Copyright © AWWA 2010

Optimizing Operations Holistically for Maximum Savings

Simon BunnCTO - Derceto

Water, Energy and Sustainability

• “The more than 60,000 water systems and 15,000 wastewater systems in the United States are among the country’s largest energy consumers, using about 75 billion kWh/yr nationally —3 percent of annual U.S. electricity consumption.“Electric Power Research Institute, Energy Audit Manual for Water/Wastewater Facilities, (Palo Alto: 1999), Executive Summary

• That’s $10 billion in energy costs per year!

• “Water services are monopolistic by nature (on a local level) and are not naturally driven to increase efficiency and achieve best practices”International Water Association (IWA) 2008

Sustainability for Water Utilities

• Water Systems use large amounts of energy. According to some US based studies*1, on average 80% of the marginal costs is for electricity.

• New treatment process demand higher energy levels, ozonation, UV disinfection, desalination

• Climate change introduces new issues such as droughts, reducing inflows, and flooding disrupting delivery.

• While wastewater utilities have tackled energy management via bio-gas fed generators the water utilities have made more limited steps

1. Ghimire, S. and Barkdoll,B. (2007) “Issues in energy consumption by municipal drinking water distribution systems” World environmental and water resources congress 2007 ASCE

Operations Optimization Goals

• AWWA RF Energy and Water Quality Management System project (EWQMS) starting in 1993 with a functional specification released in 1997 defining:◦ Interface with SCADA System ◦ State Estimator ‘Data Scrubber’ ◦ Water Demand Forecaster◦ Water Quality Module ◦ Energy Cost Calculator ◦ Pump Schedule Optimization◦ System Monitoring & Alarms

• No complete systems delivered as of today

Why Not? The Optimization Problem

• Self modifying behaviour, starting an additional pump at a treatment plant can change pressure everywhere

• Water quality requirements, flow smoothing• Leakage, pressure control• Poor quality of input data (SCADA and demand)• Reliability of outputs, pump failures, telemetry issues• Flexibility to deal with planned and unplanned

outages• Non-linear pump curves, 2 pumps don’t give twice

the flow of one pump

With 11 pumps at ½ hour schedules there are 2^69 possible combinations, more than all the atoms in the entire universe

Need for a holistic optimizer

Able to handle• Water quality issues• Tariffs from Flat Time Of Use spot market• Electricity Demand charges (peak kW or kVa) with ratchet

clauses and real-time market requirements• Treatment plant marginal cost for production, which can

vary due to raw water quality, time of day etc• Alternative pumping path options• Non-linear pump efficiency, plus parallel pump efficiency at

each pump station and globally• Solve all pump stations together, willing to sacrifice cost at

one site if overall benefit is greater system-wide

Water Utility SCADA System

PC on LAN

Application Manager218

PC onLAN

Dashboard210

Current day / real-time

Data Cleaner206

SCADA Interface203

PC onLAN

Operator Panel201

Operations Simulator209

Hydraulic Model208

Primary Database(Live Server)

Historian(B/U Server)

Aquadapt software

What does Aquadapt do?

• Interfaces directly to existing SCADA to both read input values and write pump schedules – fully automatic

• Targets five areas simultaneously:◦ Electrical load movement in time, to maximise utilisation of

low cost tariff blocks◦ Electricity peak demand reduction.◦ Utilisation of lowest production and chemical cost sources of

water.◦ Utilisation of shortest path between source and destination ◦ Energy efficiency improvements from pumps and pumping

plants.• Solves holistically for all costs simultaneously

Case Study 1: East Bay MUD• System installed 2003• Achieved 13% energy cost savings

180 Distribution Reservoirs

3 Aqueducts ( 90 mi/147 km ) 7 Water Supply Reservoirs 6 Water Treatment Plants 25 Rate Control Valves 135 Pumping Plants

3900 Miles of Distribution Pipeline

2 Hydroelectric Plants

220 MGD Average1.3 million Customers

Case Study 1: East Bay MUD

• EBMUD were already avoiding TOU tariffsMedium Size Electric Accounts

-

4,000

8,000

12,000

16,000

20,000

0 4 8 12 16 20 24

Time of the Day

KW

$-

$0.1000

$0.2000

$0.3000

$0.4000

$ / K

Wh

Load Electric Rates

Case Study 1: East Bay MUD

0%

5%

10%

15%

20%

25%

45 - 55% 55 - 65% 65 - 75% 75 - 85%

Aver

age

Efficie

ncy

Impr

ovem

ent (

%)

Original Average Efficiency Range (%)

EBMUD Aquadapt Pump Efficiency Improvements by Original Efficiency, 2003-2008

• So the holistic optimizer targeted efficiency

Pump station efficiency improved universally

Pumps operate more efficiently

Case Study 2: Wellington NZ

• In late 2001 New Zealand was at the end of a major drought that reduced hydro storage levels to critical low points

70% of New Zealand’s power generation was from hydro

Case Study 2: Wellington NZ

• Greater Wellington Water contact Derceto and asked if Aquadapt could be changed to target efficiency instead of lowest energy cost.

• This merely involved changing all tariffs to a single flat tariff and removing demand charges

• Result was an immediate additional 6% reduction in kWh consumption to deliver the same water volume

• Increased energy cost overall by about 2%• The tariff change was reversed after the crisis ended

• The public energy company thanked Greater Wellington Water …but still charged the extra cost

Case Study 3 : Northumbrian (UK)

• Northumbrian Water provide water and sewage services to 4.4 million people in the UK

• 64 water Treatment Works• 362 Pump Stations• 356 Reservoirs• Analyzed savings for this major utility using a closed

loop optimization approach• Analysis showed significant savings but UK energy

rates increasing at 17% per year• New energy provider with higher rates proposed• What would the impact on savings be?

Case Study 3 : Northumbrian (UK)

Case Study 3 : Northumbrian (UK)

Case Study 3 : Northumbrian (UK)

• What if a flat tariff was introduced?

• But what if source shifting (using different total production volumes at each treatment plant) was not possible?

• Almost no drop in savings

• £391,700 or 84.5% as electrical load shifting increased 270% to fill the gap

Savings actually increased (but so does energy cost)

Source shift = £167,500 or 70.2% Load shift = £71,100 or 29.8%

Method Original Analysis New tariffLoad + Source Shifting £167,500 £238,600Demand Reduction £7,200 £7,200Effi ciency Gains £150,000 £195,000Smaller Pump Stations £22,500 £22,500

Total £347,200 £463,300

Derceto AQUADAPT Utility Case Studies – USA

* Factory Tests Complete – Projects being installed now

Aquadapt Client Total Utility Population

Energy Cost

Savings

Approx Annual

Savings

Efficiency Gains

Annual GHG Reduction (metric ton)

WaterOne KS 400 k 14% $ 745 k 6% 4,800

Full System – May 2006

Eastern Municipal Water District CA 700 k 10% $120 k 8% 300

Stage 1 - August 2006

Eastern Municipal Water District CA 15% $190 k 8% 240

Stage 2 – September 2007

East Bay Municipal Utility District CA 1.3 M 12% $360 k 6% 800

Stage 1 – August 2004

Washington Suburban Sanitary Commission MD 1.8 M 11% $865 k 8% 4,500

Full System – May 2006

Regional Municipality of Peel*1 ON 1.2 M 10% C$1.6 M 6% 5,600

Full System – September 2010

Gwinnett County Dept. of Water Resources GA 800 k 8% $460k 6% 2,300

Full System – December 2009

Conclusions

• Operations optimization and especially energy management can lead to substantial savings

• Focusing on just tariff or single pump stations can be counter productive

• A global holistic optimizer takes into account;◦ Water quality◦ Tariff◦ Production costs (chemical and electrical)◦ Constraints

• Savings are not independent, removing one area of potential savings can lead to improvements in other areas with little impact on overall savings

Thank You

Simon Bunnsbunn@derceto.com

Wes Woodwwood@derceto.com