1. October 8, 2013 Eric Fox and Mike Russo

2. AGENDA »Recent Sales and Customer Trends »Preliminary State Sales and Demand Forecast »Building a No DSM Forecast »End-Use Saturation Projections Integrating the New Appliance Saturation Survey »Estimating Solar Load Impacts

3. VELCO SYSTEM ENERGY 2003 TO 2013 While sales have been flat over the last ten years There have been two distinct periods – before and after the recession * 2013 – 7 mo actual /5 mo forecast

4. VELCO SYSTEM PEAK DEMAND *WNLF_Peak = WN Energy / WN Peak Load Factor System peak shows a similar pattern Positive growth in 2013

5. PEAK-DAY TEMPERATURES 2013 was the hottest peak day in 11 years. Second hottest day based on a 3-day weighted THI

6. GMP YEAR TO DATE SALES January through August Beginning to see some sales and customer growth with improving economy

7. Sales & Customers Weather Conditions Economic Drivers Electric Prices Structural Changes Customer Class and End-Use Energy Forecast System Hourly Load Peak-Day Weather System Energy and Peak Forecast System Profile System Hourly Load Forecast Solar Load and EVs Demand Response DSM SYSTEM FORECAST APPROACH Residential and Commercial Sales Forecasted using a SAE Modeling Framework Residential and Commercial Sales Forecasted using a SAE Modeling Framework End-Use CP Factors

8. SAE MODELING FRAMEWORK

9. KEY FORECAST DRIVERS »Economic activity and population growth Moody Analytics Vermont economic forecast »Weather conditions Twenty-year normal HDD and CDD »Price projections »End-Use Intensity Projections Saturation forecast – Vermont appliance saturation surveys Baseline efficiency projections – 2013 AEO »Intensity adjustments for state efficiency programs »Residential and commercial solar net metering system market penetration »Electric vehicles »???

10. PRELIMINARY VERMONT ENERGY AND DEMAND FORECAST »Revenue class sales and customer data through March 2013 »Moody Analytics June 2013 economic forecast for Vermont »2012 end-use intensity projections Reflects the 2012 VEIC efficiency savings projections »No solar load adjustment »No price impacts Used as a basis for developing a No DSM Forecast

11. BASELINE END-USE INTENSITY TRENDS »End-use intensity trends reflect both saturation and average stock efficiency improvements »Current intensity trends reflect KEMA state saturation survey, EIA New England forecasts, and past BED appliance saturation surveys

12. DSM ADJUSTED END-USE INTENSITIES »Develop baseline end-use sales forecast from SAE models »Calculate adjusted end-use sales forecasts for DSM savings projections Residential: assume 75% is embedded in the baseline forecast Commercial: assume 50% is embedded in the baseline forecast »Adjust end-use intensity forecasts to reflect DSM savings adjustments DSM embedded assumptions based on calibration to actual sales

13. DSM ADJUSTED WATER HEATING INTENSITY Baseline Adjusted

14. TOTAL END-USE INTENSITY PROJECTIONS Baseline Adjusted Baseline Adjusted Residential Commercial

15. RESIDENTIAL AVERAGE USE COMPARISON New England Vermont (with DSM)

16. DEVELOPING THE “NO DSM” FORECAST »Adjust end-use intensities upwards – add back in 100% of projected DSM savings Assume no future DSM is embedded in the baseline forecast Residential Commercial No DSM

17. RESIDENTIAL AVERAGE USE No DSM With DSM

18. COMMERCIAL AVERAGE USE No DSM With DSM

19. VERMONT ENERGY REQUIREMENTS No DSM With DSM

20. VERMONT PEAK DEMAND No DSM With DSM By 2023, DSM programs reduce peak demand by 119 MW (10%)

21. UPDATING END-USE SATURATION ESTIMATES »Incorporate new appliance saturation survey information NMR 2012 Residential Home Survey (Reported February 2013) »Also have the KEMA 2005 survey, earlier BED survey, and the EIA estimates for New England »We were hoping to connect the dots between the KEMA and NMR survey Problem: The two survey points are not all that consistent

22. ELECTRIC HEAT KEMA NMR Surveys show consistently lower shares than that implied by the billing data

23. ELECTRIC HEAT CUSTOMER SHARE AND USE There appears to be significant electric heating

24. SECONDARY ELECTRIC HEAT NMR KEMA Could be people with electric heat consider it a back-up source

25. CENTRAL AIR CONDITIONING NMR KEMA 2 out of 3 sources say CAC saturation is higher

26. ROOM AIR CONDITIONING NMR KEMA Reported RAC saturation is about the same but not consistent with the BED saturation growth

27. ELECTRIC WATER HEATING NMR KEMA KEMA and NMR diverge from New England water heating saturation trends

28. SECOND REFRIGERATORS NMR KEMA NMR saturation is more consistent with New England

29. FREEZERS NMR KEMA The two surveys imply an unlikely sharp decline in the number of freezers

30. CLOTHES WASHERS NMR KEMA

31. DRYERS NMR KEMA NMR survey closer to that reported by EIA

32. DISH WASHERS NMR KEMA KEMA survey closer to that reported by EIA

33. PV MARKET PENETRATION »Though still relatively small net metering (particular residential and commercial photovoltaic systems) has been growing quickly Residential Commercial Share of customers with PV systems (GMP solar customer data) Through 2012

34. FACTORS DRIVING NET METERING PENETRATI0N »Federal Investment Incentives – Through 2017 30% of system installed cost »State Investment Incentives Was $0.45 per watt now $0.25 per watt On a 5 kW system incentive drops from $2,250 to $1,250 - But federal absolute dollar credit will offset some of this »High avoided electric rates average residential rate $0.16 per kWh »Generous buy-back rate Credit equal to $0.20 per kWh (retail rate plus $0.04 per kWh)

35. SOLAR LOAD IS HAPPENING WHERE STATE INCENTIVES ARE SIGNIFICANT

36. SHOULD SEE STRONG PV MARKET GROWTH Assumes 10% annual decline in system cost Simple Payback Assumes continuation of federal tax credit

37. RESIDENTIAL SIMPLE PAYBACK MODEL

38. RESIDENTIAL PV MARKET PENETRATION FCST Base Case No Federal Tax Credit No State or Federal Tax Credit

39. RESIDENTIAL AND SOLAR CUSTOMER FORECAST

40. RESIDENTIAL GENERATION AND USE Average kWh per month Generated 6,700 kWh per year Billed Average Use 6,680 kWh per year Own Use 5,200 kWh per year

41. RESIDENTIAL SOLAR LOAD FORECAST Capacity estimated using a 0.17 load factor, assume average system size = 4.5 Mw