It's a

matter of looking at things on paper and going out

into the plant. It's a top down/bottom up approach."

Where they looked

This wasn't Tektronix's first energy audit, so some

easy areas of improvement that many companies find

had already been taken care of. "One of the biggest

things typically is lighting. We had done a lot of

lighting retrofits some time ago, so we didn't find as

much opportunity there." Even so, by updating a few

parts of their lighting management system and

hanging the settings, they still managed to identify an

additional $30K in annual savings. Where they did

find substantial savings was in their hot and chilled

water systems. "We're looking at actually shutting

down the boilers in the summertime," Ohama says.

"We have always run boilers and chillers 24/7. Now

we're doing some modifications that will allow us to

shut the boilers down in certain months, saving

hot a

nd c

old

runn

ing

sav

ing

sJa

nu

ary

- M

arc

h 2

01

2a

qua

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e of

the

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ety

of e

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24

natural gas." Instead of keeping the plant's boilers

fired up, Ohama's group plans to switch to localized

hot water tank systems capable of running targeted

smaller applications. Annual savings-$133K "One of

the biggest audit findings was the benefit of pulling in

people from our different user groups," he says.

"Manufacturing, engineering-getting everyone in the

room at the same time. For example, we've always

run compressed air at 110 pounds. We thought our

users needed that much. But our users said, 'We

really only need 100 pounds.' Annual savings-$7K. We

did the same thing with chilled water for

environmental and machinery cooling, going from

43.5 °F to 45 °F." Annual savings-$20K. No area was

overlooked. Foregoing the company's fountain saves

$45K; not watering the grass in the summer saves

$48K. Optimizing and calibrating air handlers garners

$9K; resizing the exhaust fan saves $15K, replacing

cafeteria spray nozzles saves $2K.

How they did it

If many of Ohama's biggest savings came from

comparing supply vs. demand, many other

incremental savings came from tried-and-true best

practices.

w Ohama tracks power consumption by building per

day and tracks consumption on specific loads with

individual power loggers. This both identifies and

confirms energy savings.

- In particular, the teams identified an opportunity to

reduce kWh used by the cooling tower, by adding a

VFD. The VFD will drive the cooling towers in

accordance with load demand, at an annual

savings of $39K.

- Running a power logger on the air compressor

mentioned above allowed the team to calculate

how much they would save from a 10-pound

compression reduction.

- The team surveyed kWh consumption at multiple

motors and VFDs and calculated ROI gains from

modulating operation, instead of running at 100 %.

w Identifying new opportunities to optimize air

handlers. By incorporating some new tuning

procedures into the existing preventive

maintenance schedule and evaluating the

percentage of outside air being conditioned,

Ohama's team hopes to save an additional $18K

annually.

w The team will also optimize the Central Plant

Operations (CPO) chiller, saving $2.6K. To do this,

the team increased parameters on the chiller

controls, so they could stage down to the small

chiller and still carry the load at 45 degrees.

They'll stay this course until the chilled water flow

demand increases in the summer.

- Using thermal imagers, the team surveyed their

buildings for thermal loss, air leaks, and vent leaks,

turning up $3k of annual savings opportunities.

- They also used thermal imagers to scan electrical

panels, looking for hot spots that could indicate

high resistance or connector malfunctions that

manifest as wasted heat energy.

- This summer the team is considering raising indoor

building temperatures from the previous standard

72 °F to a higher 77 °F. Doing this will require

resetting building temperature sensors and

controls, using the building management system,

and conducting ambient air temperature

measurements.

Off and running

Tektronix Chief Financial Officer Chuck McLaughlin

was pleased with the results of the energy audit. "Joe

and the team took the time to set themselves up for

success, brought the right people together and asked

the tough questions. Their results will serve as a great

stretch goal for other companies as the energy audits

continue." Identifying $510K of estimated annual

savings is a solid accomplishment for three days of

focus. But Ohama's work isn't done. In the coming

months, Ohama will be helping other companies run

similar energy audits. Who knows what they'll find-or

where they'll find it.

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25free cooling: an energy

conservationmeasure

Balbir Singh and V K Sethi

The free-cooling concept has been

successfully implemented in

around 90 AC plants in BSNL,

Haryana, and has resulted in

considerable reduction in energy

consumption. The switch

room/equipment room in telephone

exchanges is cooled by pumping

cold air from outside through the

AC plant aided by the blowers of

package AC units.

free

cool

ing

: an

ener

gy

cons

erva

tion

mea

sure

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26

free

cool

ing

: an

ener

gy

cons

erva

tion

mea

sure

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27

ajority of air-conditioning systems are based on Mthe re-circulated air system, in which

irrespective of the outside ambient conditions, the

conditioned space/equipment area is to be

maintained at the desired temperature level. The

required fresh air and return air are cooled by

refrigeration compressors. All telephone exchanges,

big and small, function under controlled conditions

and are air conditioned. The temperature is required

to be maintained at a certain level throughout the

year. Major exchanges are temperature sensitive, and

temperature is required to be maintained in the range

of 23 ± 3°C. There are around 100 air-conditioning

plants in BSNL exchanges in the state of Haryana,

and the capacity of these plants normally ranges from

21 TR to 50 TR; the majority being of 21 TR. Air-

conditioning plants are bulk consumers of energy,

and there exists a great potential for energy

conservation. It is to be noted that even a decrease of

indoor temperature by 1°C results in an increase of

energy consumption by 4%.

The Concept

In northern India the outdoor temperature during

winter (November to February) is quite low. Such

favourable outside conditions can be utilized for

maintaining the switch room/equipment room

temperature by pumping cold air from the outside into

the equipment room through the plant room by

running the blowers of package AC units. This

concept is known as free cooling. The normal

temperature of the cool air at the canvas connection

of a package AC unit is 13-14°C. So, when the

outside temp is <14°C, then no package AC unit is

required to be run. When the outside temperature is

even up to 20°C, the temperature in the switch

room/equipment room can be maintained by pumping

more air.

Design and Methodology

wThe air flow (in cubic feet per minute, CFM)

requirement for free cooling for a particular AC

plant is calculated on the basis of average running

of the number of AC package units during the

The normal temperature of the cooled air

at the canvas connection of a package AC

unit is 13-14°C. When the outside temp is

<14°C, no package AC unit is required to

be run.

winter season; for example, one package unit

means 5000 CFM.

wFree air from the outside is pumped into the

package room and further supplied to the switch

room through the blowers of package AC units.

wThe hot air from the switch room is thrown out

using an exhaust fan/damper, or by keeping the

doors open if feasible.

wThe system can be manual or automatic.

Manual:

The free-cooling system is started manually, and the

dampers are adjusted accordingly. The system is

operated when the outside temperature is <20°C. The

components used are as follows: A 24 SWG GI duct

with a mechanical filter, a 600 mm axial fan, a

damper, a contactor, cables and so on.

Automatic:

Free cooling will start working as and when the

outside temperature goes below 20°C and will turn

OFF when the temperature inside the switch room is

below 25.5°C; also the compressors will turn ON only

when free cooling is not working due to any fault or

when outside conditions are not favourable. In this

system, the louvers of the inlet and outlet fans shall

work automatically with the thrust of the air. The

components used are as follows: A 24 SWG GI sheet

duct with a mechanical filter, a 600-mm diameter axial

fan, a 450 mm exhaust fan, dampers, louvers, digital

temperature controllers, contactors, relays, control

wiring and cables, and so on.

Implementation

Pilot automated project:

A pilot project has been undertaken with an

automated system at the telephone exchange

building, Yamuna Nagar, Haryana. The desired inside

temperature is 25°C.

Whenever the outside temperature is

below 20°C, the fresh air and exhaust air

fans start working, sensing the outside

ambient temperature through a

temperature sensor. This air is sucked in

by the package AC units and supplied into

the conditioned space, and is drawn out

by the exhaust fans.

In this project, 10,000 CFM air is required to cool the

conditioned space, that is, switch room/equipment

room containing C-DoT and OCB exchange

equipment. Two 5000 CFM fans with mechanical

filters and suitable duct work are provided to push the

air into the existing AC plant room, and four 18"

exhaust fans with shutters in the return air path are

provided to exhaust the air into the atmosphere.

Whenever the outside temperature is below 20°C, the

fresh air and exhaust air fans start working, sensing

the outside ambient temperature through a

temperature sensor. This forced air is sucked in by

the package AC units and supplied into the

conditioned space, where, after taking the heat of the

equipment, it is exhausted by the exhaust fans. A

temperature sensor is provided in the switch room so

that when the temperature is about to go below 25°C

the system stops and turns ON only when the

temperature is about to increase from the desired

value of 25°C. This also adds further energy savings

by switching off the inlet and outlet air fans.

The general layouts of the system with and without

free cooling are as shown in Figures 1 and 2,

respectively. The control circuit is shown in Figure 3.

Figure 1: Layout Plan of AC Plant at the telephone Exchange, Yamunanagar (air circuit normal)

Switch room

X-MISSION

BTS

OFFICE

AC PLANTCONDENSORS

OMC

OFFICE

GREEN (SUPPLY AIR)RED (RETURN AIR)BLACK ( CONDENSOR AIR CIRCUIT)RETURN AIR PATH

CONDENSOR

AC PACKAGFE

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ajority of air-conditioning systems are based on Mthe re-circulated air system, in which

irrespective of the outside ambient conditions, the

conditioned space/equipment area is to be

maintained at the desired temperature level. The

required fresh air and return air are cooled by

refrigeration compressors. All telephone exchanges,

big and small, function under controlled conditions

and are air conditioned. The temperature is required

to be maintained at a certain level throughout the

year. Major exchanges are temperature sensitive, and

temperature is required to be maintained in the range

of 23 ± 3°C. There are around 100 air-conditioning

plants in BSNL exchanges in the state of Haryana,

and the capacity of these plants normally ranges from

21 TR to 50 TR; the majority being of 21 TR. Air-

conditioning plants are bulk consumers of energy,

and there exists a great potential for energy

conservation. It is to be noted that even a decrease of

indoor temperature by 1°C results in an increase of

energy consumption by 4%.

The Concept

In northern India the outdoor temperature during

winter (November to February) is quite low. Such

favourable outside conditions can be utilized for

maintaining the switch room/equipment room

temperature by pumping cold air from the outside into

the equipment room through the plant room by

running the blowers of package AC units. This

concept is known as free cooling. The normal

temperature of the cool air at the canvas connection

of a package AC unit is 13-14°C. So, when the

outside temp is <14°C, then no package AC unit is

required to be run. When the outside temperature is

even up to 20°C, the temperature in the switch

room/equipment room can be maintained by pumping

more air.

Design and Methodology

wThe air flow (in cubic feet per minute, CFM)

requirement for free cooling for a particular AC

plant is calculated on the basis of average running

of the number of AC package units during the

The normal temperature of the cooled air

at the canvas connection of a package AC

unit is 13-14°C. When the outside temp is

<14°C, no package AC unit is required to

be run.

winter season; for example, one package unit

means 5000 CFM.

wFree air from the outside is pumped into the

package room and further supplied to the switch

room through the blowers of package AC units.

wThe hot air from the switch room is thrown out

using an exhaust fan/damper, or by keeping the

doors open if feasible.

wThe system can be manual or automatic.

Manual:

The free-cooling system is started manually, and the

dampers are adjusted accordingly. The system is

operated when the outside temperature is <20°C. The

components used are as follows: A 24 SWG GI duct

with a mechanical filter, a 600 mm axial fan, a

damper, a contactor, cables and so on.

Automatic:

Free cooling will start working as and when the

outside temperature goes below 20°C and will turn

OFF when the temperature inside the switch room is

below 25.5°C; also the compressors will turn ON only

when free cooling is not working due to any fault or

when outside conditions are not favourable. In this

system, the louvers of the inlet and outlet fans shall

work automatically with the thrust of the air. The

components used are as follows: A 24 SWG GI sheet

duct with a mechanical filter, a 600-mm diameter axial

fan, a 450 mm exhaust fan, dampers, louvers, digital

temperature controllers, contactors, relays, control

wiring and cables, and so on.

Implementation

Pilot automated project:

A pilot project has been undertaken with an

automated system at the telephone exchange

building, Yamuna Nagar, Haryana. The desired inside

temperature is 25°C.

Whenever the outside temperature is

below 20°C, the fresh air and exhaust air

fans start working, sensing the outside

ambient temperature through a

temperature sensor. This air is sucked in

by the package AC units and supplied into

the conditioned space, and is drawn out

by the exhaust fans.

In this project, 10,000 CFM air is required to cool the

conditioned space, that is, switch room/equipment

room containing C-DoT and OCB exchange

equipment. Two 5000 CFM fans with mechanical

filters and suitable duct work are provided to push the

air into the existing AC plant room, and four 18"

exhaust fans with shutters in the return air path are

provided to exhaust the air into the atmosphere.

Whenever the outside temperature is below 20°C, the

fresh air and exhaust air fans start working, sensing

the outside ambient temperature through a

temperature sensor. This forced air is sucked in by

the package AC units and supplied into the

conditioned space, where, after taking the heat of the

equipment, it is exhausted by the exhaust fans. A

temperature sensor is provided in the switch room so

that when the temperature is about to go below 25°C

the system stops and turns ON only when the

temperature is about to increase from the desired

value of 25°C. This also adds further energy savings

by switching off the inlet and outlet air fans.

The general layouts of the system with and without

free cooling are as shown in Figures 1 and 2,

respectively. The control circuit is shown in Figure 3.

Figure 1: Layout Plan of AC Plant at the telephone Exchange, Yamunanagar (air circuit normal)

Switch room

X-MISSION

BTS

OFFICE

AC PLANTCONDENSORS

OMC

OFFICE

GREEN (SUPPLY AIR)RED (RETURN AIR)BLACK ( CONDENSOR AIR CIRCUIT)RETURN AIR PATH

CONDENSOR

AC PACKAGFE

Er. Balbir Singh is the Chief

Engineer (E) at BSNL, Haryana and

Er. V.K.Sethi is the Sub Divisional

Engineer (E) at BSNL, Yamuna

Nagar.

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Switch room

X-MISSION

BTS

OFFICE

AC PLANTCONDENSORS

OMC

OFFICE

GREEN (FREE OUTER COLD AIR)RED (HEATED EXHAUST AIR)RETURN AIR PATHSECTION LINE

CONDENSORAC PACKAGE5000CFM AIR INLET FAN

450 M HOT AIR EXH. FAN

OUTER COLD AIR

Figure 2. Layout Plan of the AC Plant at the Telephone Exchange at Yamunanagar (Free Cooling)

TC-1

NEUTRAL

TC-2

FREE AIREXHAUST

OUTSIDE TEMP. SENSOR

INDOOR TEMP SENSOR

Figure 3: Temperature Controller for Free Air Cooling in Winter (Schematic Diagram)

Table 1: Energy Conservation Achieved in the AC Plants of BSNL, Haryana, by Means of Free Cooling

The free-cooling concept has been successfully

implemented in around 90 AC plants in BSNL,

Haryana. It has resulted in considerable reduction in

energy consumption, as detailed in Table 1:

From Table 1, it is observed that there is a huge

potential for energy conservation by using the free-

cooling concept. In our practical experience, it has

been observed that the actual operating period of the

free-cooling concept is around 4½ months.

In appreciation of the achievement in

energy conservation in the office buildings

sector, BSNL Haryana has won three

National Energy Conservation Awards in

2010.

Benefits

wReduction in compressor running hours.

wIncreased compressor life

wLower energy cost

wLower CO emission2

In appreciation of the achievement in energy

conservation in the office buildings sector, BSNL

Haryana has won three National Energy Conservation

Awards in 2010. The awards were presented by

Honorable Minister of Power, Mr. Shushil Kumar

Shinde, on 14 December, 2010.

Sr. No. Description Result

1 No. of AC plants in which the free-cooling concept is implemented 90

2 Reduction in running of package AC units (at least one package unit

of 7 TR in each plant) 7 TR × 90 = 630 TR

3 No of working hours (round the clock) 24 h

4 Power consumption 1.8 kW/TR

5 Period of operation of free cooling (October to March) - 90 days × 24 h

restricted to 3 months for calculations purpose = 2160 h

6 Reduction in energy consumption in units 630 × 1.8 × 2160

= 24,49,440 kWh

7 Units consumed for running the free-cooling system 1.50 × 90 × 24

@ 1.50 kW per free-cooling system (in units) = 3,240 kWh

(which is negligible)

Visit http://www.energyprofessional.in/magazine.php?category=5and click on Subscribe Now button

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Er. Balbir Singh is the Chief

Engineer (E) at BSNL, Haryana and

Er. V.K.Sethi is the Sub Divisional

Engineer (E) at BSNL, Yamuna

Nagar.

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Switch room

X-MISSION

BTS

OFFICE

AC PLANTCONDENSORS

OMC

OFFICE

GREEN (FREE OUTER COLD AIR)RED (HEATED EXHAUST AIR)RETURN AIR PATHSECTION LINE

CONDENSORAC PACKAGE5000CFM AIR INLET FAN

450 M HOT AIR EXH. FAN

OUTER COLD AIR

Figure 2. Layout Plan of the AC Plant at the Telephone Exchange at Yamunanagar (Free Cooling)

TC-1

NEUTRAL

TC-2

FREE AIREXHAUST

OUTSIDE TEMP. SENSOR

INDOOR TEMP SENSOR

Figure 3: Temperature Controller for Free Air Cooling in Winter (Schematic Diagram)

Table 1: Energy Conservation Achieved in the AC Plants of BSNL, Haryana, by Means of Free Cooling

The free-cooling concept has been successfully

implemented in around 90 AC plants in BSNL,

Haryana. It has resulted in considerable reduction in

energy consumption, as detailed in Table 1:

From Table 1, it is observed that there is a huge

potential for energy conservation by using the free-

cooling concept. In our practical experience, it has

been observed that the actual operating period of the

free-cooling concept is around 4½ months.

In appreciation of the achievement in

energy conservation in the office buildings

sector, BSNL Haryana has won three

National Energy Conservation Awards in

2010.

Benefits

wReduction in compressor running hours.

wIncreased compressor life

wLower energy cost

wLower CO emission2

In appreciation of the achievement in energy

conservation in the office buildings sector, BSNL

Haryana has won three National Energy Conservation

Awards in 2010. The awards were presented by

Honorable Minister of Power, Mr. Shushil Kumar

Shinde, on 14 December, 2010.

Sr. No. Description Result

1 No. of AC plants in which the free-cooling concept is implemented 90

2 Reduction in running of package AC units (at least one package unit

of 7 TR in each plant) 7 TR × 90 = 630 TR

3 No of working hours (round the clock) 24 h

4 Power consumption 1.8 kW/TR

5 Period of operation of free cooling (October to March) - 90 days × 24 h

restricted to 3 months for calculations purpose = 2160 h

6 Reduction in energy consumption in units 630 × 1.8 × 2160

= 24,49,440 kWh

7 Units consumed for running the free-cooling system 1.50 × 90 × 24

@ 1.50 kW per free-cooling system (in units) = 3,240 kWh

(which is negligible)

Visit http://www.energyprofessional.in/magazine.php?category=5and click on Subscribe Now button

Now pay online to subscribe to

Jan

ua

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rch

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n going through the annual administration report Oof Kerala State Electricity Board (KSEB) for

2009-10, it is learnt that during this period the T&D

loss came down to 19.41% from 20.45% (1.04%

reduction) in the previous year [1]. This was achieved

through the execution of the following improvement

works: commissioning of 266.4 km of EHT lines, 25

EHT sub-stations, 3398 km of HT lines, 7838 km of LT

lines and 5790 distribution transformers.

The system load factor of KSEB during 2009-10 was

65%, which is very low as compared to the other

southern states of India (see Table 1) [2]. Nothing is

seen mentioned in the report regarding measures to

improve the load factor. In this context, it is

worthwhile to make a study of the impact of system

load factor on T&D loss reduction and the

consequent increase in profitability of power utilities,

with a focus on the Kerala system.

Here it is attempted to make a theoretical study of the

impact of system load factor on T&D losses.

Ideal System Loss (Ld)

The ideal condition of loading of a system occurs

when the load factor is 100%.

Let us consider a case in which a uniform apparent

power of X units flows for a time period T, such that

the energy consumption for the period is Q units.

Load Factor = 100%

Energy consumption = Q units

Average apparent power = X units

Current, I = X/E (where E is a

constant that depends

on voltage etc.)

System loss depends on apparent power and not on

active power.

2System loss = D × I ×T (where D is

a constant that depends

on system parameters

such as Impedance etc.)

2= D × (X/E) × T

2= (D/E ) × (average 2apparent power) ×

time period

= K × (average apparent 2power) × time period

2(where K = D/E )

This is the minimum possible system loss for any

given time period and the given system parameters.

impact ofsystem load factor

on T&D lossesK K Babu

The system load factor of the Kerala

State Electricity Board (KSEB) during

2009-10 was 65%, which is very low

as compared to the other southern

states of India. It is worthwhile to

make a study of the impact of system

load factor on transmission and

distribution (T&D) loss reduction and

the consequent increase in

profitability of power utilities, with a

focus on the Kerala system. The study

shows that an annual savings up to

Rs.99.2894 crores can be achieved

through improvement in load factor.

Jan

ua

ry -

Ma

rch

2012

a q

uarte

rly m

agaz

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of th

e so

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y of

ene

rgy

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inee

rs a

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/ Ind

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imp

act o

f sys

tem

load

fact

or o

n T&

D lo

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n going through the annual administration report Oof Kerala State Electricity Board (KSEB) for

2009-10, it is learnt that during this period the T&D

loss came down to 19.41% from 20.45% (1.04%

reduction) in the previous year [1]. This was achieved

through the execution of the following improvement

works: commissioning of 266.4 km of EHT lines, 25

EHT sub-stations, 3398 km of HT lines, 7838 km of LT

lines and 5790 distribution transformers.

The system load factor of KSEB during 2009-10 was

65%, which is very low as compared to the other

southern states of India (see Table 1) [2]. Nothing is

seen mentioned in the report regarding measures to

improve the load factor. In this context, it is

worthwhile to make a study of the impact of system

load factor on T&D loss reduction and the

consequent increase in profitability of power utilities,

with a focus on the Kerala system.

Here it is attempted to make a theoretical study of the

impact of system load factor on T&D losses.

Ideal System Loss (Ld)

The ideal condition of loading of a system occurs

when the load factor is 100%.

Let us consider a case in which a uniform apparent

power of X units flows for a time period T, such that

the energy consumption for the period is Q units.

Load Factor = 100%

Energy consumption = Q units

Average apparent power = X units

Current, I = X/E (where E is a

constant that depends

on voltage etc.)

System loss depends on apparent power and not on

active power.

2System loss = D × I ×T (where D is

a constant that depends

on system parameters

such as Impedance etc.)

2= D × (X/E) × T

2= (D/E ) × (average 2apparent power) ×

time period

= K × (average apparent 2power) × time period

2(where K = D/E )

This is the minimum possible system loss for any

given time period and the given system parameters.

impact ofsystem load factor

on T&D lossesK K Babu

The system load factor of the Kerala

State Electricity Board (KSEB) during

2009-10 was 65%, which is very low

as compared to the other southern

states of India. It is worthwhile to

make a study of the impact of system

load factor on transmission and

distribution (T&D) loss reduction and

the consequent increase in

profitability of power utilities, with a

focus on the Kerala system. The study

shows that an annual savings up to

Rs.99.2894 crores can be achieved

through improvement in load factor.

imp

act o

f sys

tem

load

fact

or o

n T&

D lo

sses

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That means, it is the Ideal system loss.

So, ideal system loss, Ld = K × (average apparent 2power) × time period (1)

Also, system loss if apparent maximum demand (MD)

is maintained during the time period

2= K × (apparent MD) ×

time period (2)

Note that Ld changes when there is any change in the

constant K.

The Actual Loss can be worked out based

on the relation between load factor (G ) L

and loss factor (G ). In fact, loss factor is V

the 'load factor of losses'. It is defined as

the ratio of actual energy loss during a

particular period to the energy loss

assuming peak apparent demand

throughout the period.

Load Factor and Loss Factor

In actual practice, ideal loading never occurs and the

actual system loss will be more than Ld. Losses in

series elements are related to the square of the

current flow. It is possible to establish a relationship

between peak demand on a system and the average

technical losses, through consideration of load factor

(G ) and loss factor (G ).L V

The Actual Loss can be worked out based on the

relation between G and G . In fact, loss factor is the L V

'load factor of losses'. It is defined as the 'ratio of

actual energy loss during a particular period to the

energy loss assuming peak apparent demand

throughout the period'.

G = Energy loss over a time period ÷ (Power V

loss at apparent MD × the time period)

G = Energy consumed over a time period ÷ L

(MD × the time period)

According to the Electrical Engineering Hand Book

published by SIEMENS, (the relevant extract is given

below) we get the following relation [3]:

1.6G = (G )V L

[Extract from Electrical Engineering Handbook

published by SIEMENS

Section 8.1, Network Parameters, pp 356-357.]

Load Factor and Loss Factor

G = A /P t load factorL u max

G = A /V t loss factorV V max

P : maximum transmitted power (peak load) in MW max

in a certain period,

t : duration of the period in hours,

A : energy transmitted in time t in MWh,u

V : loss power at apparent load power Smmax ax,

A : energy loss in time tV

No simple curve, which is correct for every case,

exists for the relation G = f(G ), because of the effect V L

of power factor and load fluctuation. The bandwidth is 1-2given by the relation G = (G ) . The index 1 is valid V L

for a load diagram which only contains the values P

= P and P = 0. A load diagram for index 2 would max

have the power P during a very short period of max

time, while a constant load would exist during the rest

of the time. The emphasized curve can be used with

sufficient accuracy under most practical conditions

(approximately corresponding to an index of 1.6)].

Now,G = Energy consumed over a time L

period ÷ (MD × the time period)= Average apparent power ÷

Apparent MD

2(G ) = (Average apparent power) ÷ L

2(Apparent MD)

= [K × (Average apparent 2power) × Time period] ÷

2[K × (Apparent MD) × Time period]

= Ideal loss over a time period

(L ) ÷ (Energy loss if apparent MD is d

maintained over the time period)

G = Energy loss over a time period ÷ V

(Power loss at apparent MD × the

time period)

= Actual system loss over a time

period ÷ (Energy loss if apparent MD

is maintained over the time period)

2G /(G ) = Actual loss over a time period ÷ V L

Ideal loss over the same time period

= Actual loss ÷ Ideal loss (L )d

2So, Actual loss = L × [ G /(G ) ]d V L

1.6But, we know that G = (G )V L

1.6 2So, Actual Loss = L × [(G ) /(G ) ]d L L

0.4= L × [1/(G ) ] d L

Now, Actual loss L 1

0.4at load factor G = L × [1/(G ) ]L1 d L1

Actual loss L 2

0.4at load factor G = L × [1/(G ) ]L2 d L2

0.4 So, L /L = (G /G )1 2 L2 L1

Impact of Load Factor on Profitability

From the Annual Report for 2009-10 of Southern

Regional Power Committee (under CEA), Bangalore,

the statistics with regard to the southern states of

India can be obtained, which is presented in Table 1.

From Table 1, it is observed that the system load

factor of Kerala for 2009-10 is 65%, while those of

other southern states are much higher. A load factor

of 80% can be taken as the target. The T&D loss of

Kerala during 2009-10 was 19.41%. Now, let us see

what would have been the T&D loss, if the load factor

were improved to 80%.

2

Andhra Karnataka Kerala Tamil Nadu Pondicherry Southern

Pradesh Region

Annual Load Factor (%) 78 70 65 83 77 81

Source: SRPC (2010) Annual Report 2009-2010 of Southern Region Power Committee. Bangalore, India: Southern Region Power Committee

(under CEA). www.srpc.kar.nic.in

Table 1. Annual Average Load Factor of the Southern States of India

Loss Factor as a function of Load Factor

1.0

0.8

0.6

0.4

0.2

00.2 0.4 0.6 0.8 1.0

GV

GV = GL

GV = GL( (2

Practical Condition

GL

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That means, it is the Ideal system loss.

So, ideal system loss, Ld = K × (average apparent 2power) × time period (1)

Also, system loss if apparent maximum demand (MD)

is maintained during the time period

2= K × (apparent MD) ×

time period (2)

Note that Ld changes when there is any change in the

constant K.

The Actual Loss can be worked out based

on the relation between load factor (G ) L

and loss factor (G ). In fact, loss factor is V

the 'load factor of losses'. It is defined as

the ratio of actual energy loss during a

particular period to the energy loss

assuming peak apparent demand

throughout the period.

Load Factor and Loss Factor

In actual practice, ideal loading never occurs and the

actual system loss will be more than Ld. Losses in

series elements are related to the square of the

current flow. It is possible to establish a relationship

between peak demand on a system and the average

technical losses, through consideration of load factor

(G ) and loss factor (G ).L V

The Actual Loss can be worked out based on the

relation between G and G . In fact, loss factor is the L V

'load factor of losses'. It is defined as the 'ratio of

actual energy loss during a particular period to the

energy loss assuming peak apparent demand

throughout the period'.

G = Energy loss over a time period ÷ (Power V

loss at apparent MD × the time period)

G = Energy consumed over a time period ÷ L

(MD × the time period)

According to the Electrical Engineering Hand Book

published by SIEMENS, (the relevant extract is given

below) we get the following relation [3]:

1.6G = (G )V L

[Extract from Electrical Engineering Handbook

published by SIEMENS

Section 8.1, Network Parameters, pp 356-357.]

Load Factor and Loss Factor

G = A /P t load factorL u max

G = A /V t loss factorV V max

P : maximum transmitted power (peak load) in MW max

in a certain period,

t : duration of the period in hours,

A : energy transmitted in time t in MWh,u

V : loss power at apparent load power Smmax ax,

A : energy loss in time tV

No simple curve, which is correct for every case,

exists for the relation G = f(G ), because of the effect V L

of power factor and load fluctuation. The bandwidth is 1-2given by the relation G = (G ) . The index 1 is valid V L

for a load diagram which only contains the values P

= P and P = 0. A load diagram for index 2 would max

have the power P during a very short period of max

time, while a constant load would exist during the rest

of the time. The emphasized curve can be used with

sufficient accuracy under most practical conditions

(approximately corresponding to an index of 1.6)].

Now,G = Energy consumed over a time L

period ÷ (MD × the time period)= Average apparent power ÷

Apparent MD

2(G ) = (Average apparent power) ÷ L

2(Apparent MD)

= [K × (Average apparent 2power) × Time period] ÷

2[K × (Apparent MD) × Time period]

= Ideal loss over a time period

(L ) ÷ (Energy loss if apparent MD is d

maintained over the time period)

G = Energy loss over a time period ÷ V

(Power loss at apparent MD × the

time period)

= Actual system loss over a time

period ÷ (Energy loss if apparent MD

is maintained over the time period)

2G /(G ) = Actual loss over a time period ÷ V L

Ideal loss over the same time period

= Actual loss ÷ Ideal loss (L )d

2So, Actual loss = L × [ G /(G ) ]d V L

1.6But, we know that G = (G )V L

1.6 2So, Actual Loss = L × [(G ) /(G ) ]d L L

0.4= L × [1/(G ) ] d L

Now, Actual loss L 1

0.4at load factor G = L × [1/(G ) ]L1 d L1

Actual loss L 2

0.4at load factor G = L × [1/(G ) ]L2 d L2

0.4 So, L /L = (G /G )1 2 L2 L1

Impact of Load Factor on Profitability

From the Annual Report for 2009-10 of Southern

Regional Power Committee (under CEA), Bangalore,

the statistics with regard to the southern states of

India can be obtained, which is presented in Table 1.

From Table 1, it is observed that the system load

factor of Kerala for 2009-10 is 65%, while those of

other southern states are much higher. A load factor

of 80% can be taken as the target. The T&D loss of

Kerala during 2009-10 was 19.41%. Now, let us see

what would have been the T&D loss, if the load factor

were improved to 80%.

2

Andhra Karnataka Kerala Tamil Nadu Pondicherry Southern

Pradesh Region

Annual Load Factor (%) 78 70 65 83 77 81

Source: SRPC (2010) Annual Report 2009-2010 of Southern Region Power Committee. Bangalore, India: Southern Region Power Committee

(under CEA). www.srpc.kar.nic.in

Table 1. Annual Average Load Factor of the Southern States of India

Loss Factor as a function of Load Factor

1.0

0.8

0.6

0.4

0.2

00.2 0.4 0.6 0.8 1.0

GV

GV = GL

GV = GL( (2

Practical Condition

GL

(ABT) regime, there will be a monetary benefit if

there is any reduction in demand during the low-

frequency period.

Action Plan for Achieving Loss Reduction by

Improvement of System Load Factor

Load factor can be improved only by flattening of the

load curve. It can be done only by limiting the evening

peak and by creating additional demand during off-

peak periods.

A detailed and in-depth study is needed for

implementing appropriate measures to improve the

load factor and thus reduce the system loss.

References

1. KSEB (2010) Annual Administration Report 2009-2010 of Kerala

State Electricity Board. Trivandrum, India: Kerala State Electricity

Board.

2. SRPC (2010) Annual Report 2009-2010 of Southern Region

Power Committee. Bangalore, India: Southern Region Power

Committee (under CEA). www.srpc.kar.nic.in.

3. SIEMENS (1981) Electrical Engineering Handbook. New Delhi,

India: New Age International (P) Limited.

We know that

0.4L /L = (G /G )1 2 L2 L1

0.4So, L = L × (G /G )2 I L1 L2

T&D Loss at 65%

load factor, L = 19.41% (i.e., 0.1941) 1

Suppose the load factor is improved to 80%

T&D loss at 80% 0.4load factor, L = L × (G /G )2 I L1 L2

0.4 = 0.1941 × (0.65/0.80)= 0.1941 × 0.920 = 0.1786 (i.e., 17.86%)

Reduction in T&D Loss = (19.41 - 17.86)%= 1.55%

Annual energy sold = 14,047.75 M.U.

during 2009-10 (million units)

Annual reduction in

T&D Loss = 217.74 M.U.

Per unit cost of energy = Rs. 4.56

Annual Savings due to improvement in load factor =

Rs.99.2894 Crores

Additional Savings Due to Improvement in Load

Factor

1. Capacity enhancement of the system (generation,

transmission and distribution) is usually

necessitated to meet the evening peak demand. If

load factor is improved, evening peak will be

reduced and consequently there will be savings

due to the reduction in capital investment.

2. The frequency will usually be low during the

evening peak. Under the availability-based tariff

Capacity enhancement of the system

(generation, transmission and distribution)

is usually necessitated to meet the

evening peak demand. If load factor is

improved, evening peak will be reduced

and consequently there will be savings

due to the reduction in capital investment.

Load factor can be improved only by

flattening of the load curve. It can be done

only by limiting the evening peak and by

creating additional demand during off-

peak periods.

Mr. K. K. Babu, MSEEM is a former

Deputy Chief Engineer of the Kerala

State Electricity Board. He has

30 years of experience in Design,

Planning, Construction, Operation and

Maintenance of various Electrical

Installations (LT, HT & EHT). He has

also actively involved in Energy Audits,

Grid Management, Load Generation

Balance and Water Management.

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code optimization technique:an approach towards

energy efficient computingSoujanya Nemalikanti and Polavarapu Sindhura

Moving towards a 'greener' era of

computing, it is the need of the hour to

consider high-performance systems that

are energy efficient and thereby are lesser

heat and carbon emitters. The conventional

approach, on software grounds, includes

redefining algorithms that focus on the

reduction of time complexity and space

complexity of programmes. The authors

propose a novel approach that takes into

consideration power optimization, with

respect to making an algorithm more

energy-efficient.

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code optimization technique:an approach towards

energy efficient computingSoujanya Nemalikanti and Polavarapu Sindhura

Moving towards a 'greener' era of

computing, it is the need of the hour to

consider high-performance systems that

are energy efficient and thereby are lesser

heat and carbon emitters. The conventional

approach, on software grounds, includes

redefining algorithms that focus on the

reduction of time complexity and space

complexity of programmes. The authors

propose a novel approach that takes into

consideration power optimization, with

respect to making an algorithm more

energy-efficient.

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o begin with, 'green' computing is defined as "the Tstudy and practice of designing, manufacturing,

using, and disposing of computers, servers, and

associated subsystems - such as monitors, printers,

storage devices, and networking and communications

systems - efficiently and effectively with minimal or no

impact on the environment." This definition was

proposed by Samir Botros in Green Technology and

Design for the Environment [1].

With the advent of novel technologies to address

complex problems in the world of computation, the

focal point, to a large extent, remains to be the

performance factor, marring the consequences that it

renders to the milieu around in the form of carbon

and heat emissions affecting humans and the

environment equally. Thence is the yearning for eco-

friendly alternatives that consume less units of power

for execution and also save your money.

Case Studies

1. Fine-grained green computing

'Fine-grained green computing' refers to running a

programme efficiently and effectively via a subtle

power control on each computing resource such as

CPU, memory, registers, peripherals, clock and power

supply. A simple power cut as a whole, like in coarse-

grained green computing, yields less leverage on

manipulating energy consumption in light of the

characteristics and the context of a specific

application. Table 1 shows a green-computing version

of the 'Hello World' programme with respect to the

coarse-grained and the fine-grained green-computing

methodologies. The code on the left shows a coarse-

grained green-computing programme in which the

programme's execution is in the full-power mode,

disregarding whether the program is using memory

Fine-grained green computing' refers to

running a programme efficiently and

effectively via a subtle power control on

each computing resource such as CPU,

memory, registers, peripherals, clock and

power supply. A simple power cut as a

whole, like in coarse-grained green

computing, yields less leverage on

manipulating energy consumption in light

of the characteristics and the context of a

specific application.

banks or I/O peripherals. Note that the system is set

to the full-power mode when an external event occurs

such as a key pressing or a peripheral interrupt.

Therefore, on entry into the programme, the system is

assumed to be in the full-power mode [2].

With fine-grained green computing (the code on the

right-hand side of Table 1), only the required memory

banks and I/O peripherals are activated for the

programme. The number of memory banks that

should be activated and the I/O peripherals that

should be turned on really depend on the underlying

application. This approach allows energy

consumption of the system components to be fine-

tuned, and will further reduce power consumption, as

low-power modes do for the CPU alone.

2. Power-aware merge algorithm

Components other than CPU will require another

control unit in the system. However, this will increase

the complexity of the design, and some algorithms

may have to be redesigned to achieve this objective.

Note that it seems plausible that the green code at

the right-hand side of Table 1 involves a higher

number of instructions and thus consumes more

power. Actually, it is the idle power consumption that

makes the non-green code drain more current than

the green code.

A big portion of power consumption is attributed to

the memory in which programmes and their data are

stored. Thus, a compact design of code and data

structures is a key to power reduction. For example, a

regular merge sort algorithm will waste about 50% of

memory space in storing sub-type elements, as in the

A big portion of power consumption is

attributed to the memory in which

programmes and their data are stored.

Thus, a compact design of code and data

structures is a key to power reduction.

case of, say, a 32-bit CPU sorting 16-bit short

integers. Two problems arise: First, it doubles the

memory space requirement to store the data, and,

therefore, it may not take advantage of turning off

unused memory banks to save power. Second, it

requires two times more memory loads than if the

data were to be sorted in a compact form, for

example, two short integers are stored in a 32-bit

memory space. Table 2 illustrates a power-aware

merge algorithm that reduces memory power

consumption and size by 50%, and increases

programme efficiency by eliminating a half of the

lengthy memory accesses (assuming that all auto

variables i, j, k and n can be allocated to registers).

The idea of the power-aware merge algorithm is to

pack two short integers into one word, which is the

basic unit for the CPU, when loading data into

registers. Each load instruction will actually load two

short integers. The operations of this merge algorithm

are similar to those of a traditional one. The only

difference is the three 'if' statements to check whether

the indices have reached 2.

The asymptotic time complexity will remain the same,

that is, O(n), but the actual run time will be shorter if

m > 4, where m is the number of times the memory

access is slower as compared to CPU instructions.

The following depicts the time complexity of the

merge algorithm of the original version and that of the

power-aware version shown in Table 2.

T (n) = nm + n

T'(n) = nm/2 + 3n

Table 1: A Green-Computing Version of the 'Hello World' Program for

Coarse-Grained (Left) and Fine-Grained (Right) Green Computing

Programme HelloWorld_c Programme HelloWorld_f

print "Hello World\n" activate(memory_bank)

low_power_mode() activate(io)

print "Hello World\n"

deactivate(memory_bank)

deactivate(io)

low_power_mode()

Table 2: A Power-Aware Merge Algorithm for Memory Power and Size

Reduction

Merge (A, L, R)

n = k = 0;

i = j = 2;

while(not (empty(L) or empty(R))) {

if (i = 2)

W1 = head(L);

i = 0;

if (j = 2)

W2 = head(R);

j = 0;

if (W1[i] > W2[j])

w[k++] = W2[j++];

else

w[k++] = W1[j++];

if k = 2

A[n++] = w;

k = 0;

end of while

// append the rest of lists to A

if (notempty(L)) append L to A

elseif (notempty(R)) append R to A

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o begin with, 'green' computing is defined as "the Tstudy and practice of designing, manufacturing,

using, and disposing of computers, servers, and

associated subsystems - such as monitors, printers,

storage devices, and networking and communications

systems - efficiently and effectively with minimal or no

impact on the environment." This definition was

proposed by Samir Botros in Green Technology and

Design for the Environment [1].

With the advent of novel technologies to address

complex problems in the world of computation, the

focal point, to a large extent, remains to be the

performance factor, marring the consequences that it

renders to the milieu around in the form of carbon

and heat emissions affecting humans and the

environment equally. Thence is the yearning for eco-

friendly alternatives that consume less units of power

for execution and also save your money.

Case Studies

1. Fine-grained green computing

'Fine-grained green computing' refers to running a

programme efficiently and effectively via a subtle

power control on each computing resource such as

CPU, memory, registers, peripherals, clock and power

supply. A simple power cut as a whole, like in coarse-

grained green computing, yields less leverage on

manipulating energy consumption in light of the

characteristics and the context of a specific

application. Table 1 shows a green-computing version

of the 'Hello World' programme with respect to the

coarse-grained and the fine-grained green-computing

methodologies. The code on the left shows a coarse-

grained green-computing programme in which the

programme's execution is in the full-power mode,

disregarding whether the program is using memory

Fine-grained green computing' refers to

running a programme efficiently and

effectively via a subtle power control on

each computing resource such as CPU,

memory, registers, peripherals, clock and

power supply. A simple power cut as a

whole, like in coarse-grained green

computing, yields less leverage on

manipulating energy consumption in light

of the characteristics and the context of a

specific application.

banks or I/O peripherals. Note that the system is set

to the full-power mode when an external event occurs

such as a key pressing or a peripheral interrupt.

Therefore, on entry into the programme, the system is

assumed to be in the full-power mode [2].

With fine-grained green computing (the code on the

right-hand side of Table 1), only the required memory

banks and I/O peripherals are activated for the

programme. The number of memory banks that

should be activated and the I/O peripherals that

should be turned on really depend on the underlying

application. This approach allows energy

consumption of the system components to be fine-

tuned, and will further reduce power consumption, as

low-power modes do for the CPU alone.

2. Power-aware merge algorithm

Components other than CPU will require another

control unit in the system. However, this will increase

the complexity of the design, and some algorithms

may have to be redesigned to achieve this objective.

Note that it seems plausible that the green code at

the right-hand side of Table 1 involves a higher

number of instructions and thus consumes more

power. Actually, it is the idle power consumption that

makes the non-green code drain more current than

the green code.

A big portion of power consumption is attributed to

the memory in which programmes and their data are

stored. Thus, a compact design of code and data

structures is a key to power reduction. For example, a

regular merge sort algorithm will waste about 50% of

memory space in storing sub-type elements, as in the

A big portion of power consumption is

attributed to the memory in which

programmes and their data are stored.

Thus, a compact design of code and data

structures is a key to power reduction.

case of, say, a 32-bit CPU sorting 16-bit short

integers. Two problems arise: First, it doubles the

memory space requirement to store the data, and,

therefore, it may not take advantage of turning off

unused memory banks to save power. Second, it

requires two times more memory loads than if the

data were to be sorted in a compact form, for

example, two short integers are stored in a 32-bit

memory space. Table 2 illustrates a power-aware

merge algorithm that reduces memory power

consumption and size by 50%, and increases

programme efficiency by eliminating a half of the

lengthy memory accesses (assuming that all auto

variables i, j, k and n can be allocated to registers).

The idea of the power-aware merge algorithm is to

pack two short integers into one word, which is the

basic unit for the CPU, when loading data into

registers. Each load instruction will actually load two

short integers. The operations of this merge algorithm

are similar to those of a traditional one. The only

difference is the three 'if' statements to check whether

the indices have reached 2.

The asymptotic time complexity will remain the same,

that is, O(n), but the actual run time will be shorter if

m > 4, where m is the number of times the memory

access is slower as compared to CPU instructions.

The following depicts the time complexity of the

merge algorithm of the original version and that of the

power-aware version shown in Table 2.

T (n) = nm + n

T'(n) = nm/2 + 3n

Table 1: A Green-Computing Version of the 'Hello World' Program for

Coarse-Grained (Left) and Fine-Grained (Right) Green Computing

Programme HelloWorld_c Programme HelloWorld_f

print "Hello World\n" activate(memory_bank)

low_power_mode() activate(io)

print "Hello World\n"

deactivate(memory_bank)

deactivate(io)

low_power_mode()

Table 2: A Power-Aware Merge Algorithm for Memory Power and Size

Reduction

Merge (A, L, R)

n = k = 0;

i = j = 2;

while(not (empty(L) or empty(R))) {

if (i = 2)

W1 = head(L);

i = 0;

if (j = 2)

W2 = head(R);

j = 0;

if (W1[i] > W2[j])

w[k++] = W2[j++];

else

w[k++] = W1[j++];

if k = 2

A[n++] = w;

k = 0;

end of while

// append the rest of lists to A

if (notempty(L)) append L to A

elseif (notempty(R)) append R to A

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where T(n) is the time complexity of the original

algorithm and T'(n) is that of the power-aware

algorithm.

However, the energy complexity for the original

version is 2 times as much as that of the power-aware

version if the data memory is much larger than the

programme memory. Therefore, it is necessary to

perform fine-grained tuning of the power consumption

of an algorithm. To reap that benefit, an algorithm will

typically be redesigned.

Similarly, when green computing is applied to

operating systems, especially its scheduler would

have to handle per-process requirements in order to

optimally control all peripherals in terms of power

consumption. If dynamic voltage scaling (DVS) were

to be added, the scheduler would have to consider

CPU power supply in light of the deadlines and

priorities of a task. Often there are situations where

lower voltage may end up consuming more power for

completing a task. Perhaps, the most difficult task is

to find where to sneak in green computing and how it

improves system performance.

A Novel Approach

There are two possible domains in which the study

can progress: One is software, and the other

hardware. On the grounds of software issues, there

are four approaches with reference to a typical

C/C++ programme, for instance. Source code and

instruction-level optimizations appear to be an

alternative in low power consumption analysis [3-5].

First, the use of some special operators in the source

code can contribute remarkably towards lowering

power consumption during its execution. This

technique is termed as 'algorithmic transformation'.

These special operators include:

1. Shorthand operators like +=, *=, /=, %=, -=, &=,

|=, ^=, ~=, <<= and >=

2. Increment/Decrement operators like ++, --. For

example, the assignment instruction n = n + 1 can

be replaced with the increment operator n++ or ++n

requiring only two cycles as against by the former that

requires three cycles for that instruction.

3. Tertiary operators like the conditional operator (test

condition ? expr1:expr2, syntactically) instead of

larger blocks of compound statements like 'If-elseif-

else' to compute a selection-based task.

Second, the use of operands from the registers rather

than from the memory will prove to be an appreciable

deal. An instruction using register operands costs up

to 300 mA of current per cycle, whereas the memory

read/write operations cost in the range of 430-530 mA

per cycle. Since the register set is limited and hence

cannot be used for applications with larger memory

requirement, the next alternative is seen in the form of

storing operands using caches. Further, the code

transformations available in recent scenarios help

improve the cache hit ratios and make it a better

option as compared to registers. This technique is

associated with memory management, as illustrated

by Tiwari et al. [6].

An instruction using register operands

costs up to 300 mA of current per cycle,

whereas the memory read/write operations

cost in the range of 430-530 mA per cycle.

Since the register set is limited and hence

cannot be used for applications with larger

memory requirement, the next alternative

is seen in the form of storing operands

using caches.

The use of inline functions has a

significant impact on power requirement.

In function inlining, the body of a function

is inserted directly into the code structure

where it is used.

Third, the technique of loop unrolling is being

considered. Loop unrolling is an optimization

technique where the body of a loop is copied several

times. This prevents the amount of power consumed

in the overhead otherwise caused during the change

in control flow due to loop transformations and

iterations. Since loop unrolling has been shown to

yield good results in terms of low power consumption

for the Intel 8051 platform in previous literature, there

seems to be a good sign for the validity of this

approach, as demonstrated by Ortiz and Santiago

[7].

Fourth, the use of inline functions has a significant

impact on power requirement. In function inlining, the

body of a function is inserted directly into the code

structure where it is used. Also, variable declaration is

used to replace variable types used in other methods,

which tend to lower power consumption [8].

There are several important works on source code-

level optimization. Source code-level optimization for

execution time has been studied extensively by

Leupers [9]. Leupers [9] and Sharma and Ravikumar

[10] classified source code optimization techniques

as machine-independent and machine-dependent. In

terms of source code optimization for power

reduction, Simunic et al. [11] classified code

optimization techniques into algorithmic, data-flow

and instruction-flow optimization. In our study, we

used algorithmic optimization since it does not take

into consideration the target platform. Dalal and

Ravikumar [3] studied software-dependent

components such as arithmetic circuits, data busses

and memories, as a way to lower power consumption

in embedded applications. Sharma and Ravikumar

[10] presented a study of the implementation of the

ADPCM codec benchmark. In this work, optimization

techniques applied at the source code level were

classified into structural and machine-dependent

optimization.

Tool Talk

MATLAB software serves as an apposite tool for the

analysis of the subject being researched here. The

following are a few relevant utilities available in this

tool.

1. Code Analyzer Report: It displays potential errors

and problems, as well as opportunities for

improvement, in MATLAB programmes. It displays a

message for each line of MATLAB code and

determines how it might be improved. For example, a

common message is that a variable is defined but

never used, as shown in Figure 1. By performing the

cod

e op

timiz

atio

n te

chni

que

: an

app

roac

h to

war

ds

ener

gy

effic

ient

com

put

ing

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

40

cod

e op

timiz

atio

n te

chni

que

: an

app

roac

h to

war

ds

ener

gy

effic

ient

com

put

ing

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

41

where T(n) is the time complexity of the original

algorithm and T'(n) is that of the power-aware

algorithm.

However, the energy complexity for the original

version is 2 times as much as that of the power-aware

version if the data memory is much larger than the

programme memory. Therefore, it is necessary to

perform fine-grained tuning of the power consumption

of an algorithm. To reap that benefit, an algorithm will

typically be redesigned.

Similarly, when green computing is applied to

operating systems, especially its scheduler would

have to handle per-process requirements in order to

optimally control all peripherals in terms of power

consumption. If dynamic voltage scaling (DVS) were

to be added, the scheduler would have to consider

CPU power supply in light of the deadlines and

priorities of a task. Often there are situations where

lower voltage may end up consuming more power for

completing a task. Perhaps, the most difficult task is

to find where to sneak in green computing and how it

improves system performance.

A Novel Approach

There are two possible domains in which the study

can progress: One is software, and the other

hardware. On the grounds of software issues, there

are four approaches with reference to a typical

C/C++ programme, for instance. Source code and

instruction-level optimizations appear to be an

alternative in low power consumption analysis [3-5].

First, the use of some special operators in the source

code can contribute remarkably towards lowering

power consumption during its execution. This

technique is termed as 'algorithmic transformation'.

These special operators include:

1. Shorthand operators like +=, *=, /=, %=, -=, &=,

|=, ^=, ~=, <<= and >=

2. Increment/Decrement operators like ++, --. For

example, the assignment instruction n = n + 1 can

be replaced with the increment operator n++ or ++n

requiring only two cycles as against by the former that

requires three cycles for that instruction.

3. Tertiary operators like the conditional operator (test

condition ? expr1:expr2, syntactically) instead of

larger blocks of compound statements like 'If-elseif-

else' to compute a selection-based task.

Second, the use of operands from the registers rather

than from the memory will prove to be an appreciable

deal. An instruction using register operands costs up

to 300 mA of current per cycle, whereas the memory

read/write operations cost in the range of 430-530 mA

per cycle. Since the register set is limited and hence

cannot be used for applications with larger memory

requirement, the next alternative is seen in the form of

storing operands using caches. Further, the code

transformations available in recent scenarios help

improve the cache hit ratios and make it a better

option as compared to registers. This technique is

associated with memory management, as illustrated

by Tiwari et al. [6].

An instruction using register operands

costs up to 300 mA of current per cycle,

whereas the memory read/write operations

cost in the range of 430-530 mA per cycle.

Since the register set is limited and hence

cannot be used for applications with larger

memory requirement, the next alternative

is seen in the form of storing operands

using caches.

The use of inline functions has a

significant impact on power requirement.

In function inlining, the body of a function

is inserted directly into the code structure

where it is used.

Third, the technique of loop unrolling is being

considered. Loop unrolling is an optimization

technique where the body of a loop is copied several

times. This prevents the amount of power consumed

in the overhead otherwise caused during the change

in control flow due to loop transformations and

iterations. Since loop unrolling has been shown to

yield good results in terms of low power consumption

for the Intel 8051 platform in previous literature, there

seems to be a good sign for the validity of this

approach, as demonstrated by Ortiz and Santiago

[7].

Fourth, the use of inline functions has a significant

impact on power requirement. In function inlining, the

body of a function is inserted directly into the code

structure where it is used. Also, variable declaration is

used to replace variable types used in other methods,

which tend to lower power consumption [8].

There are several important works on source code-

level optimization. Source code-level optimization for

execution time has been studied extensively by

Leupers [9]. Leupers [9] and Sharma and Ravikumar

[10] classified source code optimization techniques

as machine-independent and machine-dependent. In

terms of source code optimization for power

reduction, Simunic et al. [11] classified code

optimization techniques into algorithmic, data-flow

and instruction-flow optimization. In our study, we

used algorithmic optimization since it does not take

into consideration the target platform. Dalal and

Ravikumar [3] studied software-dependent

components such as arithmetic circuits, data busses

and memories, as a way to lower power consumption

in embedded applications. Sharma and Ravikumar

[10] presented a study of the implementation of the

ADPCM codec benchmark. In this work, optimization

techniques applied at the source code level were

classified into structural and machine-dependent

optimization.

Tool Talk

MATLAB software serves as an apposite tool for the

analysis of the subject being researched here. The

following are a few relevant utilities available in this

tool.

1. Code Analyzer Report: It displays potential errors

and problems, as well as opportunities for

improvement, in MATLAB programmes. It displays a

message for each line of MATLAB code and

determines how it might be improved. For example, a

common message is that a variable is defined but

never used, as shown in Figure 1. By performing the

cod

e op

timiz

atio

n te

chni

que

: an

app

roac

h to

war

ds

ener

gy

effic

ient

com

put

ing

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

42

Ms. Soujanya

Nemalikanti and Ms.

Polavarapu Sindhura

are affiliated to the

Department of

Information Science

and Technology,

Koneru Lakshmaih

University,

Vaddeswaram, Guntur.

suggested transformations, lesser number of cycles

will be needed to execute the instructions.

2. Improving Performance Using the Profiler: MATLAB

Profiler helps you improve the performance of your

MATLAB programmes. Run a MATLAB statement or

any programme file in the Profiler, and it produces a

report of where the time is being spent (see Figure 2).

The Profiler can be accessed from the Desktop menu,

or the profile function can be used.

an unexpected and remarkable manner. In the near

future, the urge for eco-friendly solutions in

computing shall be on the rise, and so will be the

advancement in the relevant technology. In the

domain of software engineering, there is an

imperative requirement for the genesis of power-

aware algorithms and such transformations at the

instruction and source-code levels to optimize the

energy efficiency of a given software product, thereby

making it a 'green' software.

References

1. Botros S. (1996) Green Technology and Design for the

Environment, 3rd edn. New York: McGraw-Hill.

2. Grochowski E. and Annavaram M. Energy per instruction trends in

Intel® microprocessors, available at

http://support.intel.co.jp/pressroom/kits/core2duo/pdf/epi-trends-

final2.pdf.

3. Dalal V. and Ravikumar C.P. (2001) Software power optimizations in

an embedded system. Fourteenth International Conference on VLSI

Design, January 2001. pp. 254-59.

4. Oliver J., Mocanu O. and Ferrer C. (2003) Energy awareness

through software optimization as a performance estimate case study

of the MC68HC908GP32 microcontroller. Fourth International

Workshop on Microprocessor Test and Verification: Common

Challenges and Solutions, May 2003. pp. 111-16.

5. Yingbiao Y., Qingdong Y., Peng L. and Zhibin X. (2004) Embedded

software optimization for MP3 decoder implemented on RISC core.

IEEE Transactions on Consumer Electronics, 50(4):1244-49.

6. Tiwari V., Malik S. and Wolfe A. (1994) Compilation techniques for

low energy: An overview. Digest of Technical Papers, IEEE

Symposium on Low Power Electronics at San Diego, CA, USA, 10-12

October 1994. pp. 38-39.

7. Ortiz D.A. and Santiago N.G. (2007) High-level optimization for low

power consumption on microprocessor-based systems. Fiftieth IEEE

International Midwest Symposium on Circuits and Systems

(MWSCAS'07), August 2007. pp. 1265-68.

8. Zambreno J., Kandemir M.T. and Choudhary A. (2002) Enhancing

compiler techniques for memory energy optimizations. Embedded

Software. Second International Conference, EMSOFT 2002,

2491:364-81.

9. Leupers R. (2000) Code Optimization Techniques for Embedded

Processors. Dordrecht, NL: Kluwer Academic Publishers.

10. Sharma A. and Ravikumar C.P. (2000) Efficient implementation of

ADPCM codec. Thirteenth International Conference on VLSI Design,

January 2000. pp. 456-61.

11. Simunic T., Benini L. and de Micheli G. (2001) Energy-efficient

design of battery-powered embedded systems. IEEE Transactions on

Very Large Scale Integration Systems, 9(1):15-28.

Figure 1: A snapshot of the Code Analyzer in the MATLAB Tool

This is an indirect approach for power optimization.

The segment of the code that consumes the

maximum time for its execution, as depicted by the

profiler, can be modified so that it consumes lesser

number of time cycles for execution. This can

contribute to a lowering of the amount of power

consumed and thus to the fulfilment of our objective.

The contemporary developments towards a greener

epoch of computing have so far gained momentum in

Figure 2: This Utility in MATLAB Renders the Time Statistics Per

Instruction of the Input Code.

Jan

uary

- M

arc

h 2

01

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charring-briquetting:

a novel cookingfuel technology

Nema B P

Organic material can be charred and crushed into powder, which

can then be mixed with a binder and briquetted into compact solid

fuel like charcoal. The char briquettes are equivalent to charcoal in

burning characteristics and combustion efficiency. The Central

Institute of Agricultural Engineering (CIAE), Bhopal, has designed

and developed a high-capacity charring kiln, which can take a

charge of 100 kg crop residues in one run, yielding about 35-40 kg

of good quality char, and a power-operated briquetting machine,

which is basically a full-screw horizontal extruder machine similar to

plastic extruders/food product extruders.

Table 1: Brief Specifications of the CIAE-Developed Charring Kiln and

Briquetting Machine.

CIAE charring kiln

Overall length 1100 mm

Overall diameter 800 mm

Material of construction MS sheets (3 mm),

MS flat (35 × 5) and

rod (12 mm dia)

Weight 75-80 kg

Capacity (char output) 80 kg/day

CIAE power-operated briquetting machine

Overall length 1.6 m

Overall width 3.0 m

Overall height 1.0 m

Size of the prime mover 3.75 kW electric motor

Barrel diameter 21 cm

Barrel Length 42 cm

No of screws 1

Pitch of the screw 20.7 cm

No of exit tubes 5

Length of the exit tube 7 cm

Diameter of the exit tube 3 cm

Power transmission Through belt and pulley

Jan

uary

- M

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01

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rterly

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azin

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44

char

ring

–briq

uetti

ng: a

nov

el c

ooki

ng fu

el te

chno

log

y

char

ring

–briq

uetti

ng: a

nov

el c

ooki

ng fu

el te

chno

log

y

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

45

n rural areas fuel wood, cow dung and crop waste Iare used as kitchen fuel. Apart from these, people

use twigs, hard stalk/straw and so on, as such, to

build fire for cooking and heating. These fuels have

low heat output per unit of fuel used and release a lot

of gases harmful for human health. Over the above,

charcoal is a preferred fuel because it produces a

hot, long-lasting, virtually smokeless fire. In earlier

days, people were using the charcoal obtained from

partially burnt wood remaining at the end of the

routine cooking process. There also existed a practice

of turning powdery coal into balls for use as fuel.

Nevertheless, biofuels accounted for 80% of their

kitchen energy needs.

In rural areas, according to one expert's opinion, in

coming years there will be sufficient food but

insufficient fuel to cook the food, as the rate of

In the years to come, there will be

sufficient food but insufficient fuel to cook

the food in rural areas as well as among

the urban poor, which can be attributed to

the higher rate of deforestation as

compared to that of afforestation.

deforestation is very high in comparison to the

afforestation rate. The rural population is unable to

shift to commercial fuels due to their low purchasing

power and the limited availability of commercial fuels.

Urban poor (25-30% of the urban population) are also

heavily dependent on biofuel due to short supply of

commercial fuels like kerosene and liquefied

petroleum gas. Although a good number of Indian

villages are electrified, the supply of electricity is very

erratic and uncertain in the villages.

Evolution of the Design

Organic material can be charred and crushed into a

powder. The powdery char can then be mixed with a

binder and briquetted into a compact solid fuel like

charcoal. The char briquettes are equivalent to

charcoal in burning characteristics and combustion

efficiency. In the context of using loose biomass for

charring and briquetting, the following issues were

considered:

1. Performing the charring process locally, thus

avoiding collection and transportation of biomass in

large quantities and over long distances

2. Converting low-density biomass of poor thermal

efficiency into char

3. Converting the char thus produced into briquettes

at low pressure, requiring low energy input.

Charring Kiln

A number of charring kilns for processing biological

waste into charcoal, developed by various

organizations like the Tropical Products Institute (TPI),

London; Tongon, Tonga; Indian Institute of Technology

(IIT), Delhi, and Jawaharlal Nehru Krishi

Viswavidyalaya (JNKVV), Jabalpur, were evaluated at

the Central Institute of Agricultural Engineering

(CIAE), Bhopal, with crop residues and other locally

available forest wastes. Stationary charring kilns

require water to extinguish the fire after operation,

which necessitates some time before starting again.

Portable kilns do not produce the desired quality of

char due to improper air control, except the Tongon-

designed kiln. The study concluded that the 'Tongon'

kiln was better than other kilns in terms of the quality

and quantity of char, except that it was neither

economically viable nor ergonomically suitable. To

overcome the problems in existing charring kilns, a

high-capacity charring kiln was designed and

developed which can take a charge of 100 kg crop

residues in one run, yielding about 35-40 kg of good-

quality char. The kiln consists of a metallic cylinder

having a diameter of 800 mm and a length of 1100

mm. Both ends of the cylinder are closed. A

transverse rectangular lid of 550 mm × 450 mm is

provided on its side to serve as the feed inlet (for

specifications of the kiln see Table 1). A batch of 100

kg of crop residues is fed gradually and ignited. The

crop residues get converted into char in about 2-4 h

and yield about 35-40% charred material.

Performance of the machine

Charring of biomass is done at a low rate of heating,

and hence requires a sufficiently long time for the

reaction. The CIAE kiln was extensively evaluated with

soybean crop residue, and pigeon pea and cotton

stalks. About 100 kg of biomass was charged into the

kiln in one batch, and good-quality char was obtained

in a total time period of about 4 h. A char yield of 36%

was realized with cotton and pigeon pea stalks, and

40% with soyabean residue, with a high calorific value

of 15.0-17.5 MJ/kg. Long-duration evaluation of the

kiln over an extended period of more than 3 years

revealed that, on an average, 80 kg char per day can

be produced with one kiln in two batches. Two

unskilled workers were needed, and cost of operation

was Rs 270/q.

Briquetting Machine

A briquetting machine suitable for use in a village

setting should be able to meet the following

requirements:

A char yield of 36% was realized with

cotton and pigeon pea stalks, and 40%

with soyabean residue, with a high

calorific value of 15.0-17.5 MJ/kg. Long-

duration evaluation of the kiln over an

extended period of more than 3 years

revealed that, on an average, 80 kg char

per day can be produced with one kiln in

two batches.

Table 1: Brief Specifications of the CIAE-Developed Charring Kiln and

Briquetting Machine.

CIAE charring kiln

Overall length 1100 mm

Overall diameter 800 mm

Material of construction MS sheets (3 mm),

MS flat (35 × 5) and

rod (12 mm dia)

Weight 75-80 kg

Capacity (char output) 80 kg/day

CIAE power-operated briquetting machine

Overall length 1.6 m

Overall width 3.0 m

Overall height 1.0 m

Size of the prime mover 3.75 kW electric motor

Barrel diameter 21 cm

Barrel Length 42 cm

No of screws 1

Pitch of the screw 20.7 cm

No of exit tubes 5

Length of the exit tube 7 cm

Diameter of the exit tube 3 cm

Power transmission Through belt and pulley

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

44

char

ring

–briq

uetti

ng: a

nov

el c

ooki

ng fu

el te

chno

log

y

char

ring

–briq

uetti

ng: a

nov

el c

ooki

ng fu

el te

chno

log

y

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

45

n rural areas fuel wood, cow dung and crop waste Iare used as kitchen fuel. Apart from these, people

use twigs, hard stalk/straw and so on, as such, to

build fire for cooking and heating. These fuels have

low heat output per unit of fuel used and release a lot

of gases harmful for human health. Over the above,

charcoal is a preferred fuel because it produces a

hot, long-lasting, virtually smokeless fire. In earlier

days, people were using the charcoal obtained from

partially burnt wood remaining at the end of the

routine cooking process. There also existed a practice

of turning powdery coal into balls for use as fuel.

Nevertheless, biofuels accounted for 80% of their

kitchen energy needs.

In rural areas, according to one expert's opinion, in

coming years there will be sufficient food but

insufficient fuel to cook the food, as the rate of

In the years to come, there will be

sufficient food but insufficient fuel to cook

the food in rural areas as well as among

the urban poor, which can be attributed to

the higher rate of deforestation as

compared to that of afforestation.

deforestation is very high in comparison to the

afforestation rate. The rural population is unable to

shift to commercial fuels due to their low purchasing

power and the limited availability of commercial fuels.

Urban poor (25-30% of the urban population) are also

heavily dependent on biofuel due to short supply of

commercial fuels like kerosene and liquefied

petroleum gas. Although a good number of Indian

villages are electrified, the supply of electricity is very

erratic and uncertain in the villages.

Evolution of the Design

Organic material can be charred and crushed into a

powder. The powdery char can then be mixed with a

binder and briquetted into a compact solid fuel like

charcoal. The char briquettes are equivalent to

charcoal in burning characteristics and combustion

efficiency. In the context of using loose biomass for

charring and briquetting, the following issues were

considered:

1. Performing the charring process locally, thus

avoiding collection and transportation of biomass in

large quantities and over long distances

2. Converting low-density biomass of poor thermal

efficiency into char

3. Converting the char thus produced into briquettes

at low pressure, requiring low energy input.

Charring Kiln

A number of charring kilns for processing biological

waste into charcoal, developed by various

organizations like the Tropical Products Institute (TPI),

London; Tongon, Tonga; Indian Institute of Technology

(IIT), Delhi, and Jawaharlal Nehru Krishi

Viswavidyalaya (JNKVV), Jabalpur, were evaluated at

the Central Institute of Agricultural Engineering

(CIAE), Bhopal, with crop residues and other locally

available forest wastes. Stationary charring kilns

require water to extinguish the fire after operation,

which necessitates some time before starting again.

Portable kilns do not produce the desired quality of

char due to improper air control, except the Tongon-

designed kiln. The study concluded that the 'Tongon'

kiln was better than other kilns in terms of the quality

and quantity of char, except that it was neither

economically viable nor ergonomically suitable. To

overcome the problems in existing charring kilns, a

high-capacity charring kiln was designed and

developed which can take a charge of 100 kg crop

residues in one run, yielding about 35-40 kg of good-

quality char. The kiln consists of a metallic cylinder

having a diameter of 800 mm and a length of 1100

mm. Both ends of the cylinder are closed. A

transverse rectangular lid of 550 mm × 450 mm is

provided on its side to serve as the feed inlet (for

specifications of the kiln see Table 1). A batch of 100

kg of crop residues is fed gradually and ignited. The

crop residues get converted into char in about 2-4 h

and yield about 35-40% charred material.

Performance of the machine

Charring of biomass is done at a low rate of heating,

and hence requires a sufficiently long time for the

reaction. The CIAE kiln was extensively evaluated with

soybean crop residue, and pigeon pea and cotton

stalks. About 100 kg of biomass was charged into the

kiln in one batch, and good-quality char was obtained

in a total time period of about 4 h. A char yield of 36%

was realized with cotton and pigeon pea stalks, and

40% with soyabean residue, with a high calorific value

of 15.0-17.5 MJ/kg. Long-duration evaluation of the

kiln over an extended period of more than 3 years

revealed that, on an average, 80 kg char per day can

be produced with one kiln in two batches. Two

unskilled workers were needed, and cost of operation

was Rs 270/q.

Briquetting Machine

A briquetting machine suitable for use in a village

setting should be able to meet the following

requirements:

A char yield of 36% was realized with

cotton and pigeon pea stalks, and 40%

with soyabean residue, with a high

calorific value of 15.0-17.5 MJ/kg. Long-

duration evaluation of the kiln over an

extended period of more than 3 years

revealed that, on an average, 80 kg char

per day can be produced with one kiln in

two batches.

char

ring

–briq

uetti

ng: a

nov

el c

ooki

ng fu

el te

chno

log

yJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

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46

1. It must be inexpensive and easy to operate.

2. It must be repairable and must be economical with

regard to energy consumption.

3. It must be suitable for a variety of biomass and

should not require sophisticated storage space for

the raw material or finished product.

Keeping these basic concepts in view, a power-

operated briquetting machine, which is basically a full

screw horizontal extruder machine similar to plastic

extruders/food product extruders, was developed by

CIAE (Table 1).

Performance of the machine

Char is converted into briquettes very easily even at

low pressure. The briquettes prepared from the

charred biomass can serve as an excellent domestic

fuel. The volume of the briquettes was only 9-11% of

the original feed material, that is, biomass. Therefore,

it may be concluded that this integrated technology

helps to save on transportation charges of feed

material. The briquettes can be produced

economically using a power-operated machine having

a capacity of 75 kg/h and using 10% cow dung as

binder.

Specific Features of the Charring-and-Briquetting

Technology

1. Easy handling of crop residues

2. Less space required for storage of briquettes due

to reduction in volume

3. Easy to use in traditional and improved sigris

4. Simple and low-cost

5. Eco-friendly and hence reduced smoke density in

kitchen

6. High thermal efficiency

7. Technology suitable for rural entrepreneurship

Economics of Operation

Cost economics was worked out for a system of six

charring kilns and one briquetting machine with a

production capacity of 500 kg briquettes per day. Life

of the charring kilns was considered as 3 years and

that of the briquetting machine as 10 years with an

annual usage of 1200 h. After considering the cost of

operation of the charring kilns and briquetting

machine, the estimated annual profit was Rs 97,800.

Farmers, entrepreneurs, village artisans,

village extension officers and engineers

from state government were trained in the

use of the charring kiln and briquetting

machine. Under the operational research

project, briquettes were supplied to more

than 500 families in the nearby villages for

use in improved cook stoves.

Present Status of the Technology

A number of demonstrations were conducted in the

nearby villages to create awareness. Farmers,

entrepreneurs, village artisans, village extension

officers and engineers from state government were

trained in the use of the charring kiln and briquetting

machine. Under the operational research project,

briquettes were supplied to more than 500 families in

the nearby villages for use in improved cook stoves.

Improved Cook stove: Specific features

1. Radiation and

convection losses

have been

considerably

reduced by

enclosing the

burning

charcoal/briquettes

within two concentric

aluminium reflectors

between which an

insulating layer of

asbestos cloth of 3-5

mm thickness is riveted firmly.

2. There is a saving of 60% expenditure in the

operation of the improved sigri over the traditional

method of chulah and fuel wood.

3. CO emission into the breathing zone is 2-3 ppm

from the improved sigri, as compared to the

emission of 12-15 ppm from a single-mouth

chulah.

4. The improved sigri is portable, with a weight of

only 2.0 kg.

Mr. B P Nema is Principal Scientist

at Central Institute of Agricultural

Engineering, ICAR, Bhopal

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wind turbinesfor oceanic areas:

innovations anddevelopments

Ron Steenbergen

Two of the continuing problems faced by wind power development in most

areas of the world are the inability to make real inroads into the use of diesel

in power systems (the 'penetration rate') and the inability to accurately

forecast the expected generation from wind turbines ('dispatchability'). This

article discusses the innovations in the wind power industry in recent months

on these two major issues and the ongoing development of wind power to

improve its applicability in grid-connected and off-grid situations.

different approaches and different

technical solutions. Even the simplest of

solutions may achieve substantial fuel

savings if the right approach is adapted.

There is no unique solution for wind-diesel coupling.

Attention is often focused on integrated systems with

very high penetration rates. They may be the best

solution when financial and technical means are

considered. However, the concept cannot be applied

to all locations. Different contexts require different

approaches and different technical solutions. Even

the simplest of solutions may achieve substantial fuel

savings if the right approach is adapted.

Jan

uary

- M

arc

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01

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48

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rbin

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anic

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as: i

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atio

ns a

nd d

evel

opm

ents

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rbin

es fo

r oce

anic

are

as: i

nnov

atio

ns a

nd d

evel

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49

ind turbines have a long and productive history Win oceanic areas, including the Pacific and

Indian Oceans and other similar regions around the

world. Wind power plays a vital role in delivering

mainstream renewable energy in a sustainable

manner and is one of the most widely available,

commercial and proven forms of renewable energy

that can be deployed in the 'oceanic island' context.

Power from wind is able to compete commercially

with that of diesel generation in many regions and

has helped usher in economic development in many

poor countries.

Even though many successful wind energy projects

have been developed in oceanic regions, they had

faced a number of challenges and difficulties. Typical

challenges include areas being prone to cyclones,

remoteness, low accessibility and lack of suitable

cranes. Two of the continuing problems faced by wind

power development in most areas of the world are the

inability to make real inroads into the use of diesel in

power systems (the 'penetration rate') and the inability

to accurately forecast the expected generation from

wind turbines ('dispatchability'). This article will

discuss the innovations in the wind power industry in

recent months on these two major issues and provide

a taste of the ongoing development of wind power to

improve its applicability in grid-connected and off-grid

situations.

Increasing the Penetration Rate

Historically, when fuel prices were significantly lower

than they are today, remote locations were supplied

with electricity by diesel units in majority of cases, as

the technology is reliable, mature and well known.

However, evolution of fuel prices, together with

increasing reliability of alternative energy sources, has

spurred the emergence of a new market for megawatt

(MW)-scale hybrid systems, capable of meeting the

increasing power demand. Wind energy is often used

as the main means of reducing the dependency on

diesel.

Attention has been focused on a few

operating systems or concepts featuring

advanced components and controls,

sometimes performing remarkably well

and achieving high fuel savings. Such

systems are, however, very costly and

require a high level of technical

competence, and often need public

subsidies. In remote locations with very

little infrastructure and technical means,

such skill levels are seldom available, not

to mention the financial means or

subsidies.

In industrialized countries, much effort has been put

in the development of high-penetration wind systems.

Attention has been focused on a few operating

systems or concepts featuring advanced components

and controls, sometimes performing remarkably well

and achieving high fuel savings. Such systems are,

however, very costly and require a high level of

technical competence, and often need public

subsidies. In remote locations with very little

infrastructure and technical means, such skill levels

are seldom available, not to mention the financial

means or subsidies. Such solutions are therefore hard

to implement or not sustainable in an island context.

Comparatively little attention has been paid to

solutions designed for meeting such needs, although

they concern a much larger share of the population

and represent a larger market. Hybrid systems

suitable for such locations require a sturdy and

proven design, reliable, replicable and easy to

maintain. The new generation of wind-diesel (low

load) systems, now implemented in the megawatt

range, have taken up this challenge. With a

sophisticated architecture comprising of wind

turbines, low-load diesel power plants and a control

system ensuring optimal management of and

dialogue between the wind and diesel plants, they

can achieve an annual average wind penetration of

between 30% and 40%, with low wind energy losses,

and do not demand new competencies from the utility

staff - diesel sets are off-the-shelf models but sized to

match the wind turbine.

Efforts have also been underway to achieve 50% or

higher average wind penetration, while keeping the

industrial vision for reliability of the system and

deployment on remote island grids. The idea is to

have an integrated solution for grid management

support together with forecast elements. This allows

utilities to have a clear vision of how much energy will

be available in the coming hours, anticipating the

wind level and the load curve, thus overcoming wind

resource variability.

The production units of an effective wind-diesel hybrid

system added to a weak grid should contribute to

grid support to reach high penetration rates. In

particular, they should provide the following services:

wLow-voltage ride through: the production unit

remains connected to help pass a fault on the grid.

wFrequency and voltage regulation: by adjusting the

input of active and reactive power to the grid

wOperational power reserve: input power to help

pass a major fault on the grid

wAnticipation of power production: help the utility

manage the number and type of production units to

run at an efficient load factor in order to increase wind

penetration; wind turbines should behave like a diesel

generator for a stipulated time period.

There is no unique solution for wind-diesel

coupling. Different contexts require Figure 1: Demonstrated Payback Period for Wind-Diesel Systems

Figure 2: Schematic Representation of Wind-Diesel System Control

different approaches and different

technical solutions. Even the simplest of

solutions may achieve substantial fuel

savings if the right approach is adapted.

There is no unique solution for wind-diesel coupling.

Attention is often focused on integrated systems with

very high penetration rates. They may be the best

solution when financial and technical means are

considered. However, the concept cannot be applied

to all locations. Different contexts require different

approaches and different technical solutions. Even

the simplest of solutions may achieve substantial fuel

savings if the right approach is adapted.

Jan

uary

- M

arc

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01

2a

qua

rterly

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the

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of e

nerg

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s / I

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48

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rbin

es fo

r oce

anic

are

as: i

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atio

ns a

nd d

evel

opm

ents

win

d tu

rbin

es fo

r oce

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are

as: i

nnov

atio

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nd d

evel

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Jan

uary

- M

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49

ind turbines have a long and productive history Win oceanic areas, including the Pacific and

Indian Oceans and other similar regions around the

world. Wind power plays a vital role in delivering

mainstream renewable energy in a sustainable

manner and is one of the most widely available,

commercial and proven forms of renewable energy

that can be deployed in the 'oceanic island' context.

Power from wind is able to compete commercially

with that of diesel generation in many regions and

has helped usher in economic development in many

poor countries.

Even though many successful wind energy projects

have been developed in oceanic regions, they had

faced a number of challenges and difficulties. Typical

challenges include areas being prone to cyclones,

remoteness, low accessibility and lack of suitable

cranes. Two of the continuing problems faced by wind

power development in most areas of the world are the

inability to make real inroads into the use of diesel in

power systems (the 'penetration rate') and the inability

to accurately forecast the expected generation from

wind turbines ('dispatchability'). This article will

discuss the innovations in the wind power industry in

recent months on these two major issues and provide

a taste of the ongoing development of wind power to

improve its applicability in grid-connected and off-grid

situations.

Increasing the Penetration Rate

Historically, when fuel prices were significantly lower

than they are today, remote locations were supplied

with electricity by diesel units in majority of cases, as

the technology is reliable, mature and well known.

However, evolution of fuel prices, together with

increasing reliability of alternative energy sources, has

spurred the emergence of a new market for megawatt

(MW)-scale hybrid systems, capable of meeting the

increasing power demand. Wind energy is often used

as the main means of reducing the dependency on

diesel.

Attention has been focused on a few

operating systems or concepts featuring

advanced components and controls,

sometimes performing remarkably well

and achieving high fuel savings. Such

systems are, however, very costly and

require a high level of technical

competence, and often need public

subsidies. In remote locations with very

little infrastructure and technical means,

such skill levels are seldom available, not

to mention the financial means or

subsidies.

In industrialized countries, much effort has been put

in the development of high-penetration wind systems.

Attention has been focused on a few operating

systems or concepts featuring advanced components

and controls, sometimes performing remarkably well

and achieving high fuel savings. Such systems are,

however, very costly and require a high level of

technical competence, and often need public

subsidies. In remote locations with very little

infrastructure and technical means, such skill levels

are seldom available, not to mention the financial

means or subsidies. Such solutions are therefore hard

to implement or not sustainable in an island context.

Comparatively little attention has been paid to

solutions designed for meeting such needs, although

they concern a much larger share of the population

and represent a larger market. Hybrid systems

suitable for such locations require a sturdy and

proven design, reliable, replicable and easy to

maintain. The new generation of wind-diesel (low

load) systems, now implemented in the megawatt

range, have taken up this challenge. With a

sophisticated architecture comprising of wind

turbines, low-load diesel power plants and a control

system ensuring optimal management of and

dialogue between the wind and diesel plants, they

can achieve an annual average wind penetration of

between 30% and 40%, with low wind energy losses,

and do not demand new competencies from the utility

staff - diesel sets are off-the-shelf models but sized to

match the wind turbine.

Efforts have also been underway to achieve 50% or

higher average wind penetration, while keeping the

industrial vision for reliability of the system and

deployment on remote island grids. The idea is to

have an integrated solution for grid management

support together with forecast elements. This allows

utilities to have a clear vision of how much energy will

be available in the coming hours, anticipating the

wind level and the load curve, thus overcoming wind

resource variability.

The production units of an effective wind-diesel hybrid

system added to a weak grid should contribute to

grid support to reach high penetration rates. In

particular, they should provide the following services:

wLow-voltage ride through: the production unit

remains connected to help pass a fault on the grid.

wFrequency and voltage regulation: by adjusting the

input of active and reactive power to the grid

wOperational power reserve: input power to help

pass a major fault on the grid

wAnticipation of power production: help the utility

manage the number and type of production units to

run at an efficient load factor in order to increase wind

penetration; wind turbines should behave like a diesel

generator for a stipulated time period.

There is no unique solution for wind-diesel

coupling. Different contexts require Figure 1: Demonstrated Payback Period for Wind-Diesel Systems

Figure 2: Schematic Representation of Wind-Diesel System Control

Case Study 1 - Coral Bay, Australia

Technology flywheel, low-load gensets,

full automation

Installed capacity Wind: 3 x 275 kW

Diesel: 7 x 320 kW modified

for low load

Flywheel: 500 kW

Peak load 700 kW

The system is designed to achieve a very high wind

penetration rate with high power quality. Integration of

all components was considered from the beginning.

wThe size of the power station allows flexible

management of operating power. Diesel gensets

are modified to run at a low load factor to leave

room for wind energy and to limit the number of

starts, thus reducing maintenance costs.

wThe wind turbines are rated in such a way to match

the size of the diesel generator.

wFor periods of very high wind penetration, a

flywheel supports the stability of the grid and

provides high power quality.

wManagement of the power station, flywheel, wind

turbines and the load is fully automated.

Installation of the system benefitted from subsidies

from the authorities in accordance with their

renewable energy policy.

Case Study 2 - Devil's Point, Vanuatu

Technology Conventional diesel power

station, manual management of

coupling, no storage

Installed capacity Wind: 11 x 275 kW

Diesel: 2 x 4.1 MW + 4 x 1 MW +

10 MW in Vila

Peak load 11 MW

Approach: The asset owner chose to proceed step by

step, for a gradual insertion of wind turbines in the

energy mix. The idea is both to gradually assimilate

the management of a new technology and to test the

impact of wind energy on the local grid.

2007: The existing conventional power station is

based on low-speed diesel generators. A single 275

kW wind turbine is installed as a pilot project.

2008: Ten additional 275 kW wind turbines are added,

together with four containerized high-speed diesel

generators. The capability of the grid to absorb wind

fluctuations is assessed; operators learn to adapt the

management of the power station to the wind profile

and wind turbine response.

Next step: The asset owner is considering the

installation of additional 275 kW wind turbines to

reach 30% average wind penetration and the

extension of the high-speed diesel capacity of the

power station. Automation of the whole system is an

option, but may not be necessary at the moment.

The system does not benefit from any subsidy for

equipment installation, nor from any customer tariff

policy or fuel pricing policy. Although the average

income per capita of the country is quite low, the tariff

policy actually reflects the true cost of energy

production. Wind energy is thus cheaper than diesel,

resulting in effective fuel savings and reduction of

operating cost.

After the first year of operation, as of December 2009:

Average wind penetration: 17% (source: Unelco)

Instantaneous penetration: >60% (source: Unelco)

With the extension of the wind farm to include more

275 kW wind turbines, the average wind penetration is

expected to rise to 30%.

win

d tu

rbin

es fo

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are

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atio

ns a

nd d

evel

opm

ents

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- M

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01

2a

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rterly

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the

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ager

s / I

ndia

50

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rbin

es fo

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ns a

nd d

evel

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51

Figure 5: Devil's Point Wind Farm, Vanuatu

guarantee. Forecasts of 48 or 72 hours in

advance can also be offered, with a

consequent reduction in accuracy and

guarantee.

Predictability - Forecasting Wind Energy

Production

Thanks to the extensive experience with weak grids,

especially in islands, wind turbines can now offer

solutions to address utility concerns: grid support to

reach higher wind penetration rates, while avoiding

the two drawbacks of high-penetration systems,

namely, cost and technical complexity. These systems

can then lend themselves to providing accurate

forecasts of power generation from a wind farm by as

much as 24 hours in advance with a 95% guarantee.

Forecasts of 48 or 72 hours in advance can also be

offered, with a consequent reduction in accuracy and

guarantee.

Recent innovations that provide flexibility, certainty

and adaptability for accurate energy forecasts include

a number of differing technologies.

1. The AC-DC-AC drive (back-to-back converter)

buffers power quality fluctuations and also

Figure 3: Example of an Automated Flywheel System for High

Penetration Stability

Average wind penetration: 70% (source: Powercorp)

Instantaneous penetration: up to 98% (source:

Powercorp)

The flywheel ensures frequency and voltage stability

at high wind penetration and serves as a power

reserve for very short time periods (see Figure 4).

Figure 4: Performance Graph of the System with Flywheel Installed

Figure 6: Wind Farm Output in Grid Supply

These systems can then lend themselves

to providing accurate forecasts of power

generation form a wind farm by as much

as 24 hours in advance with a 95%

Case Study 1 - Coral Bay, Australia

Technology flywheel, low-load gensets,

full automation

Installed capacity Wind: 3 x 275 kW

Diesel: 7 x 320 kW modified

for low load

Flywheel: 500 kW

Peak load 700 kW

The system is designed to achieve a very high wind

penetration rate with high power quality. Integration of

all components was considered from the beginning.

wThe size of the power station allows flexible

management of operating power. Diesel gensets

are modified to run at a low load factor to leave

room for wind energy and to limit the number of

starts, thus reducing maintenance costs.

wThe wind turbines are rated in such a way to match

the size of the diesel generator.

wFor periods of very high wind penetration, a

flywheel supports the stability of the grid and

provides high power quality.

wManagement of the power station, flywheel, wind

turbines and the load is fully automated.

Installation of the system benefitted from subsidies

from the authorities in accordance with their

renewable energy policy.

Case Study 2 - Devil's Point, Vanuatu

Technology Conventional diesel power

station, manual management of

coupling, no storage

Installed capacity Wind: 11 x 275 kW

Diesel: 2 x 4.1 MW + 4 x 1 MW +

10 MW in Vila

Peak load 11 MW

Approach: The asset owner chose to proceed step by

step, for a gradual insertion of wind turbines in the

energy mix. The idea is both to gradually assimilate

the management of a new technology and to test the

impact of wind energy on the local grid.

2007: The existing conventional power station is

based on low-speed diesel generators. A single 275

kW wind turbine is installed as a pilot project.

2008: Ten additional 275 kW wind turbines are added,

together with four containerized high-speed diesel

generators. The capability of the grid to absorb wind

fluctuations is assessed; operators learn to adapt the

management of the power station to the wind profile

and wind turbine response.

Next step: The asset owner is considering the

installation of additional 275 kW wind turbines to

reach 30% average wind penetration and the

extension of the high-speed diesel capacity of the

power station. Automation of the whole system is an

option, but may not be necessary at the moment.

The system does not benefit from any subsidy for

equipment installation, nor from any customer tariff

policy or fuel pricing policy. Although the average

income per capita of the country is quite low, the tariff

policy actually reflects the true cost of energy

production. Wind energy is thus cheaper than diesel,

resulting in effective fuel savings and reduction of

operating cost.

After the first year of operation, as of December 2009:

Average wind penetration: 17% (source: Unelco)

Instantaneous penetration: >60% (source: Unelco)

With the extension of the wind farm to include more

275 kW wind turbines, the average wind penetration is

expected to rise to 30%.

win

d tu

rbin

es fo

r oce

anic

are

as: i

nnov

atio

ns a

nd d

evel

opm

ents

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

50

win

d tu

rbin

es fo

r oce

anic

are

as: i

nnov

atio

ns a

nd d

evel

opm

ents

Jan

uary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

51

Figure 5: Devil's Point Wind Farm, Vanuatu

guarantee. Forecasts of 48 or 72 hours in

advance can also be offered, with a

consequent reduction in accuracy and

guarantee.

Predictability - Forecasting Wind Energy

Production

Thanks to the extensive experience with weak grids,

especially in islands, wind turbines can now offer

solutions to address utility concerns: grid support to

reach higher wind penetration rates, while avoiding

the two drawbacks of high-penetration systems,

namely, cost and technical complexity. These systems

can then lend themselves to providing accurate

forecasts of power generation from a wind farm by as

much as 24 hours in advance with a 95% guarantee.

Forecasts of 48 or 72 hours in advance can also be

offered, with a consequent reduction in accuracy and

guarantee.

Recent innovations that provide flexibility, certainty

and adaptability for accurate energy forecasts include

a number of differing technologies.

1. The AC-DC-AC drive (back-to-back converter)

buffers power quality fluctuations and also

Figure 3: Example of an Automated Flywheel System for High

Penetration Stability

Average wind penetration: 70% (source: Powercorp)

Instantaneous penetration: up to 98% (source:

Powercorp)

The flywheel ensures frequency and voltage stability

at high wind penetration and serves as a power

reserve for very short time periods (see Figure 4).

Figure 4: Performance Graph of the System with Flywheel Installed

Figure 6: Wind Farm Output in Grid Supply

These systems can then lend themselves

to providing accurate forecasts of power

generation form a wind farm by as much

as 24 hours in advance with a 95%

win

d tu

rbin

es fo

r oce

anic

are

as: i

nnov

atio

ns a

nd d

evel

opm

ents

Jan

uary

- M

arc

h 2

01

2a

qua

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w

w

wprovides reactive power even without active power

production

wprovides a baseplate for embedded battery storage

or development of super-capacity supplements.

2. Battery storage plugged on to the DC bus of the

AC-DC-AC link provides power reserve for grid

support and easier production unit management.

Several working modes are possible:

wProduction: the wind turbine produces the

maximum power depending on wind conditions

wStorage (from the wind turbine or from the grid):

storage is done by transferring power from the DC

bus to the batteries

wPower reserve call: if grid frequency drops below a

pre-defined threshold, extra power is supplied from

batteries to the DC bus, which is then injected to

support the grid. Warning is sent to the utility to

take appropriate action before the reserve is

exhausted (1/4 hour).

3. Production forecast: Together with the embedded

turbine power reserve, power forecast at 72 h/48 h/24

h allows the utility to plan production and optimize its

spinning reserve:

wPower production is based on weather forecasts,

which are very reliable today

wThanks to forecast reliability, batteries are little

used as power reserve, thus reducing wear cycles.

wPower production can be adjusted with either

storage or power limitation and remain stable for

30 min

With grid support capability, wind energy no longer

belongs to the intermittent sources of power, allowing

ensures compliance to all grid codes

provides fault-ride-through capability

Battery storage plugged on to the DC bus

of the AC-DC-AC link provides power

reserve for grid support and easier

production unit management. Several

working modes are possible.

Mr. Ron Steenbergen is the

Managing Director of

Projectioneering Pvt Ltd and has

over 30 years of technical,

environmental and project

management experience in

renewable energy development.

Figure 7: Example of Forecast (red) v Actual (green) Generation

of a Wind Project

higher penetration rates of wind energy on small

grids, at a reasonable cost and avoiding complex

solutions.

These innovative uses of a traditional technology

improve the technology's abilities in

wgenuine reduction of fuel usage in diesel-

dominated power systems

wlong-term sustainability of commercially viable

renewables

wforecasting the generation output for the following

day

wimproved power quality and power system

reliability

wmanaging demand and load in power system

dispatch

These processes also lend themselves to further

innovation by incorporating low-cost technologies under

development at present such as battery storage or super

capacity to provide energy buffering.

Note: This article was prepared based upon a presentation made by

the author to the Pacific Power Association 2011 Conference in Guam.

Jan

ua

ry -

Ma

rch

2012

a q

uarte

rly m

agaz

ine

of th

e so

ciet

y of

ene

rgy

eng

inee

rs a

nd m

anag

ers

/ Ind

ia

54

Jan

ua

ry -

Ma

rch

2012

a q

uarte

rly m

agaz

ine

of th

e so

ciet

y of

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rgy

eng

inee

rs a

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/ Ind

ia

55

ith the high growth rate of the Indian Weconomy, energy needs are growing rapidly.

India ranks fifth in the world in terms of energy

consumption. The average annual growth rate of

energy consumption is growing at about 6% per

annum with economy growth pegged at 7-8%. This

will lead to a growing gap between demand and

supply of commercial energy, resulting in an

increasing dependence on imported oil.

The total energy consumption of the country in

2007-08 was 570 million tonnes of oil equivalent

(MTOE) of which 745 was from commercial sources

like coal, oil, hydro and so on, while 265 was from

non-commercial sources. The total energy

consumption is expected to rise threefold to 1836

MTOE by 2031-32 of which 90% will be accounted

for by commercial energy.

In India, during the period 1960-2007, the use of

commercial sources of energy increased 10-fold

and electricity use increased by 100 times. In the

non-commercial sector, India uses 200 million

tonnes of fuel wood, apart from large quantities of

energy and environment

symbiosisA.K. Jain

Indian cities are facing a grim situation

in terms of energy. To tackle this

situation, there is a need to evolve a

multi-pronged and multi-disciplinary

approach. The basic premise of a

sustainable, energy-efficient city is

conservation of transport fuels and

energy. A sustainable urban structure

begins with the urban region, the city

and its hinterland; the sustainability of

each is dependent on the other. At the

level of the city, a 'walkable'

community provides the fundamental

building block in creating a

sustainable urban form.

Jan

ua

ry -

Ma

rch

2012

a q

uarte

rly m

agaz

ine

of th

e so

ciet

y of

ene

rgy

eng

inee

rs a

nd m

anag

ers

/ Ind

ia

54

Jan

ua

ry -

Ma

rch

2012

a q

uarte

rly m

agaz

ine

of th

e so

ciet

y of

ene

rgy

eng

inee

rs a

nd m

anag

ers

/ Ind

ia

55

ith the high growth rate of the Indian Weconomy, energy needs are growing rapidly.

India ranks fifth in the world in terms of energy

consumption. The average annual growth rate of

energy consumption is growing at about 6% per

annum with economy growth pegged at 7-8%. This

will lead to a growing gap between demand and

supply of commercial energy, resulting in an

increasing dependence on imported oil.

The total energy consumption of the country in

2007-08 was 570 million tonnes of oil equivalent

(MTOE) of which 745 was from commercial sources

like coal, oil, hydro and so on, while 265 was from

non-commercial sources. The total energy

consumption is expected to rise threefold to 1836

MTOE by 2031-32 of which 90% will be accounted

for by commercial energy.

In India, during the period 1960-2007, the use of

commercial sources of energy increased 10-fold

and electricity use increased by 100 times. In the

non-commercial sector, India uses 200 million

tonnes of fuel wood, apart from large quantities of

energy and environment

symbiosisA.K. Jain

Indian cities are facing a grim situation

in terms of energy. To tackle this

situation, there is a need to evolve a

multi-pronged and multi-disciplinary

approach. The basic premise of a

sustainable, energy-efficient city is

conservation of transport fuels and

energy. A sustainable urban structure

begins with the urban region, the city

and its hinterland; the sustainability of

each is dependent on the other. At the

level of the city, a 'walkable'

community provides the fundamental

building block in creating a

sustainable urban form.

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

56

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

57

cow dung and agricultural waste. The increasing

energy consumption is having a direct bearing on the

environment and economy.

Among the commercial sources of energy, coal and

lignite contribute about 59%, oil and natural gas

about 37%, and hydro-electric and nuclear power

around 4%. Thus, the main source of energy is the

stored hydrocarbons (96%) under the earth's crust,

which are being utilized liberally. At present, over 70%

of the oil requirements are met from imported

sources. The cost of energy is ever increasing, and

the lack of development of non-conventional energy

sources is making the energy situation more

challenging.

Energy, Emissions and Environment

Production, conversion and use of energy play a

significant role in global warming, which affects the

environment. In the coming decades, global

environment issues can dictate the patterns of energy

use. The principal international energy issues revolve

around supply interruptions and their implications for

energy security and price stability, and the impact of

energy production and consumption on regional and

global environments.

The use of coal on a worldwide basis will increase at

an average rate of 1.6% per year. But in India its use

will be almost double by 2025 or so. The total

recoverable reserves of coal around the world are

estimated at 1088 billion tons, out of which India's

reserve is around 100 billion tons. Between 1996 and

2020, use of coal for electricity generation in India is

projected to rise by 3% per year. India is expected to

increase its consumption of electricity at an average

annual rate of 4.9% from 1996 to 2020. In future

years, coal-based energy generation will face tough

challenges as far as environmental pollution is

concerned.

The automobile sector and thermal power plants are

the major contributors towards atmospheric pollution.

Combustion of coal, oil and natural gas accounts for

roughly three-quarters of all carbon dioxide

The use of coal on a worldwide basis will

increase at an average rate of 1.6% per

year. But in India its use will be almost

double by 2025 or so.

emissions. The industrial sector accounts for more

than one-third of the global carbon dioxide emission

from fossil fuel combustion (excluding the power

sector), the residential and commercial sector 32%,

and the transport sector a bit over 21%.

Development of eco-friendly energy supply opens up

enormous opportunities for international cooperation.

It is important to structure pricing mechanisms,

relations with other countries and commercial

transactions in a manner that meets the long-term

objectives of adequate and sustainable energy.

Renewable Sources of Energy

Harnessing of renewable energy aims not only

increasing energy generation but also helping to

restore a pollution-free environment. It is estimated

that India has the potential of generating more than

1,00,000 MW from non-conventional sources of

energy. Table 1 indicates the potential of various

renewable energy resources.

Table 1: Renewable Energy Resources Potential

In the Indian context, energy efficiency and alternative

energy sources offer the biggest scope for cutting

carbon dioxide emissions. Two missions - Solar

Mission and Enhanced Energy Efficiency Mission -

have been constituted by the Government of India to

address these issues.

The town or city depends on its hinterland

for food and water, clean air and open

space, and, looking to the future, for

biomass for fuel. The hinterland depends

on the town or city as a market for its

produce and for employment and

services. Sustainable planning demands a

more holistic and integrated approach to

the urban region, which recognizes the

interdependence and potential of both

town and country.

Urban Structure and Transport for Energy

Efficiency

In the context of surging oil prices and increasing

energy demand, urban planning assumes a critical

role. The solution to the huge energy demand lies

beyond enhancing power generation. It is the form of

the city structure, zoning controls, land use and

density pattern, together with architecture, building

and management options, which have to be tackled

in a holistic manner. The basic premise of a

sustainable, energy-efficient city is conservation of

transport fuels and energy. Sustainable urban

structure begins with the urban region, the city and its

hinterland; the sustainability of each is dependent on

the other. The town or city depends on its hinterland

for food and water, clean air and open space, and,

looking to the future, for biomass for fuel. The

hinterland depends on the town or city as a market

for its produce and for employment and services.

Sustainable planning demands a more holistic and

integrated approach to the urban region, which

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

56

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

57

cow dung and agricultural waste. The increasing

energy consumption is having a direct bearing on the

environment and economy.

Among the commercial sources of energy, coal and

lignite contribute about 59%, oil and natural gas

about 37%, and hydro-electric and nuclear power

around 4%. Thus, the main source of energy is the

stored hydrocarbons (96%) under the earth's crust,

which are being utilized liberally. At present, over 70%

of the oil requirements are met from imported

sources. The cost of energy is ever increasing, and

the lack of development of non-conventional energy

sources is making the energy situation more

challenging.

Energy, Emissions and Environment

Production, conversion and use of energy play a

significant role in global warming, which affects the

environment. In the coming decades, global

environment issues can dictate the patterns of energy

use. The principal international energy issues revolve

around supply interruptions and their implications for

energy security and price stability, and the impact of

energy production and consumption on regional and

global environments.

The use of coal on a worldwide basis will increase at

an average rate of 1.6% per year. But in India its use

will be almost double by 2025 or so. The total

recoverable reserves of coal around the world are

estimated at 1088 billion tons, out of which India's

reserve is around 100 billion tons. Between 1996 and

2020, use of coal for electricity generation in India is

projected to rise by 3% per year. India is expected to

increase its consumption of electricity at an average

annual rate of 4.9% from 1996 to 2020. In future

years, coal-based energy generation will face tough

challenges as far as environmental pollution is

concerned.

The automobile sector and thermal power plants are

the major contributors towards atmospheric pollution.

Combustion of coal, oil and natural gas accounts for

roughly three-quarters of all carbon dioxide

The use of coal on a worldwide basis will

increase at an average rate of 1.6% per

year. But in India its use will be almost

double by 2025 or so.

emissions. The industrial sector accounts for more

than one-third of the global carbon dioxide emission

from fossil fuel combustion (excluding the power

sector), the residential and commercial sector 32%,

and the transport sector a bit over 21%.

Development of eco-friendly energy supply opens up

enormous opportunities for international cooperation.

It is important to structure pricing mechanisms,

relations with other countries and commercial

transactions in a manner that meets the long-term

objectives of adequate and sustainable energy.

Renewable Sources of Energy

Harnessing of renewable energy aims not only

increasing energy generation but also helping to

restore a pollution-free environment. It is estimated

that India has the potential of generating more than

1,00,000 MW from non-conventional sources of

energy. Table 1 indicates the potential of various

renewable energy resources.

Table 1: Renewable Energy Resources Potential

In the Indian context, energy efficiency and alternative

energy sources offer the biggest scope for cutting

carbon dioxide emissions. Two missions - Solar

Mission and Enhanced Energy Efficiency Mission -

have been constituted by the Government of India to

address these issues.

The town or city depends on its hinterland

for food and water, clean air and open

space, and, looking to the future, for

biomass for fuel. The hinterland depends

on the town or city as a market for its

produce and for employment and

services. Sustainable planning demands a

more holistic and integrated approach to

the urban region, which recognizes the

interdependence and potential of both

town and country.

Urban Structure and Transport for Energy

Efficiency

In the context of surging oil prices and increasing

energy demand, urban planning assumes a critical

role. The solution to the huge energy demand lies

beyond enhancing power generation. It is the form of

the city structure, zoning controls, land use and

density pattern, together with architecture, building

and management options, which have to be tackled

in a holistic manner. The basic premise of a

sustainable, energy-efficient city is conservation of

transport fuels and energy. Sustainable urban

structure begins with the urban region, the city and its

hinterland; the sustainability of each is dependent on

the other. The town or city depends on its hinterland

for food and water, clean air and open space, and,

looking to the future, for biomass for fuel. The

hinterland depends on the town or city as a market

for its produce and for employment and services.

Sustainable planning demands a more holistic and

integrated approach to the urban region, which

recognizes the interdependence and potential of both

town and country.

At the level of the city, a 'walkable' community

provides the fundamental building block in creating a

sustainable urban form. The concept is based on a

poly-centric urban structure in which a town or city

comprises a network of distinct but overlapping

communities, each focused on a city, district or local

centre, and within which people can access on foot

most of the facilities and services needed for day-to-

day living. Each of these communities is defined by

the walking catchment or 'ped-shed' around the

centre. This is generally taken to be 800 m, equating

to a 10-minute walk.

In a large metropolitan city like Delhi, the concept of

the poly-centric structure has to be adopted, with new

centres being created along the railways, metro and

transport corridors; this can be described as the

'centres and routes' model. In this model, town

centres are the principal community focus, but there

are also linear communities developing along the

main movement routes between the centres and

especially along the principal routes. In other places,

different structures can be seen reflecting the

differences in geography, landform and economy. All

urban areas may not be within the walking catchment

of a centre. However, the proportion of areas lying

beyond walking distance of a centre increases with

distance from the city centre, reflecting both

diminishing densities of population and more widely

spread movement routes. As such, the following

planning and urban design principles can be drawn

out:

wWork centres, major institutions and services to be

focused along public transit corridors, at the

convergence of movement routes and around key

facilities such as metro stations.

wCreating a walkable neighbourhood: All local hubs

should be within easy walking and cycling

distance. Integrated planning of intra-urban and

inter-urban transport can bring about a new pattern

of urban population distribution, settlement

structure and industrial growth, and lead to

environmental conservation. This will require re-

examining of the concept of single land use zoning

and city structure which should be based on

conservation of transport.

wReorganization of land use and urban renewal,

including the circulation pattern.

w

consideration of parking requirements,

pedestrianization and efficient use of road right of

way.

wIntegration of bus and tram routes with metro rail,

rail corridors, LRT and waterways.

wIntegration of bus and rail stations and terminals

with dispersal facilities and services such as

parking and taxi stands.

w Introduction of integrated traffic and transit

operation, control and management, and setting

up of a unified metropolitan regional transport

authority for planning and implementation.

wExploring the potential of using subterranean

space for transport and parking.

wEncouraging the use of cycles and NMV transport.

Planning and Building Design

The materials used in construction, their energy

content and compatibility with climatic conditions,

and the environmental performance of buildings are

inter-linked. It is necessary to rationalize the use of

building materials for conservation of energy and

environmental efficiency of the built environment. By a

proper approach and a comprehensive strategy,

energy efficiency and economy can be achieved.

Besides through the use of energy-efficient building

materials, the energy demand in buildings can be

substantially reduced by proper designing of walls,

roofs, windows and lighting. Improved insulation of

walls and roofs can reduce the heating and cooling

load by 25%. Improved multi-pane windows can

reduce the air-conditioning and heating load

significantly.

Rationalization of land use and density with due

Zero-fossil energy development (ZED)

envisages an urban form and design of a

passive building envelope that reduces

the demand for heat and power to the

point where it becomes economically

viable to use the energy from renewable

resources. This involves a holistic

approach combining the issues and

actions at various levels of planning,

design and construction.

Zero-Fossil Energy Development Protocols

Zero-fossil energy development (ZED) envisages an

urban form and design of a passive building envelope

that reduces the demand for heat and power to the

point where it becomes economically viable to use

the energy from renewable resources. This involves a

holistic approach combining the issues and actions at

various levels of planning, design and construction.

The following checklist is a summary of the guidelines

that should be considered for site analysis, planning,

and the design and specification process. Attention at

an early stage is vital, because a scheme cannot be

redeemed if the basic concept has not addressed

efficiency.

a. Site Planning: Ensure that the proposed building

is appropriately oriented and sensitive to the

natural features and micro-climate of the site.

Assess its micro-climatic character, taking into

account exposure, shelter, natural shading of

buildings, interaction of buildings, solar access

through the seasons, atmospheric pollution, water

and drainage, and noise gradients across the site.

Minimize earth movements and excavations where

possible. Respect ground water levels, and

design to manage surface water through natural

processes. Avoid formation of heat islands and

inversion effect due of layout planning.

b. Form and Orientation: Minimize solar heat gain

during summer and maximize the same in winter

to reduce the need for additional cooling and

lighting, thus reducing the demand for energy.

Design to reduce the surface area for heat

transfer through fabric by avoiding elongated thin

forms and spread-out low-density developments.

Compact forms are preferred, subject to the

conservation policies. Group buildings for

clustered multiple uses/time zoning of buildings

and spaces where appropriate.

c. Building Volume and Envelope: Generally, avoid

over-sized interior heights and spaces when

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

58

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

59

recognizes the interdependence and potential of both

town and country.

At the level of the city, a 'walkable' community

provides the fundamental building block in creating a

sustainable urban form. The concept is based on a

poly-centric urban structure in which a town or city

comprises a network of distinct but overlapping

communities, each focused on a city, district or local

centre, and within which people can access on foot

most of the facilities and services needed for day-to-

day living. Each of these communities is defined by

the walking catchment or 'ped-shed' around the

centre. This is generally taken to be 800 m, equating

to a 10-minute walk.

In a large metropolitan city like Delhi, the concept of

the poly-centric structure has to be adopted, with new

centres being created along the railways, metro and

transport corridors; this can be described as the

'centres and routes' model. In this model, town

centres are the principal community focus, but there

are also linear communities developing along the

main movement routes between the centres and

especially along the principal routes. In other places,

different structures can be seen reflecting the

differences in geography, landform and economy. All

urban areas may not be within the walking catchment

of a centre. However, the proportion of areas lying

beyond walking distance of a centre increases with

distance from the city centre, reflecting both

diminishing densities of population and more widely

spread movement routes. As such, the following

planning and urban design principles can be drawn

out:

wWork centres, major institutions and services to be

focused along public transit corridors, at the

convergence of movement routes and around key

facilities such as metro stations.

wCreating a walkable neighbourhood: All local hubs

should be within easy walking and cycling

distance. Integrated planning of intra-urban and

inter-urban transport can bring about a new pattern

of urban population distribution, settlement

structure and industrial growth, and lead to

environmental conservation. This will require re-

examining of the concept of single land use zoning

and city structure which should be based on

conservation of transport.

wReorganization of land use and urban renewal,

including the circulation pattern.

w

consideration of parking requirements,

pedestrianization and efficient use of road right of

way.

wIntegration of bus and tram routes with metro rail,

rail corridors, LRT and waterways.

wIntegration of bus and rail stations and terminals

with dispersal facilities and services such as

parking and taxi stands.

w Introduction of integrated traffic and transit

operation, control and management, and setting

up of a unified metropolitan regional transport

authority for planning and implementation.

wExploring the potential of using subterranean

space for transport and parking.

wEncouraging the use of cycles and NMV transport.

Planning and Building Design

The materials used in construction, their energy

content and compatibility with climatic conditions,

and the environmental performance of buildings are

inter-linked. It is necessary to rationalize the use of

building materials for conservation of energy and

environmental efficiency of the built environment. By a

proper approach and a comprehensive strategy,

energy efficiency and economy can be achieved.

Besides through the use of energy-efficient building

materials, the energy demand in buildings can be

substantially reduced by proper designing of walls,

roofs, windows and lighting. Improved insulation of

walls and roofs can reduce the heating and cooling

load by 25%. Improved multi-pane windows can

reduce the air-conditioning and heating load

significantly.

Rationalization of land use and density with due

Zero-fossil energy development (ZED)

envisages an urban form and design of a

passive building envelope that reduces

the demand for heat and power to the

point where it becomes economically

viable to use the energy from renewable

resources. This involves a holistic

approach combining the issues and

actions at various levels of planning,

design and construction.

Zero-Fossil Energy Development Protocols

Zero-fossil energy development (ZED) envisages an

urban form and design of a passive building envelope

that reduces the demand for heat and power to the

point where it becomes economically viable to use

the energy from renewable resources. This involves a

holistic approach combining the issues and actions at

various levels of planning, design and construction.

The following checklist is a summary of the guidelines

that should be considered for site analysis, planning,

and the design and specification process. Attention at

an early stage is vital, because a scheme cannot be

redeemed if the basic concept has not addressed

efficiency.

a. Site Planning: Ensure that the proposed building

is appropriately oriented and sensitive to the

natural features and micro-climate of the site.

Assess its micro-climatic character, taking into

account exposure, shelter, natural shading of

buildings, interaction of buildings, solar access

through the seasons, atmospheric pollution, water

and drainage, and noise gradients across the site.

Minimize earth movements and excavations where

possible. Respect ground water levels, and

design to manage surface water through natural

processes. Avoid formation of heat islands and

inversion effect due of layout planning.

b. Form and Orientation: Minimize solar heat gain

during summer and maximize the same in winter

to reduce the need for additional cooling and

lighting, thus reducing the demand for energy.

Design to reduce the surface area for heat

transfer through fabric by avoiding elongated thin

forms and spread-out low-density developments.

Compact forms are preferred, subject to the

conservation policies. Group buildings for

clustered multiple uses/time zoning of buildings

and spaces where appropriate.

c. Building Volume and Envelope: Generally, avoid

over-sized interior heights and spaces when

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

58

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

59

designing for specific uses and functions. Thermal

characteristics of the building envelope, roof and

walls should be compatible with all U and R

values of insulation.

d. Ventilation/Air-conditioning: Use natural

ventilation. Consider the use of atria to achieve

some of these requirements and to provide

amenity space for building users. Minimize the

use of air-conditioning. Consider the interaction

between energy and ventilation strategies to

balance potentially conflicting demands. Avoid the

use of wet cooling where air-conditioning is

installed. Explore new methods of cooling, for

example, passive energy draft cooling (PEDC),

high-efficiency chilling, earth embedded cooling

and the thermal storage system.

e. Lifts: Consider building forms and heights to

economize the reliance on lifts, while meeting the

needs of people with mobility problems.

f. Resource Recovery: Specify the reuse of materials

arising from demolition onsite and recycled

materials bought in from other sites locally.

Shuttering and so on should be reused wherever

possible, rather than destroyed on completion.

Allocate space for future recycling of waste glass

and a composite facility, where appropriate.

g. Greenery: Landscape of the building should

improve the micro-climate and visual amenity, by

shading, greenery, green roof, climbing plants on

walls, window boxes and balcony gardens.

h. Internal Layout: To reduce the need for artificial

light and for optimum heat efficiency, cluster the

uses that need similar environmental conditions.

Avoid open plans to allow for better control of

services by the users.

I. Windows/Doors: Consider the percentage of

fenestration on different facades and plan to

minimize the number of different temperature

zones. Use southerly orientation for passive solar

gain. Consider the type of glazing and

summer/winter ventilation. Use blinds, curtains,

shutters, draught lobbies and air curtains. Design

super-windows that reduce heat loss.

j. Materials: Avoid over-designed structures,

footings and so on that may result in waste of

materials. Consider alternative foundations and

structures where appropriate. Specify timbers

from sustainable forests. Minimize the use of

chemicals and hazardous materials.

k. Flexibility: Plan the duct routes in such a way as

to facilitate future changes in requirements.

l. Plant location: To reduce distribution losses to a

minimum, locate plants close to areas of high

energy consumption. Lag pipe runs to high

specifications; use low-temperature storage, time

controls and intelligent systems.

m. Waste heat recovery: Consider the use of a heat

exchanger if the building is mechanically

ventilated.

n. Building fabric: Specify insulation standards

above the current regulations, where possible.

Avoid the use of CFC-blown insulation.

o. Lighting installation: Energy-efficient lighting

fixtures (LED, CFL, T-5 lamps, electronic chokes

etc.) should be used, along with automatic

sensors to control and avoid unnecessary energy

use. Consider time and intensity controls rather

than general illumination. Benchmarks should be

as per the Energy Conservation Building Code

(ECBC).

p. Wall-to-window ratio (WWR), U Factor, solar heat

gain coefficient (SHGC) and visible light

transmittance (VLT) values: ECBC 2007 2recommends a maximum U factor of 3.3 W/m /K,

an SHGC of 0.25 for a WWR of 40%, and an

SHGC of 0.2 for a WWR of 40-60%. A glazing area

in excess of 60% of gross external wall area is not

recommended. The VLT value linked to WWR

should be as per ECBC. SHGC value is

particularly critical for south, east and west

facades. Glazing U factor and SHGC should be

minimized, whereas VLT should be maximized.

q. Controls: Employ controls that can respond to

internal and external conditions. Time and

temperature should be sensor-/bionic-controlled

according to the need of the occupants.

r. Decorative Finishes: Light-coloured finishes

improve lighting conditions and reduce the

intensity of light required.

s. Details/Standards of Work: Ceiling joints,

insulation, ventilation and thermal installations

should all be checked to ensure that the work has

been carried out to a high standard.

t. Operation: A user-friendly manual for occupants

should be provided to explain the efficient

operation of building and equipment.

u. Commissioning: Before occupancy, a building

should be flushed to remove solvents, gases,

Mr. A.K. Jain is the Ex.

Commissioner (Planning) of Delhi

Development Authority. He is a

member of the UN Habitat Research

Advisory Committee and a visiting

faculty at Delhi School of Planning

and Architecture.

vapours, smells and so on that could affect future

users. Check the performance of machinery

components and equipment against standards,

and put right any defect found that could have

major long-term effects on the energy

consumption of the building.

v. Incentives: Incentives, training and user

participation for energy efficiency and energy

savings should be encouraged.

Indian cities are facing a grim situation in terms of

energy. Unless a holistic and well-worked out

approach is evolved, the scenario would be even

worse, with the galloping economic development and

ever-growing urbanization. To tackle this situation,

there is a need to evolve a multi-pronged and multi-

disciplinary approach. This should begin with

increasing power generation and transmission

capacity and mobilizing private sector resources.

Parallel actions should be taken for conservation of

natural resources and exploring renewable and non-

conventional sources of energy including geothermal

heat and energy from wastes, bio mass and so on. At

the same time, it is necessary to resort to

management reforms, energy distribution

management and audit, adoption of energy-efficient

fuels, upgradation of technology and equipment,

energy tariff reforms, and controlling thefts and

losses. The key to future is a cybernetic form of

sustainable energy, which integrates symbiosis,

recycling and energy chains.

Space and energy are the basic dimensions of the

universe. There is a uterine relationship between the

Parallel actions should be taken for

conservation of natural resources and

exploring renewable and non-conventional

sources of energy including geothermal

heat and energy from wastes, bio mass

and so on. At the same time, it is

necessary to resort to management

reforms, energy distribution management

and audit, adoption of energy-efficient

fuels, upgradation of technology and

equipment, energy tariff reforms, and

controlling thefts and losses.

two. Unless there is a synergy between land use

planning, transportation and energy, we may not be

able to achieve sustainable development. An

important aspect of the space and energy symbiosis

is rediscovering ecological and non-conventional

sources of energy, in place of animate energy and

man-made sources.

Bibliography

1. CSE (Centre for Science & Environment), India-Environment

Report, New Delhi.

2. DDA (2007) Master Plan for Delhi-2021. New Delhi: Ministry of

Urban Development, Govt. of India.

3. GOI (1998) Development Alternatives, Environmental Priorities of

India. New Delhi: Govt. of India.

4. Girardet H. (1997) 'Sustainable cities - A Contradiction in Terms?'

In Satterwaite D. (ed.) Sustainable Cities. London: Earthscan

Publishers.

5. GOI (2001) Census of India Reports. New Delhi: Govt. of India.

6. Second United Nations Conference on Human Settlements,

(Habitat II), Istanbul 1996, India National Report. New Delhi: Ministry

of Urban Affairs & Employment.

7. Planning Commission, GOI (2007) Approach to 11th 5-Year Plan.

New Delhi: Govt. of India.

8. Hough M. (1995) Cities & Natural Process. London: Routeledge.

9. Israel A. (1992) Issues for Infrastructure management in the 1990s.

Washington, D.C.: World Bank.

10. Jain A.K. (2010) Making Infrastructure Work. New Delhi:

Discovery Publishers.

11. Jain A.K. (2001) Ecology and Natural Resource Management for

Sustainable Development. New Delhi: Management Publishing Co.

12. McHarg I. (1969) Design with Nature. New York: Natural History

Press.

13. Ministry of Urban Development, GOI (1988) Report of the National

Commission on Urbanisation. New Delhi: Govt. of India.

14. Rees W.E. (1997) Ecological Footprints and Urban Transportation,

Velocity. Barcelona.

15. Steinberg F. (1995) 'Sustainable Human Settlement Development

- Is It Possible?' Unpublished paper.

16. UNCED (1992) Local Agenda 21, RIO, World Environment

Conference, 1992.

17. World Bank (1994) World Development Report: Infrastructure for

Development. Washington, D.C.

18. World Resource Institute (WRI)/United Nations Environment

Programme/United Nations Development Programme and World Bank,

World Resources 2006-07: A Guide to the Global Environment.

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designing for specific uses and functions. Thermal

characteristics of the building envelope, roof and

walls should be compatible with all U and R

values of insulation.

d. Ventilation/Air-conditioning: Use natural

ventilation. Consider the use of atria to achieve

some of these requirements and to provide

amenity space for building users. Minimize the

use of air-conditioning. Consider the interaction

between energy and ventilation strategies to

balance potentially conflicting demands. Avoid the

use of wet cooling where air-conditioning is

installed. Explore new methods of cooling, for

example, passive energy draft cooling (PEDC),

high-efficiency chilling, earth embedded cooling

and the thermal storage system.

e. Lifts: Consider building forms and heights to

economize the reliance on lifts, while meeting the

needs of people with mobility problems.

f. Resource Recovery: Specify the reuse of materials

arising from demolition onsite and recycled

materials bought in from other sites locally.

Shuttering and so on should be reused wherever

possible, rather than destroyed on completion.

Allocate space for future recycling of waste glass

and a composite facility, where appropriate.

g. Greenery: Landscape of the building should

improve the micro-climate and visual amenity, by

shading, greenery, green roof, climbing plants on

walls, window boxes and balcony gardens.

h. Internal Layout: To reduce the need for artificial

light and for optimum heat efficiency, cluster the

uses that need similar environmental conditions.

Avoid open plans to allow for better control of

services by the users.

I. Windows/Doors: Consider the percentage of

fenestration on different facades and plan to

minimize the number of different temperature

zones. Use southerly orientation for passive solar

gain. Consider the type of glazing and

summer/winter ventilation. Use blinds, curtains,

shutters, draught lobbies and air curtains. Design

super-windows that reduce heat loss.

j. Materials: Avoid over-designed structures,

footings and so on that may result in waste of

materials. Consider alternative foundations and

structures where appropriate. Specify timbers

from sustainable forests. Minimize the use of

chemicals and hazardous materials.

k. Flexibility: Plan the duct routes in such a way as

to facilitate future changes in requirements.

l. Plant location: To reduce distribution losses to a

minimum, locate plants close to areas of high

energy consumption. Lag pipe runs to high

specifications; use low-temperature storage, time

controls and intelligent systems.

m. Waste heat recovery: Consider the use of a heat

exchanger if the building is mechanically

ventilated.

n. Building fabric: Specify insulation standards

above the current regulations, where possible.

Avoid the use of CFC-blown insulation.

o. Lighting installation: Energy-efficient lighting

fixtures (LED, CFL, T-5 lamps, electronic chokes

etc.) should be used, along with automatic

sensors to control and avoid unnecessary energy

use. Consider time and intensity controls rather

than general illumination. Benchmarks should be

as per the Energy Conservation Building Code

(ECBC).

p. Wall-to-window ratio (WWR), U Factor, solar heat

gain coefficient (SHGC) and visible light

transmittance (VLT) values: ECBC 2007 2recommends a maximum U factor of 3.3 W/m /K,

an SHGC of 0.25 for a WWR of 40%, and an

SHGC of 0.2 for a WWR of 40-60%. A glazing area

in excess of 60% of gross external wall area is not

recommended. The VLT value linked to WWR

should be as per ECBC. SHGC value is

particularly critical for south, east and west

facades. Glazing U factor and SHGC should be

minimized, whereas VLT should be maximized.

q. Controls: Employ controls that can respond to

internal and external conditions. Time and

temperature should be sensor-/bionic-controlled

according to the need of the occupants.

r. Decorative Finishes: Light-coloured finishes

improve lighting conditions and reduce the

intensity of light required.

s. Details/Standards of Work: Ceiling joints,

insulation, ventilation and thermal installations

should all be checked to ensure that the work has

been carried out to a high standard.

t. Operation: A user-friendly manual for occupants

should be provided to explain the efficient

operation of building and equipment.

u. Commissioning: Before occupancy, a building

should be flushed to remove solvents, gases,

Mr. A.K. Jain is the Ex.

Commissioner (Planning) of Delhi

Development Authority. He is a

member of the UN Habitat Research

Advisory Committee and a visiting

faculty at Delhi School of Planning

and Architecture.

vapours, smells and so on that could affect future

users. Check the performance of machinery

components and equipment against standards,

and put right any defect found that could have

major long-term effects on the energy

consumption of the building.

v. Incentives: Incentives, training and user

participation for energy efficiency and energy

savings should be encouraged.

Indian cities are facing a grim situation in terms of

energy. Unless a holistic and well-worked out

approach is evolved, the scenario would be even

worse, with the galloping economic development and

ever-growing urbanization. To tackle this situation,

there is a need to evolve a multi-pronged and multi-

disciplinary approach. This should begin with

increasing power generation and transmission

capacity and mobilizing private sector resources.

Parallel actions should be taken for conservation of

natural resources and exploring renewable and non-

conventional sources of energy including geothermal

heat and energy from wastes, bio mass and so on. At

the same time, it is necessary to resort to

management reforms, energy distribution

management and audit, adoption of energy-efficient

fuels, upgradation of technology and equipment,

energy tariff reforms, and controlling thefts and

losses. The key to future is a cybernetic form of

sustainable energy, which integrates symbiosis,

recycling and energy chains.

Space and energy are the basic dimensions of the

universe. There is a uterine relationship between the

Parallel actions should be taken for

conservation of natural resources and

exploring renewable and non-conventional

sources of energy including geothermal

heat and energy from wastes, bio mass

and so on. At the same time, it is

necessary to resort to management

reforms, energy distribution management

and audit, adoption of energy-efficient

fuels, upgradation of technology and

equipment, energy tariff reforms, and

controlling thefts and losses.

two. Unless there is a synergy between land use

planning, transportation and energy, we may not be

able to achieve sustainable development. An

important aspect of the space and energy symbiosis

is rediscovering ecological and non-conventional

sources of energy, in place of animate energy and

man-made sources.

Bibliography

1. CSE (Centre for Science & Environment), India-Environment

Report, New Delhi.

2. DDA (2007) Master Plan for Delhi-2021. New Delhi: Ministry of

Urban Development, Govt. of India.

3. GOI (1998) Development Alternatives, Environmental Priorities of

India. New Delhi: Govt. of India.

4. Girardet H. (1997) 'Sustainable cities - A Contradiction in Terms?'

In Satterwaite D. (ed.) Sustainable Cities. London: Earthscan

Publishers.

5. GOI (2001) Census of India Reports. New Delhi: Govt. of India.

6. Second United Nations Conference on Human Settlements,

(Habitat II), Istanbul 1996, India National Report. New Delhi: Ministry

of Urban Affairs & Employment.

7. Planning Commission, GOI (2007) Approach to 11th 5-Year Plan.

New Delhi: Govt. of India.

8. Hough M. (1995) Cities & Natural Process. London: Routeledge.

9. Israel A. (1992) Issues for Infrastructure management in the 1990s.

Washington, D.C.: World Bank.

10. Jain A.K. (2010) Making Infrastructure Work. New Delhi:

Discovery Publishers.

11. Jain A.K. (2001) Ecology and Natural Resource Management for

Sustainable Development. New Delhi: Management Publishing Co.

12. McHarg I. (1969) Design with Nature. New York: Natural History

Press.

13. Ministry of Urban Development, GOI (1988) Report of the National

Commission on Urbanisation. New Delhi: Govt. of India.

14. Rees W.E. (1997) Ecological Footprints and Urban Transportation,

Velocity. Barcelona.

15. Steinberg F. (1995) 'Sustainable Human Settlement Development

- Is It Possible?' Unpublished paper.

16. UNCED (1992) Local Agenda 21, RIO, World Environment

Conference, 1992.

17. World Bank (1994) World Development Report: Infrastructure for

Development. Washington, D.C.

18. World Resource Institute (WRI)/United Nations Environment

Programme/United Nations Development Programme and World Bank,

World Resources 2006-07: A Guide to the Global Environment.

ener

gy

and

env

ironm

ent s

ymb

iosi

sJa

nu

ary

- M

arc

h 2

01

2a

qua

rterly

mag

azin

e of

the

soci

ety

of e

nerg

y en

gin

eers

and

man

ager

s / I

ndia

60

ener

gy

and

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- M

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61

magic wand. By ranking this table in descending cost order, you will have, at the top of

page one, all your most important problems, ranked by their apparent avoidable costs.

I call this the overspend league table. When this logic is built into software (it can be

done in Excel) the energy manager's job suddenly becomes very quick and simple:

look at what is at top of the list, and if any of the deviations are significant in cost terms,

ask the people in charge of those parts of the enterprise what might have caused the

discrepancies. Given more space I might add one or two minor refinements but the key

idea is managing unexpected waste by reporting and ranking the apparent costs of

unexplained losses. Once the data are assembled it is quick-it usually takes less than a

minute a week almost regardless of the size of the enterprise-and it requires no

professional knowledge of

energy management

because all the

professional expertise is

'embedded' in the formulae

for expected consumption.

This means the task can be

delegated. The energy

manager who adopts this

approach soon develops a

reputation for asking the

right question of the right

person at the right time

when unexpected hidden

energy waste has occurred.

Any method can be used

for gathering data, from

manual meter readings

through to high-frequency

data collected by automatic

meter reading systems,

SCADA systems, or indirect

estimates from hours-run

records, ammeters, and

pulse counters. But note:

where high volumes of

automatic meter readings

are being collected, it is no

longer necessary to

examine charts of every

meter every week. The

overspend league table will

tell you which ones are

worth looking at.

Energy managers seldom

adopt this simple strategy,

which has the potential to

bring to his table the right

balance of data and

information amidst

legislative and market

pressures, as well as data

volume. Expensive

metering systems might not

always be the right solution,

the trick lies in not letting

your metering system

drown you in data and

making sure that you don't

miss the big picture.

...continued from page 03

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gu

est

edit

ori

al

Introduction to Power QualityDavid Chapman

Power quality and energy efficiencyAngelo Baggini and Franco Bua

Capacitors in a Harmonic-rich EnvironmentStefan Fassbinder

Integrated Earthing Systems (Earthing Grid)Rob Kersten & Frans van Pelt

Resilient and Reliable Power Supply in a Modern Office BuildingAngelo Baggini& Hans De Keulenaer

Electricity Systems for HospitalsAngelo Baggini

Life Cycle Costing - The BasicsDiedertDebusscher (Forte)

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