1. Steven Carlson, P.E. CDH Energy Corp. Evansville, WI www.cdhenergy.com ACE06 San Antonio, 2006 Development of a Utility Energy Index

2. Background Support Benchmarking Efforts Water Wastewater Funding Partnership AwwaRF CEC NYSERDA Contractors CDH Energy Stearns & Wheeler Consultants from ORNL – EPA Metric Development

3. Project Goals What? Produce Industry-wide energy performance metrics for: – Water Utilities – Wastewater Utilities Why? Comparison to Peers Comparison to Ideal Identify savings potential Prioritize where to look for improvements How? Mimic EPA Energy Star for Buildings Ratings – Building characteristics – Operating Characteristics

4. Larger Picture: Benchmarking - History Business: Total Quality Management "Benchmarking - a continuous, systematic process for evaluating the products, services, and work processes of organizations that are recognized as representing best practices for the purpose of organizational improvement." Michael J. Spendolini, The Benchmarking Book, 1992 Identify actions to improve performance Identify issues (metrics) Collect Internal data (baseline) Collect External data (comparison framework) Analysis Implement change Monitor Impact

5. Energy Benchmarking Energy Management Tool How am I doing? Relative to previous performance Relative to other plants in the system Relative to national average Relative to a standard (“Best Practices”)

6. Single Parameter Comparisons

7. Define Performance: A Meaningful Metric Rich dataset for comparison Compare to what? Data source? Comparison method? Normalize for unmanaged characteristics Flow Treatment level Individual processes

8. Metrics Devised based on type of available data Often normalized to flow Energy Cost ($/MG) Energy Use (kWh/MG) Source / Site ? Electricity / Gas ? Related to... Water source, Quality, Distribution topography, etc Desire to include multiple factors f (operating conditions, plant loading, process, etc)

9. Information Model Available energy use data? Factors impacting energy use? Exogenous vs Endogenous factors? Volume Source Source type E&G Treatment Quality Volume Processes E&G Electricity & Gas Topography Pressure Distribution Volume E&G Topography Pressure Volume Water Quality Water Source Water Utility

10. Population Literature Review Population size – 4,000 utilities serve pop > 10,000 Source water distinction Treatment levels (definitions, use frequency) Existing energy data – Surface 1,400 kWh/MG (85% pumping) – Ground 1,800 kWh/MG (nearly all pumping) Little information on characterizing distribution – Total main length

11. Population – Treatment

12. Sample / Response Source EPA Safe Drinking Water Information System Criteria Population > 10,000 Representation 85% of national flow 3,611 Water utilities Process Pilot / survey refinement 1,723 three page surveys mailed SDWIS address and contact info incomplete Results 217 responses (13%) Additional NY surveys from State effort

13. Survey 97 parameters queried Water Source Average/design/maximum flow Turbidity Pumping HP / well depth Treatment Objectives Process Methods Clarification, filtration, etc Residuals handling Distribution System Population & area served Main length Pump HP Elevation range Pressure / zones

14. Survey Energy Electricity (kWh, kW, cost) – Source – Treatment – Distribution Natural Gas Other On-site Generation Engine-driven pumps Misc. Floor area of buildings (administration at plant) Operational review of utility bills Extraordinary events General notes

15. Analysis Minimal Filtering Total kWh > 2,000 kWh/year Total kWh < 5,000 kWh/MG Flow, pump HP and main length were reported 137 observations remain Dependent Variable Cost – Operators interest – Easily combines fuel types – Price variation Source Energy – Policy interest – Fuel mix impacts Log Transformation

16. Analysis – Single Parameter Single parameter model ln(Source kBtu) = 15.49 + 0.988 x ln(Flow MGD) R2 = 0.76

17. Multi-Parameter Model Improved from 0.76 Flow (total & purchased) Pumping Horsepower (total, raw, distribution) Main Length

18. Analysis – Critique Model

19. Grading on a Curve Parameters define peer group curve. Enter source energy to find score.

20. 1 - Calculate Source Energy Use

21. 2 – Predict Model Energy Use and Resulting Score Apply utility parameters to model Adjust model to sample mean Determine benchmark score

22. 3 - Calculate Target Energy Use Determine energy use for other scores Apply energy source fraction (site or sample) to restate in site energy units Determine relative change to reach target

23. Additional Data Characteristics Raw / Treatment / Distribution kWh isolation finds more related parameters n = 93 have two or more categories n = 35 have all three categories Raw Flow Raw HP Purchased flow Raw NTU Other energy Pressure filter Distribution Flow Distrib. HP Distrib. main length Treatment Flow Distrib. Main Well depth Raw NTU Raw HP Distrib. Pressure Distrib. Storage Treat Oxidation Treat Recarbonation Treat Aeration Residual Sand Residual Gravity Pressure Filter

24. Energy Use by Category Categories don’t appear different Difficult to consistently segregate Source/Treatment/Distribution?

25. How to Use the Information?

26. Moving Toward Best Practice How is it defined? Target Score / Rating (relative performance) System performance (rules of thumb) – Process level energy data & metrics Energy Model (absolute standard) How is it achieved? Look at system details Design characteristics (changeable?) Operational parameters (changeable?) Management actions (changeable?) Implementation & Feedback

27. Using the Metrics The metric isn’t the destination, Just the mile marker... A hint that potential improvements exists. Still need to figure out where to go Apply expertise Investigate systems Devise changes Assess performance

28. Summary Project Goals Collect Data (surveys) Define Comparison Framework Create Metrics Water / Wastewater Demonstrate Use (case studies) Metric only gives the score Use information in Applying Benchmarking process Investigate why Motivate action Confirm project impact Manage energy use