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NON-TECHNICAL LOSSES IN
ELECTRICAL POWER SYSTEMS
A Thesis Presented to
The Faculty of the
Fritz J. and Dolores H. Russ
College of Engineering and Technology
Ohio University
In Partial Fulfillment
of the Requirements for the Degree
Master of Science
by
Dan Suriyamongkol
November 2002
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THIS THESIS ENTITLED
NON-TECHNICAL LOSSES IN
ELECTRICAL POWER SYSTEMS
by Dan Suriyamongkol
has been approved
for the Department of Electrical Engineering and Computer Sciences
and the College of Engineering and Technology
___________________________________________________
Brian Manhire, Professor
___________________________________________________
Richard Dennis Irwin, Dean
College of Engineering and Technology
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ACKNOWLEDGMENTS
First, I would like to thank Dr. Brian Manhire, my advisor, for all of his support,
insight and invaluable help during the preparation and information collection for this
thesis.
There is a large amount of information in this thesis that would not be available
without the help from the following persons. Mrs. Prachumporn Bunnak, Acting Director
of the Department of Power Economics, the Provincial Energy Authority of Thailand
(PEA), authorized unprecedented access to PEA information and operations. Mr. Barvorn
Phattanak, Assistant Manager of the Power Economics Division, who coordinated my
information gathering effort at PEA excellently. Mr. Youngyuth Sonjaiyuth, Head of the
Three-Phase Meter Installation and Inspection Group at PEA, who provided me with
great insight into electricity theft and a priceless view from the field.
At American Electric Power, I was fortunate to receive insights from William A.
Randle, John H. Provanzana, and Jack E. Carr. The World Bank proved an invaluable
resource through the report [2] by the Energy Sector Unit, sent to me by Alfred B.
Gustone.
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TABLE OF CONTENTS
ACKNOWLEDGMENTS........iii
LIST OF FIGURES......vi
LIST OF TABLES...........vii
CHAPTER 1 INTRODUCTION 1
1.1 Losses in Electrical Power Systems1.2 Loss Analysis in Power Systems1.3 Electricity Theft1.4 Past Documentation of Non-Technical Losses1.5 Conclusions and Future Work
CHAPTER 2 ANALYSIS OF LOSSES IN
ELECTRICAL POWER SYSTEMS 6
2.1 Technical Losses in Power Systems 62.2 Technical Losses: Measurement and Practical Cases 112.3 Losses With Non-technical Losses Present 19
CHAPTER 3 NON-TECHNICAL LOSSES:
ELECTRICITY THEFT 27
3.1 Brief Background on Electricity Theft 27
3.2 Methods of Electricity Theft 30
CHAPTER 4 PAST DOCUMENTATION OF
NON-TECHNICAL LOSSES 35
4.1 Provincial Energy Authority of Thailand 364.2 American Electric Power 464.3 World Bank Eastern Europe and Former Soviet Union 47
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CHAPTER 5 CONCLUSION AND SUGGESTIONSFOR FURTHER WORK 55
BIBLIOGRAPHY 58
APPENDIX A
Principles of Power Systems Analysis:
Basic Load Flow and Loss Calculations 59
APPENDIX B
Two-Bus Load Flow Analysis Programs in MATLAB 68
APPENDIX C
Transmission Line Specifications for PEA 79
ABSTRACT
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LIST OF FIGURES
2.1 Single-Line Diagram of a Simple Two-Bus Power System 9
2.2 Three-Bus Power System 11
2.3 Single-Line Diagram of a Two-Bus, Two-Load Power Systemwith Known Load and Known Transmission Line Data(Each bus can be the Slack Bus) 12
2.4 Load Demands for the Two-Bus Power System from Figure 2.3 12
2.5 Profile of Load Power Factors for Test Power System in Figure 2.3 14
2.6 Energy Losses Calculated Using the Two-Bus Test System withBus 1 as the Slack Bus and then with Bus 2 as the Slack Bus 16
2.7 Energy Losses in the Two-Bus Test System and a Comparisonbetween the Average Losses Computed Using the DetailedLoad Schedule and Losses Computed from Average Power 18
2.8 Demand and Power Factor Changes at Load 2 Caused by Non-Technical Losses
2.9 Effects of NTL on Transmission Line Losses 24
3.1 Basic Components of a Watt-hour Meter.
3.2 Early recording meters: Sangamo Gutmann type A (c. 1899-1901)watt-hour meter, left, and Westinghouse ampere-hourmeter by Shallenberger
3.3 Modern recording meters: Schlumberger J5S (1984),and General Electric I-70S (1968)
3.4 Three-phase Watt-hour Meter Connection
3.5 Parts of a Single-phase Watt-hour Meter Where Tampering Often Occur
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4.1 Breakdown of PEA Consumers Sorted by Consumption, October 2000 41
4.2 Breakdown of PEA Consumers Sorted by Numbers ofIndividual Consumers, October 2000 41
A.1 A General Connection Situation at an Arbitrary Bus(denoted Bus A, where G denotes a generator unit). 66
B.1 Single-line diagram of a two-bus, two-load power system with
known load and known transmission line data.
Each bus can be the slack bus. 73
B.2 Information Flow Through the MATLAB Load FlowAnalysis Program. 75
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LIST OF TABLES
2.1 An Example of a Loads Consumption Information 20
2.2 Summary of Effects of Adding NTL to the Two-Bus Test System 26
4.1 PEA Policies for Billing CustomersWho Perpetrated Electricity Theft 43
4.2 Meter Inspection Protocols and Schedules for PEA 44
4.3 PEA Guidelines and Schedules for ReportingMeter Inspection Results 45
4.4 Meter Tampering Found Among High Voltage Consumersin Thailand Between October 2000 and June 2001. 46
4.5 Meter Tampering Found Among Low Voltage Consumersin Thailand Between October 2000 and June 2001. 47
4.6 Extent of the Electric Utility Non-Payment Problemin Eastern Europe and Former Soviet Union Nations 52
4.7 Capacity Utilization in the Power Sector of FSU 53
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CHAPTER 1
INTRODUCTION
A news article estimated that electricity theft in the United States costs billions of
dollars a year1. Such estimates were the beginning of this research. Electricity theft is part
of a phenomenon known as non-technical losses (NTL) in electrical power systems.
This research aims to investigate the nature of non-technical losses in power systems,
their sources, the measurement of non-technical losses, some measures taken by selected
utilities to reduce them, and possibly their impact on the system.
In this introduction, a summary of the main parts of this thesis will be presented.
Chapter 2 deals with the simulation and calculation of losses in power systems and the
effects that NTL have on those losses. Various forms of NTL and the utilities measures
to counter them are presented and discussed in Chapter 4. Before that, special attention
will be given to the watt-hour meter and various ways to tamper with it in chapter 3. The
study of utilities handling and recording of NTL cases was made possible by the
cooperation provided by the Provincial Energy Authority of Thailand (PEA) for
information obtained in rural Thailand, while information on NTL and utilities reactions
in the United States was based on a series of e-mail correspondences with officials of
American Electric Power. Also, the World Bank provided some information on the
1 Bill Nesbit, "Thieves Lurk - The Sizable Problem of Electricity Theft", Electric World T&D,www.platts.com/engineers/issues/ElectricalWorld/0009/, September/October 2000
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effects of wide-scale occurrences of NTL in Eastern Europe and Former Soviet Union
(FSU) nations.
1.1 LOSSES IN ELECTRICAL POWER SYSTEMS
In order to study non-technical losses, which constitute a portion of the total
losses in electrical power systems, the logical first step is to understand the complete
picture of power systems losses. Power system losses can be divided into two categories:
technical losses and non-technical losses.
Technical losses are naturally occurring losses (caused by actions internal to the
power system) and consist mainly of power dissipation in electrical system components
such as transmission lines, power transformers, measurement systems, etc. Technical
losses are possible to compute and control, provided the power system in question
consists of known quantities of loads. In this thesis, it will be argued that the distortion of
load quantities caused by NTL will distort the computations for technical losses caused
by existing loads, thereby rendering any results ineffectual.
Non-technical losses (NTL), on the other hand, are caused by actions external to
the power system, or are caused by loads and conditions that the technical losses
computation failed to take into account. NTL are more difficult to measure because these
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losses are often unaccounted for by the system operators and thus have no recorded
information. The most probable causes of NTL are:
Electricity theft
Non-payment by customers
Errors in technical losses computation
Errors in accounting and record keeping that distort technical information
The most prominent forms of NTL are electricity theft and non-payment, which
are thought to account for most, if not all, of NTL in power systems. However, the other
two sources of NTL listed above are not analyzed thoroughly in this thesis, so their
contribution to NTL is unknown.
The methods used to perpetrate electricity theft are discussed in Chapter 3. A few
examples of documented cases of customer non-payment and the measures used to
handle them are discussed in Chapter 4.
Other forms of NTL may exist, such as unanticipated increases in system losses
due to equipment deterioration over time, but are usually ignored in any calculations.
System miscalculation on the part of the utilities, due to accounting errors, poor record
keeping, or other information errors may also contribute to NTL. These losses are
discussed in this thesis due to insufficient background information.
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1.2 LOSS ANALYSIS IN POWER SYSTEMS
Technical losses in power systems are caused by the physical properties of the
components of power systems. The most obvious examples are the power dissipated in
transmission lines and transformers due to their internal electrical resistance. Technical
losses are easy to simulate and calculate; computation tools for calculating power flow,
losses, and equipment status in power systems have been developed for some time.
Improvements in information technology and data acquisition have also made the
calculations and verifications easier.
In this thesis, a simple power flow calculation is used to study relevant aspects of
technical losses in a very simplified power system. The results of those simulations are
presented and discussed in chapter 2. The technical principles of power flow calculations
and loss analyses are briefly discussed in Appendix A, but more useful treatments of the
subject can be found in [1].
Also discussed in this thesis is the required information for successfully analyzing
power systems using load flow analysis, the practical availability of the said information,
and the effects of adding known non-technical losses to the simulated power system
analysis. Results from simulations in Chapter 2 suggest that the use of traditional
technical losses calculation tools would not be useful in NTL calculations. This is due to
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the lack of information on NTL loads attached to power systems, as well as the lack of
information on legitimately recognized loads themselves.
1.3 ELECTRICITY THEFT
All of the utilities and sources contacted by this author agreed that the dominant
component of NTL is electricity theft and non-payment [2], [5], [6], [7]. Electricity theft
is defined as a conscience attempt by a person to reduce or eliminate the amount of
money he or she will owe the utility for electric energy. This could range from tampering
with the meter to create false consumption information used in billings to making
unauthorized connections to the power grid. Common methods of electricity theft are
discussed in Chapter 3.
1.4 PAST DOCUMENTATION OF NON-TECHNICAL LOSSES
Non-payment, as the name implies, refers to cases where customers refuse or are
unable to pay for their electricity. Non-payment cases, magnitudes and some solutions are
presented in Chapter 4. All of the non-payment information provided here are courtesy of
the World Bank Energy Sector Unit [2]. Some solution approaches reported by various
organizations that contributed to the World Bank report [2] are also included.
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Electricity theft is a problem that has long been known to utilities. Chapter 4
provides summaries of policies implemented by two utility companies: the Provincial
Energy Authority of Thailand, and American Electric Power, based in the United States
of America. The summaries include the impact of electricity theft on each company, their
procedures for dealing with electricity theft, and results of revenue recovery efforts by
PEA and AEP.
1.5 CONCLUSIONS AND FUTURE WORK
The conclusions from Chapters 2, 3, and 4 are given in Chapter 5 and can be
generally stated as follows:
NTL are nearly impossible to measure using traditional power system analysis
tools. This is due to the lack of information on both NTL and the legitimate loads
in the system, which translates to insufficient inputs for any meaningful loss
calculations.
Electricity theft, a common form of NTL, involves tampering with meters to
distort the billing information or direct connections to the power system. Each
type of theft is well documented by utilities [2], [5], [6], [7].
Utilities contacted for this thesis all agreed that electricity theft is the most
prominent form of NTL, while customer non-payment can also lead to significant
problems in areas that fail to handle the situation properly [2], [5], [6], [7].
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All of the personnel interviewed for this thesis (listed in the Acknowledgement
section) also stated that due to reasons given in Chapter 2, there have been no
attempts to calculate for NTL using current measurement techniques.
Possible future work on this topic is also discussed in Chapter 5. The possible
future topics include: use of newer technologies to increase measurement capabilities,
possible cost-benefit analyses on the current measures favored by the utilities compared
with other possible measures, and more detailed examinations of the NTL causes listed
above that are not discussed here.
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CHAPTER 2
ANALYSIS OF LOSSES IN POWER SYSTEMS
Losses incurred in electrical power systems have two components: technical
losses and non-technical losses. Technical losses mean losses that happen because of the
physical nature of the equipment and infrastructure of the power systems, i.e., I2R loss
or copper loss in the conductor cables, transformers, switches, and generators. Loads
are not included in the losses because they are actually intended to receive as much
energy as possible. Technical losses can be calculated based on the natural properties of
components in the power system: resistance, reactance, capacitance, voltage, current, and
power are routinely calculated by utility companies as a way to specify what components
will be added to the systems. Though the data and tools needed for calculating losses in
power systems are available, current techniques have certain drawbacks regarding such
calculations. This issue will be addressed in the section Technical Losses in Power
Systems below. The effects of adding non-technical losses to a power system will be
examined in the section Losses with Non-technical Losses Present later in this chapter.
2.1 TECHNICAL LOSSES IN POWER SYSTEMS
Technical losses in power systems mean power losses incurred by physical
properties of components in the power systems infrastructure. A common example of
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such losses is the power loss caused by resistance of transmission lines. The average
power loss in a transmission line can be expressed as
Ploss = Psource Pload (2.1)
where Psource means the average power that the source is injecting into the transmission
line andPloadis the power consumed by the load at the other end of the transmission line.
This is a simple enough calculation, except that power and current are both time-
dependent functions and that energy not power is the quantity that gets translated into
money. Energy is power accumulated over time, or
=b
a
lossloss dttPW )( (2.2)
with a and b as the starting and ending points of the time interval being evaluated,
respectively. As a result, we need a fairly accurate description ofPloss as a function of
time to make a reliable prediction of energy loss (Wloss). And power, in a single-phase
case, with sinusoidal current and voltage can be represented by
P1- = IVcos (2.3)
with P, V and I being the average power, rms voltage and rms current of the element in
question, respectively. The term cos is the power factor of the element in question,
while is the phase difference between the voltage and the current waveforms.
From the above it can be summarized that the information needed to calculate the
average power loss sampled at an instant of time in a transmission line or an arbitrary
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element in a power system has to be one of the following sets (all variables are single-
phase, rms values and average power):
1.) Voltage across the element, resistance, orP=V2/R
2.) Current and resistance, orP=I2R
3.) Voltage, current and phase difference between the two, orP=IVcos
These sets of data and choices of calculations are the options that an engineer will
have for computing power losses in a load-flow analysis2. But in order to gain V or I,
both rms values, the voltage must be known at two ends of the element that is evaluated,
at all times or as averages. This means the terminals that feed consumer loads must be
appropriately monitored at all times using some of the more sophisticated meters that
could store and compute average and instantaneous values that the load-flow analyst is
interested in.
The information about the power sources and loads listed above are needed to
determine expected losses in the power system using load-flow analysis software. The
actual losses are the difference between outgoing energy recorded by the source (e.g., at a
substation) and energy consumed by the consumers, which is shown on the bills. The
discrepancy between expected losses and actual losses would yield the extent of non-
technical losses in that system.
2 Load-Flow Analysis is a computational tool for calculating power flow in electrical power systems (moredetails in [1]).
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Figure 2.1 Single-Line Diagram of a Simple Two-Bus Power System.
Figure 2.1 above shows a simple power system with two buses (nodes), one a
generator, and the other a load. For the simulations undertaken for this research, the
voltage, current, power, and power factor of the generator have known values at the same
time intervals, and, consequently, the current going through the transmission line. The
loss in the transmission line is easily computed using the current and transmission line
resistance values. Information of the loads power and power factor are unknown, but at
this point the information at the generator is sufficient to determine whats happening to
the transmission line using simple calculations:
I* =load
load
V
S (2.4a)
and Ploss = (V)I* (2.4b)
With Sload, Vload, Ploss, I, andR are the load apparent power, load voltage, power
loss in the transmission line, current in the transmission line, and transmission line
resistance, respectively (all values are complex values), whileI* is the complex conjugate
of the current. The same relationships hold when analyzing these quantities as phasors or
rms values. Any major calculations become unnecessary whenIcan be measured directly
LoadG
Bus 1 Bus 2I
Transmission Line
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and the transmission line properties are known, which is never true for practical power
systems. Companies that generate and distribute electricity usually measure currents that
enter and leave their facilities in order to measure the energy that is bought or sold. For
areas outside the companies facilities, i.e., residential or business consumer areas, only
peak power and accumulated energy are usually measured.
However, the low voltage transmission systems (below 24,000 volts or 24 KV)
are not as thoroughly measured because of the costs of the added metering. This is the
reason power flow solutions are used to estimate the state the various points in the
system. Power flow analysis is generally used for specifying equipment ratings after
estimating the worst-case loading scenarios.
Finding the current in the one bus going out of a metered generator is simple, but
in reality there are often many interconnected buses and many more elements in the
system. Just expanding the two-bus characterization by one step would yield a three-bus
system shown in Figure 2.2 below. Using Kirchhoffs Current Law to solve for the
currents at the bus where the two transmission lines meet,
I1 = I2 + I3 (2.5)
As in the two-bus case, the current in Transmission Line 1 is measured. To
determine the current in Transmission Line 2 (I2), however, the current going into Load 1
must to be known. This means there has to be a meter at Load 1 with the same
capabilities as the meter at the generator in order to computeI2 at desired times.
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Figure 2.2 Three-Bus Power System
More detailed analysis of technical losses and their calculations in practical power
systems can be found in Appendix A and [1].
2.2 TECHNICAL LOSSES: MEASUREMENT AND PRACTICAL CASES
A more common case worth performing calculations for is a two-bus subsystem
with loads at both busses and one bus selected as a slack bus3
with constant voltage.
This configuration is chosen for simplicity. The bus with constant voltage is presumed, as
is the case with most systems, to be the one connected to the larger system that has a
relatively infinite supply of electrical energy with constant source characteristics. The
diagram for a two-bus system is shown in Figure 2.3 below where the electrical
3 The term slack bus refers to a reference bus (or node) in the system with known voltage and phase anglenecessary for analysis of the system. The slack bus is often treated as a source that can inject infinite(relatively very large) power and energy into the system and maintain constant voltage and phase anglethroughout the analysis. In analyzing small power systems connected to larger systems, the slack bus wouldbe the point where the system is interconnected to the wider system that can inject large amount of powerand energy into the system of interest.
Bus 3
G
I1 I3
I2
Bus 1 Bus 2
Transmission Line 1
Transmission Line 2
Load 1
Load 2
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properties needed to complete a load-flow calculation for power loss in the transmission
line are provided below and in Appendix C. The load profiles for each of the two loads
are shown in Figure 2.4 below.
Figure 2.3 Single-Line Diagram of a Two-Bus, Two-Load Power System with KnownLoad and Known Transmission Line Data (Each bus can be the Slack Bus)
0
50
100
150
200
250
300
350
400
450
500
PowerDemand(KVA
)
0:0
0
1:0
0
2:0
0
3:0
0
4:0
0
5:0
0
6:0
0
7:0
0
8:0
0
9:0
0
10:0
0
11:0
0
12:0
0
13:0
0
14:0
0
15:0
0
16:0
0
17:0
0
18:0
0
19:0
0
20:0
0
21:0
0
22:0
0
23:0
0
Time of day
Power Demands For The Two-Bus Test Power System
Load 1 Demand, KVA Load 2 Demand,K VA
Figure 2.4 Load Demands for the Two-Bus Power System from Figure 2.3
From the system specifications discussed below, it can be seen that this test
system is a very simplified one numerically and conceptually. Each load has its own
profile, i.e., each load varies with time and has a different pattern over a period of 24
Bus 1 Bus 2
Load 1 Load 2Transmission Line
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hours. To make the test loads more realistic they are represented as two sets of power
demands with different operation schedules comparable to residential and industrial
areas. The grey profile that peaks during the daytime and drops off at night represents an
industrial load, while the black profile represents a residential load.
The load peaks are at 500 KVA for load 1 and 350 KVA for load 2, which are
reasonable levels for loads connected through 750 KVA-rated and 500 KVA-rated
transformers, respectively. The average load demands are 291.67 KVA and 153.96 KVA
for load 1 and load 2, respectively. Load power factors are shown in Figure 2.5 below,
with average values of 0.83 and 0.78 for load 1 and load 2, respectively. Transformers are
omitted from the simulation program for simplicitys sake. Transmission line resistance
and reactance values are taken from 22000-volt transmission line datasheets provided by
PEA (see Appendix C). The conductor size and line length were chosen arbitrarily from
the datasheet, with the maximum conductor size of 185 mm2 chosen to avoid overloading
the line. A line typical length of 2 kilometers (about 1.25 miles) was chosen arbitrarily.
Finally, the loads were assumed balanced between all three phases, to avoid
complex computing. This means that only the positive sequence impedance values need
be used in calculations and negative and zero sequences can be ignored.
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Load Power Factors
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0:00
2:00
4:00
6:00
8:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
Time of day
PowerFactor
Load 1 Power Factor Load 2 Power Factor
Figure 2.5 Profile of Load Power Factors for Test Power Systemin Figure 2.3
Specifications of the two-bus test system (Source: see Appendix C)
Base Values4: 22000 Volts, 100 Ampere, 2.2 MVA, 220 Ohms
Transmission Line:
Resistance = 2 km * 0.175713 Ohms/conductor/km * 3 conductors
= 1.054278 Ohms = 0.004792 per unit (p.u.)
Reactance = 2 km * 0.334439 Ohms/cond./km * 3 cond.
= 2.006705 Ohms = 0.009121062 p.u.
4 The term Base Value is used in per-unit calculations; for more details, see [1].
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The test system has been used to be a source for a simple load-flow calculation
program written in MATLAB to determine the losses for the transmission line (see
Appendices A and B). The results were later compared to those obtained using the Power
Education Toolbox [10], and Power System Simulator [11]. The specifications
provided about the loads are the following: power demands of the loads at various times
of the day over 24 hours; power factor values over the same time period; the averages of
power demands and power factors. The incurred transmission losses are shown in Figure
2.6 below. The trends suggest that load number 1 is an office or workplace with a peak
demand of 400 kilowatts and the load level being high during office hours. Load number
2 is presumed to be a residential area with a peak demand of 241.5 kilowatts and load
levels that rise around time for breakfast and dinner times.
In the case where bus 1 is used as the slack bus, the average power loss in the
transmission line is around 74.53 watts, while the power loss calculated using the average
values of power and power factor is 51.69 watts.
As seen in Figures 2.4 and 2.5, the load profile changes according to the time of
the day and consumes a finite amount of energy. The load energy can also be represented
by a time invariant average demand value with the same amount of consumed energy
over the same amount of time. The point being made here is that since the utility bills
often only include energy, a number of vastly different chronological power profiles can
be introduced which end up consuming the same amount of energy.
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The MATLAB simulator was used to calculate the transmission losses for the
load demands and power factor for each hour, first using bus 1 as the slack bus, and then
with bus 2 as the slack bus. The results are shown in Figure 2.6 below. The losses based
on the average demand and power factor values were calculated only with bus 1 as the
slack bus, with results shown in Figure 2.7. The result is that the average of losses
calculated using the sum of data from individual times is notequal to the losses
calculated using the average values, as seen in Figure 2.7 below for the case where bus 1
is used as the slack bus. The reason for this inequality will be examined later in this
chapter.
Comparison of Losses Using Different Slack Buses
0
500
1000
1500
2000
2500
Time of day
Losses
(KWh)
Losses Using Bus 1 as Slack Losses Using Bus 2 as Slack
Figure 2.6 Energy Losses Calculated Using the Two-Bus Test System withBus 1 as the Slack Bus and then with Bus 2 as the Slack Bus
In the case where bus 1 is the slack bus, the total energy lost in the transmission
line each day is 6439.983 kilowatt-hours, while the energy computed using the average
power and power factor turns out to be 4466.707 kilowatt-hours. The difference is about
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1973.276 kilowatt-hours a day (30.64 % of actual loss) or, at February 2002 prices in
Athens, Ohio5, $98.68 a day.
Total Losses Calculated From Various Information
0
5000
10000
15000
20000
25000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
No. of Days With Identical Load Power Profiles (Days)
Total Daily Losses Using Hourly Demand (Bus 1 Slack)
Total Losses Using Average Demand (Bus 1)
Losses Using Hourly Demand (Bus 2 Slack)
Losses Using Average Demand (Bus 2)
Figure 2.7 Energy Losses in the Two-Bus Test System and a Comparison between theAverage Losses Computed Using the Detailed Load Schedule and Losses Computed
from Average Power. (Note: data shown as straight line to illustrate the different levelswhen using different slack busses)
This example illustrates how determining losses in transmission lines relies on
availability of information. And the information on the loads can be obtained either by
the customer monitoring the load or the utility monitoring the junction where the load is
connected. Either way, there has to be significant investment in measurement hardware
because average values are shown to be inaccurate for calculating real losses. The
5 Energy rates are published by American Electric Power at www.aepcustomer.com/tariffs/default.htm
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average values of power factor and voltages used to compute the losses in equation 2.4a
and 2.4b, for example, are meaningless because power factor and voltages may not peak
at the same time.
The nature of most loads means that the current values must be taken at intervals
small enough to make an accurate representation of the actual load characteristics. This is
where the measurement of loss in transmission lines gets complicated. The meters
required for useful measurements of current or power factor are significantly more
expensive than the simpler kind that only records consumption over time. Meters that can
record a load power profile are used mainly at substations, power plants, and by large
consumers that manage their consumption. Most locations with these meters give
accurate descriptions of losses in high-voltage power lines where there is very little, if
any, electricity theft.
Transmission and distribution line sections that are most vulnerable to theft are
the medium- and low-voltage lines that connect to most of the consumers. These lines are
numerous and usually highly interconnected, which means that isolation of an area for
calculation is difficult. The two-bus calculations above are done with one of the buses
held constant, and there must always be a slack bus with constant known properties in
order to run load flow analyses. In medium- and low- voltage subsystems, however, the
bus voltages are often shifting along with consumer demand changes and even voltage
levels at the incoming feeders sometimes fluctuate.
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At this point, it is getting clear that making calculations for expected losses
accurately is nearly impossible in practice. This is because the data required at least in
Thailands case is very difficult to gather. Once again, refer to the list of possible ways
to calculate power above to see the data needed. The obstacle here is that meters installed
and used by Thailands utilities are all old models that only record peak power and
energy in kilowatt-hours for household loads. Even the industrial meters only record the
worst-case power factor, which has no bearing on an average much less record a profile
of power and power factor. Some meters record demands (power) at peak hours, which
again have no relationships with an average value or values that are usable in load flow
analyses.
The way to obtain a fairly accurate value of average load demand is to utilize the
information the utilities use to calculate the electric bills. The calculation requires energy
consumption accumulated up to the beginning of the time period (usually a month) and
the consumption accumulated at the end of the time period. The accumulated
consumption at the end of the period is subtracted by the accumulated consumption at the
beginning of the period. The result is the total consumption during the time period in
kilowatt-hours, and the portion of the bill for energy consumption is based on this
number.
The average demand for that same time period is the total energy consumption
divided by the length of the time period, in seconds. This information is always available
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for metered loads, because it is what the utilities revenues are based on. For example, a
load that has the consumption information listed in Table 2.1 would have the average
demand as calculated below.
Table 2.1 Example of Load Consumption Information
Date/Time (mm/dd/yy, hr:min:sec) Consumption, kilowatt-hours
Begin: 01/03/02 15:06:00 23,558,407
End: 02/01/02 13:55:30 23,634,462
Calculation results
Total time elapsed: 2,501,730 Seconds
Total energy consumed: 76,055 Kilowatt-hours
Average demand: 109,459 Watts
The average demand is not something difficult to find, as seen above, but the
problem for using this in load flow calculations is that the corresponding power factor
must be found. Power factor, as mentioned earlier, is not a quantity that is recorded by
most meters. The high-voltage or high-demand meters that record power factor exists
mainly in utilities installations or very large loads, while medium-sized loads often
record only the worst-case power factor for the purpose of billing, which is not useful
when it comes to finding the average power factor.
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2.3 LOSSES WITH NON-TECHNICAL LOSSES PRESENT
Non-technical losses are difficult to quantify. They refer to losses that occur
independently of technical losses in the power system. Two easy examples of sources of
such losses are component breakdowns that drastically increase losses before they are
replaced in time, and electricity theft. Losses incurred by equipment breakdown are quite
rare. These include losses from equipment struck by lightning, equipment damaged by
time, the elements and neglect. Most power companies do not allow equipment to
breakdown in such a way and virtually all companies maintain some form of maintenance
policies. Equipment failures due to natural abuses like snow and wind are also rare, for
equipment is selected and infrastructure designed with local weather and natural
phenomena considered.
Non-technical losses can also be viewed as undetected load; customers that the
utilities dont know exist. When an undetected load is attached to the system, the actual
losses increase while the losses expected by the utilities will remain the same. The
increased losses will show on the utilities accounts, and the costs will be passed along to
the customers as transmission and distribution charges. In a simulation discussed below,
an NTL load is added to the load at bus 2, the load that exhibits patterns similar to a
housing load, as implied by the hours that load activities increase and decrease. The
reason this load is chosen is that most NTL cases in reality are found in residential areas
or light industrial areas [2], [5], [6], [7].
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From the technical loss analysis above, the effects of an undetected load attached
to one of the buses in the two-bus test system can be measured by adding extra demand
values to one of the loads and evaluating the changed losses. The extra load may be
simulated in a simplistic way by adding a profile of demands to the bus 2 load in the form
of adding VA values to the original demand and reducing the total power factors by
subtracting a power factor contribution for each value of added load. The pf
contributions chosen here were negative because the NTL load is assumed to be
inductive, i.e., motors or light fixtures. The profile of the added NTL and the total load
and the pf contribution to the load pf at bus 2 are shown in Figure 2.8 below. The
simulation is run with bus 2 as the slack bus. The NTL pf contribution is negative at all
times because the NTL load is assumed to be inductive.
After the simulation was completed and evaluated, some notable results were
evident. First, the increase in load demand and the increase in transmission losses were
not at the same levels. This is caused by the power factor contribution of the NTL load.
Indeed, the losses increased at a greater rate than the loads. On average, the load VA
increased by about 12.67 KVA, or about 7.9 per cent, while the losses had an average
increase of 23.39 per cent. The average loss here is computed by averaging the overall
loss increase for each hour.
It can be seen from Figure 2.9 below that the increase in demand caused by NTL
would also increase transmission line loss disproportionately. Even though the increase in
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transmission loss places a greater burden on the transmission equipment, the greater
cause for concern would be the NTL load itself. During a 24-hour period, the increase in
transmission losses amounts to about 771 kilowatt-hours a day, or about $38.59. The
costs of the NTL itself during the same time period is much higher at 675,953 KW-h a
day, or $ 33,797 a day.
(a) NTL Contribution to Load 2 of the Test System
0
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Load 2 Demand, VA NTL Demand, VA
(b) Negative power factor Contributions by NTL
-0.02
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0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
Time, Hrs.
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tive
pf
Con
tributions
Figure 2.8 Demand and Power Factor Changes at Load 2 Caused by Non-TechnicalLosses
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(a) Effects of NTL on Loads and Losses
0
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Increase in Transmission Losses Due to NTL Increase in Load Due to NTL
(b) Effects of NTL on Transmission Line Losses
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Losses without NTL Losses with NTL
Figure 2.9 Effects of NTL on Transmission Line Losses.
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The transmission line losses are very small compared to the loads themselves, but
the increased losses should not be ignored because they mean power dissipated in the
transmission lines as heat. When the lines get overheated, serious consequences can
follow, from loss of material strength to the weakening of insulation possibly dangerous
if the lines are in a crowded area.
The most noticeable effects of NTL, of course, are the monetary costs. In the
simulation results above, the load at bus 2 amounts to about $ 503,604 a day and the NTL
costs the utilities about $ 33,797 a day. The transmission costs due to the NTL, about $
38.59 a day, are just the transmission costs for the two kilometers of transmission lines
used in the simulation. In reality, the transmission costs would be similarly increased all
along the supply path back to the power plant, which could mean a very significant
increase depending on the distance. Table 2.2 below provides a summary of the results
obtained by the simulation of the two-bus system and the effects of NTL.
Note that once the NTL itself is taken into account, the discrepancy caused by
using average power to compute transmission losses becomes small, $4 out of nearly
$34,000. This is one of the reasons that the utility departments that work on electricity
theft interviewed for this research did not seem interested in using load-flow software.
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Table 2.2 Summary of Effects of Adding NTL to the Two-Bus Test SystemTotal daily losses Computed for each
hour in the load profileComputed usingaverage demands & pf
Transmission losses without NTL,KWH
6,439.98 4,466.70
Transmission losses with NTL,KWH
7,211.57 5,169.48
Load demand at bus 2 withoutNTL, KWH
10,061,280 10,061,280
Load demand at bus 2 with NTL,KWH
10,737,230 10,737,230
Total increased losses, KWH(increased load plus increasedtransmission loss)
676,721.59 676,652.78
Total increased losses, $ 33,836 33,832
The last issue to be addressed in this section is who pays for the NTL costs. The
transmission and distribution costs in the United States are calculated as part of the
customers bills, while in Thailand the customers are usually charged a single flat energy
rate that includes all services. The US utilities have to un-bundle the charges because
widespread deregulation in various states has made the generation and distribution
companies split into separate entities [12].
This means that in the US, the transmission and distribution losses that increased
due to NTL would be charged either to the existing customer whose power lines are
illegally tapped, or the utility, depending on the method of theft (see Chapter 3 for
details). Who pays for the NTL loads depends on how the NTL loads are connected to the
power system. If the NTL loads are connected to the systems transmission lines before
they reach the customers meters, the utilities will assume the costs of the NTL loads.
However, if the NTL loads are connected at a point beyond innocent customers meters,
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the customers will be stuck with the transmission costs and, more seriously, the increased
loads. In Chapter 3, there are lists of various types of electricity theft that include both
types of NTL described in the paragraph above.
In conclusion, the measurement of NTL and its effects on electrical power
systems as a whole using existing analytical tools would be possible only if information
about the NTL loads themselves is available to the analyst. The information would have
to include either the NTL loads power consumption profile comparable to the legitimate
loads being analyzed at the same time, as well as the NTL power factor, or power factor
contribution as in the case shown above. In interviews with experienced engineers,
technicians, and utilities officials mentioned in the acknowledgement, it is their opinion
that NTL cases cannot be directly measured because of the information gathering effort
required. After all, the people who make illegal connections to the power system are
unlikely to participate in any form of survey freely when their own illegal actions would
come to light.
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CHAPTER 3
ELECTRICITY THEFT:
A MAJOR COMPONENT OF NON-TECHNICAL LOSSES
3.1 BRIEF BACKGROUND ON ELECTRICITY THEFT
As shown in Chapter 2, non-technical losses (NTL) are difficult if not
impossible to detect using information that is typically collected by utility companies.
In some areas, the loads are not even metered or are metered communally [2], rendering
any loss calculations technical or not for that area useless. The approach used by both
utility companies contacted [2], [5], [6] involves primarily involves field staff monitoring
meters and access points in the system on a regular basis (see Chapter 4 for more details).
Sometimes this involves regular meter readers receiving special training for spotting
irregularities, and sometimes when high voltage and large consumption is involved it
involves meter technicians making dedicated meter and transformer inspection trips (see
Chapter 4).
The reason that meter inspection is the main method of NTL detection is because
the utilities consider electricity theft to be the major source of NTL and the majority of
electricity theft cases involves meter tampering or meter destruction [2], [5], [6]. The
term meter used in this and other chapters refers to the watt-hour recording meters used
in virtually every household to record and calculate electric bills by utility companies.
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The principles of operation for watt-hour meters essentially have not changed
since the 1880s and the 1890s, when the watt-hour meter was invented [3]. The basic
principle for a single-phase energy measurement meter, first commercially used in 1894,
is as follows. First, there are two coils that produce electromagnetic fluxes: a coil,
connected across the two leads, that produces a flux proportional to the voltage and a coil
connected in series with one of the leads that produces a flux proportional to the current.
The dot product of those two fluxes creates a force proportional to the load power. An
illustration of the basic components of the watt-hour meter is shown in Figure 3.1 below.
The development of these meters, technological improvements, and alternative designs,
which reflected the growing power industry in the late 19th
century, is chronicled in detail
in [3].
In early designs, such as the ones shown in Figure 3.2 below, the meters were not
enclosed and all the parts and the meter installation were easily accessible to anyone.
However, as early as 1899, the minutes of meter committees of the Association of Edison
Illuminating Companies [meter paper] showed that electricity theft was a concern early
on. In response to the committees recommendations, the following improvements
along with other efficiency and accuracy improvements were added [3]:
First, a dust- and insect-proof cover
Second, a cover and frame so shaped and retained together
as to render dishonest and curious tampering with the internal
mechanism as nearly impossible as may be.
Third, means for fully protecting from malicious tampering
the heads of all screws in the base which bind the damping
magnets, etc., in place without rendering them inaccessible to
those authorized to reach them.
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Figure 3.1 Basic Components of a Watt-hour Meter.Clockwise from top left: coil connections for voltage and current sensing elements, the
rotating disc that records consumption, and the basic construction.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)
This suggests that the problem of electricity theft has obviously been around almost as
long as power systems have been around. Modern meters, such as those in Figures 3.3
below, are relatively well enclosed and have seals that would reveal tampering. However,
theft can and does occur. Most utilities train their staff to spot tampering, but sometimes
the access to the inner mechanisms can be achieved with a very small hole, possibly
drilled using small tools and done at less obvious parts of the enclosure [7].
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Figure 3.2 Early recording meters: Sangamo Gutmann type A (c. 1899-1901) watt-hourmeter, left, and Westinghouse ampere-hour meter by Shallenberger (c. 1888-1897), right
(Source: David Dahle, www.watthourmeter.com, 2002)
Figure 3.3 Modern recording meters: Schlumberger J5S (1984), and General Electric I-70S (1968) (Source: David Dahle, www.watthourmeter.com, 2002)
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3.2 METHODS OF ELECTRICITY THEFT
There are two main categories for methods of electricity theft: directly connecting
an unregistered load to a power line, and tampering with a registered loads meter in
order to reduce the size of the bill the utility charges that load. Once the meter seals are
broken, there are many things that can be done to the meter to slow or stop it. Below is a
list of various methods of electricity theft recorded by the Provincial Energy Authority of
Thailand (PEA) [6], [7].
High Voltage Meters (12kV or 24kV, 3-phase, 3 or 4-wire primary)
High voltage three-phase watt-hour meters are installed throughout the PEA
system to monitor loads that consume high volumes of energy requiring high voltage.
Three-phase watt-hour meters use the technique known as the two watt-hour meters
connection to measure consumption. Because the load is connected with high voltage and
consumes high current levels, the current and voltage sensing are achieved by using
current transformers (CT)6 and voltage taps, respectively. The schematic that illustrates
the connections is shown in Figure 3.4 below.
6 A current transformer is a device that outputs a current proportional to the load current being measured,enabling the meter to measure the load without subjecting it to large current and power levels.
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Figure 3.4 Three-phase Watt-hour Meter Connection.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)
Tampering with terminal seals is by far the most common method of meter
violations, because the terminal seals are easy to reach, located immediately below the
meter itself. Once the terminals were broken, it is be simple to connect one of the control
wires or CT wires to ground, making it appear to the meter that at lease one phase does
not show voltage or current. The cases of seal tampering, both terminal and meter seals,
refer to cases where seals were broken but no visible tampering was done to the meters or
the terminals themselves.
Breaking control wires Control wires refer to the secondary wires of the current
transformer (CT). Meters for large loads measure high currents and must use CTs to step
the current level down to make it compatible with the components in the meter. Once the
CurrentTransformers(CT)
Voltage Taps
IncomingConnection
3-phaseLoad
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insulation of the control wire is broken, external taps could be connected to reduce the
current going into the meter, causing the meter to read less current than reality.
Tampering with meter seals is another common form of violation, tampering with
meter seals means the person now has access to the meter itself. There are many ways to
tamper with meters that will be discussed later.
Shorting control wires Like breaking control wires, this would divert the current
reading in the meter. In this case the current going to the meter would be zero. The effect
on the meter is immediate and obvious: with zero-current, the power and energy readings
become zero, or the accumulated consumption becomes stationary.
Breaking the voltage taps Voltage taps in the meter housing allows the meter to
read the voltage of the load. Once these are broken (or shorted to ground, or have another
line connected to it), the reading the meter gets is distorted from reality, reading a lower
voltage in cases of electricity theft. In the unlikely event that the person wants the meter
to read higher values, the voltage taps could be connected to a higher voltage level, and
result in higher consumption readings. Many meters would not work properly or would
be damaged by this type of action, because the internal equipment must operate within
rated conditions in order to function properly.
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Direct connections to the grid An obvious way to eliminate consumption records
is to bypass the meter altogether. The major obstacle to this is that most high voltage
loads are built and connected at the request of the customers, such as a new shopping
mall asking for 12-kV lines to run to the back of the property to keep the front clear.
Since the customers are the ones who ask for the connections, direct connections like this
would be fairly easy to discover. Also, not many electricians would like to subject
themselves to a hot high voltage line without the power company there to assist with
safety.
Tampering with the meter Once the meter seals are broken and theres easy access
to the meter inside the housing, and there are several things that can be done to slow or
stop the meter readings. A common way is to mechanically obstruct the spinning disc and
the axis that does the recording. Another popular action is to turn back the dials that bill
collectors eventually read. Obviously this wouldnt work for digital-display meters, but
all of the PEA-installed meters in Thailand are spinning disc type manufactured in the
1980s or before.
Switching CT wires This is a subtle and effective way to reduce electric bills.
Many models of three-phase meters use only two current transformers (CTs) to read
current data from phases A and B, and assume the load is balanced between all three
phases. In reality, large facilities like factories or offices have unbalanced loads.
Depending on the engineer who designed the load connections, this imbalance could vary
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between 10 and 20 percent of the most heavily loaded phase. C phase is almost always
the phase with the least load and lowest power factor, which is why CTs are connected to
the A and B phases. By switching the CTs or the wires from their secondary windings,
the meters current reading is altered. Switching A and B phases would result in a
reversal of phase difference seen by the meter, affecting the power factor reading, and
power/energy reading. If the CT from one of the phases is removed and placed on phase
C, the power reading is lowered.
Low Voltage Meters (220V single phase)
A low voltage watt-hour meter is based on the principles of operation discussed in
the beginning of the chapter. The parts of the meter where tampering often occur are
shown in Figure 3.5 below.
Figure 3.5 Parts of a Single-phase Watt-hour Meter Where Tampering Often Occur.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)
CurrentSensingElement
VoltageSensingElement
DisruptingSpinning Disc
Tamperingwith theNeutral Line
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Direct connection to the power grid Since the meters and equipment in this
section are in the 220-volt system, where customers are mostly houses and small
businesses, a direct connection to the power grid is much easier than the high-voltage
system. Well, at least safer; a pair of rubber gloves could be all the necessary protection
and a ladder and knife all the necessary tools, as opposed to climbing up HV lines five
stories up on steel masts and being careful not to get tangled in other cables below or
inadvertent electrocution. This is by far the most common method here, used a lot by
street vendors and shantytowns. In fact, some of this writers temporary neighbors on a
construction site in Bangkok, Thailand do this.
Using alternate neutral lines The single-phase system often has only one wire
going into a house, the hot line. Neutral is usually grounded (electrically connected to
the earth) and is sometimes provided by the foundation of the house (or location, to be
more generic). So if a person could manage to use a small transformer and use that as the
neutral, the meter that uses the very same neutral source would read the incoming
voltage lower than it really is, resulting in a reduced unit count.
Phase-to-phase connection is similar to using an alternate neutral line, except that
the system voltage becomes the phase-to-phase voltage, at 240 or 380 volts, depending
on the location (240 volts for the United States).
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Meter tampering/breaking seal is basically the same thing that happens to the HV
meters, since PEA uses meters that are quite aged for the low-voltage consumers, too.
Other methods of electricity theft include: tapping off a nearby paying consumer,
damage done to meter enclosures, and using magnets to slow down the spinning discs in
the meter housing.
There are also many other methods for stealing electricity that have been
circulated on the Internet recently. Some of the suggested methods are not feasible, while
others may require too much effort or are outright dangerous [7]. This author has found
some Internet message boards full of possible methods to distort billing information at
the consumer end, such as using a Tron Box a circuit to change the phase of one of
the leads passing through the meter [7].
Methods suggested in chat rooms even include some highly far flung ideas, such
as placing enormous coils around high voltage power lines to act as transformers with
ridiculously large air gaps [4]. Interestingly, these message boards were also used by
some utilities to detect electricity theft perpetrators and track them to see if any of the
individuals fall within their areas of coverage, in effect, operating an online sting
operation7.
7 International Utilities Revenue Protection Association (IURPA), www.iurpa.org, 2002.
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CHAPTER 4
PAST DOCUMENTATION OF NON-TECHNICAL LOSSES
Cases of non-technical losses (NTL) are acknowledged and dealt with by all of
the local utilities officials and international institutions contacted for this research. These
include: Thailands Provincial Energy Authority and Metropolitan Energy Authority
(PEA and MEA, respectively); USAs American Electric Power (AEP); and the World
Bank.
Utility companies with transmission and distribution (T&D) operations that were
contacted by the author were all engaged in some form of NTL reduction policy. PEA has
a set of guidelines to prevent and respond to electricity theft that will be discussed in
further detail. AEP has a Revenue Protection department dedicated to recovering lost
revenues due to electricity theft. The World Bank is involved in infrastructure
development in many countries, which bring them in direct contact with utilities and NTL
in local service areas. A summary of the World Banks experience with NTL in Eastern
European and former Soviet Union countries in the 1990s will be provided. Finally, an
international organization, IURPA [7], focused on detecting, preventing, and reducing
NTL has been established with representatives from utilities around the world.
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4.1 PROVINCIAL ENERGY AUTHORITY OF THAILAND
The Provincial Energy Authority of Thailand (PEA) is the government-owned
utility company that provides electricity to consumers in every area of Thailand except
for Bangkok and its suburbs, which are serviced by the Metropolitan Energy Authority
(MEA). Virtually all of PEAs electricity is bought wholesale from the Energy
Generation Authority of Thailand (EGAT), another government-controlled entity. A very
small amount of electricity is sold to PEA and other consumers by local generators
located in a few industrial complexes; their effects on the PEA power system is negligible
because these local generators distribute power over very short power lines that seldom
extend beyond the industrial parks that they occupy [5], [6].
Since the companies that handle virtually all the electricity generation and
distribution in the country are government-owned, the electricity industry can be easily
described as fully regulated. Electricity rates for various regions are determined by a
board of appointed directors for each of the distribution utilities (MEA and PEA). Their
prices, in turn, are almost exclusively influenced by the supply rates governed by EGAT.
With Thailand being a net importer of crude oil the fuel of choice for starting most
generators, as well as the primary fuel for some generation the prices of crude oil often
plays a big part in EGATs pricing policies. In contrast, the coal and natural gas mines
are operated by other government entities, and hydroelectric dams are controlled by
EGAT.
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The various energy sources constitute the majority of factors that govern the price
of electricity, and all of the entities controlling the sources have political and economic
considerations unique to their own organizations. For example, the hydroelectric facilities
are constantly negotiating deals with the Department of Agriculture, which operate the
reservoirs, while refineries owned by other government and private entities can alter oil
and natural gas prices based on their own agendas and situations.
The PEA determines its prices at board-of-directors meetings, where the prices of
PEAs suppliers are the chief concern. The prices are also partly based on reports from
the Power Economics Division, the primary source of information for this research. And
the Power Economics Division is also the collection center for all the statistical
information regarding consumer billing and payments to suppliers.
In the period from October 1999 to September 2000, PEA had a total of
11,399,150 individual paying consumers, sold 53,034 Gigawatt-hours of energy, and
earned 120,811 million baht (about US$ 2,730 million, by todays exchange rates)
[5],[6]. The price of electricity averaged around 5.15 cents per Kilowatt-hour, nearly the
same per-unit price as American Electric Powers residential prices in Athens, Ohio, in
January 20028.
8 AEP prices can be found on monthly statements to consumers, or at www.aep.com.
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The various types of consumers serviced by PEA include businesses of various
sizes, houses, temporary loads such as construction, agricultural irrigation loads that
include special releases of water from the dams, governmental and subsidized loads and
back-up energy sales to clients of other providers in cases of outages. A detailed
breakdown of number of consumers and consumption levels is shown in Figures 4.1 and
4.2 on the next page. It is worth noting that, in October 2000, businesses and industries
constituted about 7 per cent of the individual consumers, but consumed nearly three-
quarters of the energy sold by PEA.
SERVICE REGIONS AND SECTORS
PEA services include transmission and distribution [5] to all provinces and areas
in Thailand not including the area covered by the Metropolitan Energy Authority (MEA),
which is the province of Bangkok. This means PEA covers most of Thailands areas,
serving a total of 11,479,555 individual metered customers, including residential areas,
businesses, government installations, irrigation facilities, and temporary and back-up
loads. Figures 4.1 and 4.2 below illustrate the breakdowns of PEA customers sorted by
consumption shares and customer types, respectively.
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Homes, over 150
Kwh.
12%
Small Businesses
8%
Medium Businesses
19%
Large Businesses
42%
Homes, under 150
KWh.
11%
Agricultural
Irrigations
under 1%
Temporary Loads
1%Backup Energy Sales
under 1%Government and
Subsidized
4%
Special Businesses
3%
Figure 4.1 - Breakdown of PEA Consumers Sorted by Energy Consumption,
October 2000 (source: PEA,Internal Quarterly Report, 2000)
Homes, under 150
KWh.
73%
Medium Businesses
under 1%
Large Businesses
under 1 %
Government andSubsidized
under 1%Temporary Loads
under 1%
Agricultural Irrigations
under 1%
Backup Energy Sales
under 1%Special Businesses
under 1%
Small Businesses
5%
Homes, over 150 Kwh.
20%
Figure 4.2 - Breakdown of PEA Consumers Sorted by Numbers of Individual Consumers,
October 2000 (source: PEA,Internal Quarterly Report, 2000)
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PROVINCIAL ENERGY AUTHORITY OF THAILAND:
PROCEDURES REGARDING ELECTRICITY THEFT
The Provincial Energy Authority of Thailand (PEA) is the state enterprise that is
responsible for providing electric utility services for end users of all sizes in provincial
Thailand. The area of service includes 72 provinces of Thailand, excluding Bangkok and
a few suburbs. Its customers include: low-voltage loads such as housing, small and
medium businesses, and small industrial sites; high-voltage loads such as large
businesses, office complexes, large industrial sites, industrial parks, large housing
communities, and government installations.
According to internal reports [5],[6], discovered incidents of meter violation a
key indicator of NTL remains relatively low. Between October 2000 and June 2001, a
total of 130 violations were found on high-voltage meters, and 2167 cases were found on
low-voltage meters. This number is very small compared to 11,399,150 total registered
users. Of course, this is a misleading presentation; registered users would not include
people who tap directly to the grid without meters. Some cases of violations may have
gone unnoticed, because inspection methods may not be sufficiently effective.
The PEA has a set of targets and schedules for inspecting meters. An inspection
team for high-voltage meters was observed for this research twice in July 2001; the team
includes inspectors from the central offices in Bangkok and drivers and local officials of
the PEA who are familiar with local sites and consumers. The local officials usually are
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selected from the group of people who conduct inspections for transformers installed for
customers, which are invariably located near the meters that are the targets of inspection.
METER INSPECTION PROTOCOLS
PEA has set guidelines and policies for dealing with electricity theft, as shown in
Table 4.1 below. Table 4.2 below shows the inspection schedules for the group
responsible for inspecting high-voltage (HV: 115 KV, 69 KV, 24 KV, and 12 KV) and
low-voltage (LV: loads with 380 V line-to-line) meters. The number of 220 V meters is
too great to make a dedicated inspection effort, so the inspection workload for those
meters goes to the unit-readers who are also trained to detect improprieties (see Chapter
3). Table 4.3 shows the regular schedule for reporting and deadlines for analyzing the
data on electricity theft collected in the field.
Table 4.1 - PEA Policies for Billing Customers Who Perpetrated Electricity Theft(Source: PEA internal memorandum, June 2001)
Billing Services Target Timeframes
1.) Billing for fines, revised rates, andmeter depreciation for large consumers
1.) Within 7 office days of receiving results
from the Evidence Department, the finesare sent out. Revised rates and depreciationbills are sent out within 15 office days.
2.) Billing for fines, revised rates, andmeter depreciation for small consumers
2.) The revised rates and fines are both sentout within 7 days of the reports of damagedmeters.3.) If the fines and bills in items 1 & 2 donot elicit any response from the consumerwithin 3 months, the case is summarizedand sent on to the legal department of therespective district office.
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Table 4.2 - Meter Inspection Protocols and Schedules for PEA (Source: PEA internalmemorandum, June 2001)
Item Goal/Schedule
1.) Regular Inspections1.1) 69 KV and 115 KV meters1.2) HV and LV meters with CTs1.3) LV meters
1.1)All meters inspected twice a year1.2)All meters inspected once a year1.3)Each year, at least 50% of all
meters in each district will beinspected
2.) Inspections of large customers with
violation records and customers inhigh risk businesses such as icefactories, hotels, etc.
2.) PEAs task forces will compile a list
and inspect all meters in these groups oncea quarter.
3.) Inspections for large customers thatare recently installed/changed
3.) All cases will be inspected within 30days of the installation/change
4.) Large customers with irregularities
4.1) Checking and isolating cases withirregular consumption or irregularbehaviors for future meter checks
4.2) Checking for irregularconsumption
4.1) The comptroller reviews consumptionand separate the irregularities within 15days of meter readings
4.2) Consumers with irregularities and
usage over one million baht($25,000) a month will be checkedimmediately
Low voltage meters are to bechecked within 15 days of therequest for checks
High voltage meters are to bechecked within 30 days
5.) Checking small consumers with 0unit readings
5.) A list of consumers with 3consecutive months of 0 unitreadings is compiled each trimester
Within the following trimester, themeters will be checked and thereasons for the 0 unit reading wouldbe reported
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Table 4.3 - PEA Guidelines and Schedules for Reporting Meter Inspection Results
(Source: PEA, internal memorandum, June 2001)
Operations and Results Report Due Dates
1. PEA operations:1.1Reports for routine meter checks1.2Reports for meters with past violations
and suspicious business groups1.3Major consumers with recent meter
installation/changes1.4Results from checking large
consumers with irregularities1.5Results from checking meters with
zero unit reading1.6Results from fine and revised rates
collections for large and smallconsumers
1. Reports of results in items 1.1 through1.6 are to be submitted to the districtoffices for each month within the 7 th ofthe following month.
2. Results reports for each district,
combined with reports from item 1.
2. Every meter-checking activity resultsand results from fines/revised rates for
each month are to be summarized andreported to the deputy head of eachdistrict. The deputy heads of districtsthen follow up and make necessarychanges in operations, then a report issubmitted for each month to theElectricity Economy Department by the15th of the following month.
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ECONOMIC CONSEQUENCES OF NON-TECHNICAL LOSSES FOR
THE PROVINCIAL ENERGY AUTHORITY OF THAILAND
According to PEA estimates [6], the 127 high-voltage meter violations found
between October 2000 and June 2001 resulted in the recovery of 4,904,021.45 units lost,
or about $245,000. The low-voltage meter violations in the same time period added up to
about $155,000 in lost revenues. These numbers reflect only the cost of producing the
stolen energy without taking into account the cost of equipment damage and payments
for the staff charged with detecting these thefts. These numbers also do not reflect energy
lost due to undetected theft. Details of electricity theft are shown in Tables 4.4 and 4.5
below.
Table 4.4 - Meter Tampering Found Among High Voltage Consumers in Thailand
Between October 2000 and June 2001.(Source: PEA, internal memorandum, June 2001)
High Voltage Consumers (Oct. 00 Jun 01)
Violation Type Cases Found
Tampering with terminal seals 69
Breaking control wires 12
Tampering with meter seals 30
Shorting control wires 5
Breaking the voltage taps 5Direct connections to grid 3
Tampering with the meter 2
Switching control wires 3
Total 127
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Table 4.5 - Meter Tampering Found Among Low Voltage Consumers in ThailandBetween October 2000 and June 2001.
(Source: PEA, internal memorandum, June 2001)
Low Voltage Consumers (Oct. 00 Jun. 01)
Violation Type Cases Found
Direct connections to grid 677
Using alternative neutral lines 541
Phase-to-phase connections 270
Meter tampering/ breaking meter seals 270Other 409
Total 2,167
The total amount of estimated recovered loss due to electricity theft in the period
between October 2000 and June 2001, about 8 million units [6], is very small compared
to the total losses of the system. The total losses of the PEA system is characterized by
subtracting the energy generated and purchased (system input) with the energy sold and
provided to some consumers without charge (system output), and the total losses amounts
to about 2.5 billion units, approximately 5.69 per cents of the system input. This means
the electricity theft found only accounts for about 0.32 per cent of the system losses, or
about 0.018 per cent of the systems energy input.
Though the NTL energy costs recovered seem to make up an insignificant
proportion of the system or even the total system losses, interviews with members of the
PEA inspection team observed for this research revealed that there are undoubtedly some
undiscovered cases of electricity theft. The undiscovered cases may be more or less than
the recovered costs. Also, the recovered costs only include the stolen energy. Other
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related costs that were not mentioned were maintenance costs, equipment damages, labor
costs, and the administrative costs for pursuing electricity theft cases.
4.2 AMERICAN ELECTRIC POWER (AEP)
AEP is a utility company that services a large area in the USA, covering nearly
200,000 square miles spanning eleven states. AEP is the largest investor owned utility in
the United States9. At AEP, the Revenue Protection department is directly responsible for
personnel training, receiving information on electricity theft from customers and staff,
analyze consumer load profiles for drastic changes compared to past trends, assessing
charges for electricity theft and equipment tampering, and if necessary prosecute
clients who endanger themselves or AEP field staff.
The main source of information AEP uses to detect and prevent electricity theft is
the meter reading staff, which is routinely trained by the Revenue Protection Department
to detect tampering with AEP equipment. According to Mr. Bill Daniel, manager of the
Revenue Protection program, AEP had revenue protection-related billings exceeding $
3.2 million annually. In the 2001 annual report available on the AEP website, AEP sold
over $41 billion worth of electricity and bought over $37 billion in the year ending
December 31, 2001. Interestingly, the same report lists $109 million under allowance
for uncollectible accounts.
9 American Electric Power, www.aep.com, 2002.
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The charges that constitute these billings include lost energy, tampering fees,
investigation fees, and interest. Customers are prosecuted under the following
circumstances:
1) the customer threatens (implied or actual) an AEP employee
2) repeat offenders
3) professionals who tamper with anothers meter for a fee
4) if law enforcement is already involved
5) the customer accesses any high voltage compartments or equipment (2.4 kV
or above)
6) the customer climbs or accesses a pole with the intent to steal electricity.
It should be noted again that the main sources of information regarding electricity
are field employees and trend analysis of customer load profiles. In his correspondence
with the author, Mr. Daniel stated that, regarding using power system analysis software
for detecting electricity theft, AEP has a large number of unmetered (flat rate)
installations that would render the resulting calculations unusable.10
In addition to AEP, a search for the phrase electricity theft on any search engine
on the Internet would yield information sites posted by utilities companies all over the
world.
10 Quoted from an electronic mail correspondence with Mr. Daniel from AEP, May 2002.
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4.3 WORLD BANK EASTERN EUROPE AND FORMER SOVIET UNION
The World Bank provides financial assistance to public utilities in many
developing countries, including countries in the former Soviet Union (FSU) and Eastern
Europe. The World Bank studied NTL in these areas in an effort to increase the
efficiency and profitability for local utilities. The results of the World Banks studies are
the sources of the summary below.
In a 1999 publication [2], the World Bank Energy Sector Unit reported on non-
payment in the electrical sector in various countries in Eastern Europe and the FSU
nations. The study covered various time spans for different countries ranging from 1992
to 1998. The main stated reason for the significant in some places very large amount
of non-payment, is the political and economic turmoil caused by the collapse of
communism and the response of the governments and the public to those changes.
The extent of the non-payment problem varies from country to country, and the
cause of the problem also varies. For example, countries with large natural energy
resources such as Russia and Ukraine continue to have problems collecting from
consumers, while countries that are dependent on energy imports have greater incentives
to solve the problem of non-payment. Household consumers are the main area of concern
in Albania, Georgia, and Armenia, while industrial consumers are the bigger problem in
Russia and Ukraine. An interesting type of non-payment is the use of cash substitutes that
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cant be converted to liquid assets by the utilities, which is a problem seen in Russia,
Ukraine, Georgia, and Armenia. The dimensions of the non-payment problem in these
countries are illustrated in Table 4.6 below.
IMPACTS
Large-scale non-payment by consumers has led to enormous consequences both at
the micro and macroeconomic level [2]. Payment default at the consumer end resulted in
transmission and distribution companies defaulting on their dues to the generating
companies, which in turn accumulate unpaid debts to energy suppliers, banks, and
employees. In some cases, the inability to pay for energy has led to rationing, such as
Georgia, which had only a few hours of electricity supply each day in 1995 [2], or
Armenia, which had supply for only two hours a day because its gas utility could not
settle debt with Turkmenistan suppliers.
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Table 4.6 - Extent of the Electric Utility Non-Payment Problem in Eastern Europe andFormer Soviet Union Nations (Source: World Bank Energy Sector Unit, Non-Payment in
the Electricity Sector in Eastern Europe and the Former Soviet Union, 1999)
Country Year Collection as %of billings
Cash as% of collections
Albania 1997 58 97Armenia 1992 1995
19961997
306562
256064
Bulgaria 19921997
7591
100100
Georgia 19961997 (Grid Co. Level)1997 (Distribution Co. Level)
577068
--3736
Hungary 19921997
8596
100100
Poland 1994 90 100Lithuania 1993
19978796
100100
Russia 19961998
7084
1617.6
Ukraine 199419961997
838691
--2018
In Russia, the utilities owe the government significant sums in taxes, while it is
estimated that the government owed even more for energy supplies. This situation created
a vicious cycle that resulted in Russian utilities being unable to pay for fuel supplies and
maintenance. Many large consumers also bartered or provided other cash substitutes for
electricity, forcing the utilities to do the same for fuel, resulting in inflated fuel prices
paid by utilities. This coupled with a drop in demand, ultimately led to a steep drop in
electricity generation utilization, the ratio of actual generation to total generation
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capacity, in Russia as well as other FSU nations with similar problems, shown in Table
4.7 below.
Table 4.7 - Capacity Utilization in the Power Sector of FSU(Source: World Bank Energy Sector Unit, Non-Payment in the Electricity Sector in
Eastern Europe and the Former Soviet Union, 1999)
Country Capacity (GW) Utilization %, 1990 Utilization %, 1994
Russia 205.6 60.1 46.9Ukraine 16.9 62.8 42.8
Lithuania 5.1 59.0