1. Electric / Gas / Water Eric Fox Oleg Moskatov Itron, Inc. April 17, 2008 VELCO Long-Term Demand Forecast Methodology Overview

2. Knowledge to Shape Your Future Page 2 Overview Methodology –SAE energy model –Hourly Load and Peak Demand Model Assumptions –Weather data Normal weather –Economic drivers –End-use saturation and efficiency trends –Price Preliminary Results –Recent peak and energy trends –Hourly load build-up results –Peak and energy forecast

3. Knowledge to Shape Your Future Page 3 Forecasting Approaches Three general approaches are used for forecasting long- term peak demand: –Load factor model Load factor = Average Demand / Peak Demand Peak Forecast = Energy Forecast / Hours * Load Factor –Generalized econometric model Peak Forecast = ƒ(peak-day weather, customers, economic activity) –Build-up approach Combine class energy forecasts with hourly profiles Aggregate to system load Find system peak Load factors and econometric models are adequate for short-term forecasting, but can’t capture the impact of changing load diversity on long-term peak demand.

4. Knowledge to Shape Your Future Page 4 Build-up Forecast Approach Develop long-term energy forecasts by customer class –Residential, Commercial, Industrial, and Other Combine class energy forecasts with class hourly load profile models –Evaluate using end-use hourly load and energy estimates Aggregate class profiles to generate a long-term system forecast and extract the monthly system peak demand Calibrate to weather-normalized 2008 demand estimates

5. Knowledge to Shape Your Future Page 5 System Peak and Energy

6. Knowledge to Shape Your Future Page 6 Summer Peak

7. Knowledge to Shape Your Future Page 7 System Peak Demand Analysis Daily Peak Demand (MW) 2002 to 2007 Significantly less temperature- sensitive load than compared with other regions Significantly less temperature- sensitive load than compared with other regions

8. Knowledge to Shape Your Future Page 8 Winter and Summer Monthly Peaks (MW) But not surprisingly, peaks are driven by heating and cooling demand But not surprisingly, peaks are driven by heating and cooling demand

9. Knowledge to Shape Your Future Page 9 System Peak Demand (Weekdays vs. Weekends) Summer peak demand always falls during the week capturing both commercial and residential cooling loads Summer peak demand always falls during the week capturing both commercial and residential cooling loads Winter peaks also tend to fall during the week-days, but winter week-end peaks can be nearly as high on cold days Winter peaks also tend to fall during the week-days, but winter week-end peaks can be nearly as high on cold days

10. Knowledge to Shape Your Future Page 10 Monthly peak demand (MW) Since 2002, peak demand has been increasing roughly 1.0% per year Since 2002, peak demand has been increasing roughly 1.0% per year Summer peak: 10 MW per year Winter peak: 6 MW per year Summer peak: 10 MW per year Winter peak: 6 MW per year

11. Knowledge to Shape Your Future Page 11 System Monthly Load Factor Load Factor Moving Average Trend The load factor appears to be trending down slightly implying peak demand is growing slightly faster than energy The load factor appears to be trending down slightly implying peak demand is growing slightly faster than energy

12. Knowledge to Shape Your Future Page 12 Peak-Day System Hourly Load Profile (MW) System Commercial Residential Industrial Small differences in customer class load growth can have a significant impact on the peak and its timing Small differences in customer class load growth can have a significant impact on the peak and its timing

13. Knowledge to Shape Your Future Page 13 Peak-Day Residential Load Profile (MW) Residential Cooling Base Use Changes in end-use sales growth in turn impact customer class hourly load Changes in end-use sales growth in turn impact customer class hourly load

14. Knowledge to Shape Your Future Page 14 Build-Up Model Hourly And Peak Forecast Monthly/Annual Energy Forecast Monthly/Annual Energy Forecast Class or End Use Profiles Class or End Use Profiles Hourly System Forecast Hourly System Forecast Long-Run Load Shape Forecasting System Combine energy forecast and hourly class profiles using MetrixLT Need class and end-use energy and profile forecasts

15. Knowledge to Shape Your Future Page 15 Long-Term Energy Forecasting Model that can account for economic changes as well as long term structural changes –Economic impacts – income, household size, household growth –Price impacts –Structural changes – saturation, efficiency, floor space, and thermal integrity trends –Weather impacts –Appropriate interaction of these variables Approaches –End-Use Modeling Framework – REEPS and COMMEND –Statistically Adjusted End-Use Model – Econometric model specification

16. Knowledge to Shape Your Future Page 16 SAE Modeling Approach Blend end-use concepts into an econometric modeling framework: –Average Use = Heating + Cooling + Other Use Define components in terms of its end use structure: –Cooling = f (Saturation, Efficiency, Utilization) Utilization = g (Weather, Price, Income, Household Size) Leverage off of EIA census region end-use forecasts –Adjust for known differences in service area saturations

17. Knowledge to Shape Your Future Page 17 Residential & Commercial SAE Model Regions

18. Knowledge to Shape Your Future Page 18 Statistically Adjusted End-use Modeling (cont.) Estimate model using Ordinary Least Squares:

19. Knowledge to Shape Your Future Page 19 Residential Cooling End Use

20. Knowledge to Shape Your Future Page 20 Residential Cooling Saturation Trends

21. Knowledge to Shape Your Future Page 21 Residential Cooling Efficiency Trends Efficiency for cooling equipment is given for the total US Seasonal Energy Efficiency Ratio (SEER) is defined as a ratio of the total cooling of a central unitary air conditioner or a unitary heat pump in Btu during its normal annual usage period for cooling and the total electric energy input in watt-hours during the same period

22. Knowledge to Shape Your Future Page 22 Residential Cooling Index (Annual kWh)

23. Knowledge to Shape Your Future Page 23 Residential XCool Variable Monthly cooling requirements (kWh) Average cooling use increases with increasing air conditioning saturation

24. Knowledge to Shape Your Future Page 24 Residential XHeat Variable Monthly heating requirement (kWh) Average heating use declines with declining heating saturation

25. Knowledge to Shape Your Future Page 25 Residential Non HVAC End-uses

26. Knowledge to Shape Your Future Page 26 Residential Non HVAC End-uses (cont.)

27. Knowledge to Shape Your Future Page 27 Residential XOther Variable Monthly base use requirement (kWh)

28. Knowledge to Shape Your Future Page 28 Impact of 2007 Energy Act - Lighting 2007 Energy Independence and Security Act introduces a number of new appliance efficiency standards New lighting standards have the most significant impact on residential load –Lighting accounts for approximately 20% of residential “other” use New England Lighting UEC (2007-2008) New England XOther New lighting standards Sharp drop in electric sales results Results in a sharp drop in base use Current lighting standards

29. Knowledge to Shape Your Future Page 29 New England Residential Forecast Comparison (GWh) Due to the high lighting replacement rate, residential electric sales drop off quickly once the new standards go in place. Residential energy use is 2.5% lower by 2013

30. Knowledge to Shape Your Future Page 30 Estimated SAE Model – Residential Average Use

31. Knowledge to Shape Your Future Page 31 Predicted Vs. Actual Average Use

32. Knowledge to Shape Your Future Page 32 Residential Sales Forecast by End-Use (GWh) Base Use Heating Cooling

33. Knowledge to Shape Your Future Page 33 Residential End-Uses (EIA) Heating – electric resistance, heat pump Cooling – CAC, room air conditioning, heat pump Other Use –Water heating –Cooking –Refrigeration –Second refrigerator –Freezer –Dishwasher –Clothes washer –Dryer –Microwave –Color TV –Lighting –Miscellaneous

34. Knowledge to Shape Your Future Page 34 Commercial End-Uses (EIA) Heating Cooling Other Use –Ventilation –Water heating –Cooking –Refrigeration –Lighting –Miscellaneous

35. Knowledge to Shape Your Future Page 35 Vermont Monthly Sales Forecast Models Customer Classes –Residential –Commercial –Industrial –Other Monthly residential and commercial class models are estimated using an SAE specification The industrial sales model estimated using a generalized econometric model We assume historical DSM activity is embedded in the sales data and thus in the estimated models

36. Knowledge to Shape Your Future Page 36 Data Sources Monthly Sales, Customer and Revenue Data –Energy Information Agency January 1999 to November 2007 Depending on system loss factor, sales data account for 95% to 97% of delivered system energy Weather Data –Historical daily maximum and minimum temperatures Burlington Airport, 1970 to current –Evaluated other weather stations, however, there were too many holes in the data series Burlington-based HDD and CDD explain state-level sales well. Price Data –Price series was calculated from reported revenues, sales, and Vermont CPI Price calculated as a 12-month moving average of the prior twelve-month average rate (real basis) Assume constant real price in the forecast

37. Knowledge to Shape Your Future Page 37 Data Sources Economic Data –Fall 2007 Vermont economic forecast by Economy.com Population, number of households, real personal income Gross State Product, manufacturing output, non-manufacturing and manufacturing employment –Final forecast will be based on Economy.com’s current state economic forecast End-Use Saturation and Efficiency Trends –Developed from the 2007 EIA Energy Outlook Forecast for New England –Currently updating efficiency projections to reflect the recently passed energy bill –End-use saturation trends will be calibrated against recent state and Burlington Electric residential saturation surveys

38. Knowledge to Shape Your Future Page 38 Long-Term Vermont Economic Projections

39. Knowledge to Shape Your Future Page 39 Long-Term US Economic Projections

40. Knowledge to Shape Your Future Page 40 Preliminary Class Energy Forecasts (MWh) Commercial 1.1% Commercial 1.1% Residential 1.1% Residential 1.1% Industrial 0.2% Industrial 0.2% Other No Growth Other No Growth

41. Knowledge to Shape Your Future Page 41 Preliminary Class Energy (MWh)

42. Knowledge to Shape Your Future Page 42 Class Hourly Profile Data Sources Load Data –Burlington Electric Load Research Data Residential Small General Service Large General Service –Other Load Research Data Industrial Street Lighting Daily maximum and minimum temperatures –Burlington Airport Daily calendar –Day of the week, month, holiday, hours of sunlight

43. Knowledge to Shape Your Future Page 43 Class Hourly Profile Models Class Hourly Model Structures –Twenty-four hourly regression models HDD and CDD Month, Day of the Week, Holidays Hours of Light Estimation Period –January 1, 2004 to December 31, 2006

44. Knowledge to Shape Your Future Page 44 Calculation of Daily Normal Weather Ten years daily average temperature for Burlington –1998-2007 Rank and Average approach –Daily average temperatures ranked from highest to lowest and within each year then averaged across all 10 years Map daily normal ranked weather data to a typical daily weather pattern –Typical year weather pattern calculated from historical daily weather data –Map the ranked temperature data to the typical year weather pattern Used MetrixLT for calculating daily normal temperature series

45. Knowledge to Shape Your Future Page 45 Chaotic Daily Normal Weather Series Daily normal weather series mapped to the average ten- year weather pattern

46. Knowledge to Shape Your Future Page 46 Residential Load Model (kW per customer)

47. Knowledge to Shape Your Future Page 47 Large General Service Load Model

48. Knowledge to Shape Your Future Page 48 Residential End-Use Profiles Cooling, heating, and other use profiles estimated from end-use weather response models –Data is based on building simulation runs Models simulated for 2004 to 2007 using Burlington actual weather End-use profiles scaled to residential profile model

49. Knowledge to Shape Your Future Page 49 Residential Cooling Profile

50. Knowledge to Shape Your Future Page 50 Residential Heating Profile

51. Knowledge to Shape Your Future Page 51 Load Build-up Comparison System Build-up Uncalibrated Comparison Calibrated Comparison

52. Knowledge to Shape Your Future Page 52 Preliminary Forecast (No Additional DSM) Based on EIA saturation projections

53. Knowledge to Shape Your Future Page 53 Class Coincident Demand

54. Knowledge to Shape Your Future Page 54 Preliminary Energy and Demand Forecast (No Additional DSM) BEC end-use saturation projections (calibrated into state RASS)