Owen Electric Cooperative 2006 Load Forecast

1. Owen Electric Cooperative2006 Load Forecast Prepared by: East Kentucky Power Cooperative, Inc. Forecasting and Market Analysis Department July 2006

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3. Table of Contents Page Number • Introduction and Executive Summary 5 • Narrative 16 • Key Assumptions 22 • Methodology and Results 30 • Residential Forecast 35 • Public Buildings 40 • Small Commercial 42 • Large Commercial 44 • Other Forecast 46 • Peak Day Weather Scenarios 49 • RUS Form 341 52

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5. IntroductionExecutive Summary Owen Electric Cooperative (Owen Electric) located in Owenton, Kentucky, is an electric distribution cooperative that serves members in nine counties. This load forecast report contains Owen Electric’s long-range forecast of energy and peak demand. Owen Electric and its power supplier, East Kentucky Power Cooperative (EKPC), worked jointly to prepare the load forecast. Factors considered in preparing the forecast include the national and local economy, population and housing trends, service area industrial development, electric price, household income, weather, and appliance efficiency changes. EKPC prepared a preliminary load forecast, which was reviewed by Owen Electric for reasonability. Final projections reflect a rigorous analysis of historical data combined with the experience and judgment of the manager and staff of Owen Electric. Key assumptions are reported beginning on page 22.

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7. Executive Summary (continued) The load forecast is prepared biannually as part of the overall planning cycle at EKPC and Owen Electric. Cooperation helps to ensure that the forecast meets both parties’ needs. Owen Electric uses the forecast in developing two-year work plans, long-range work plans, and financial forecasts. EKPC uses the forecast in areas of marketing analysis, transmission planning, generation planning, demand-side planning, and financial forecasting. The complete load forecast for Owen Electric is reported in Table 1-1. Residential and commercial sales, total purchases, winter and summer peak demands, and load factor are presented for the years 1990 through 2025.

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11. Executive Summary (continued)Overall Results • Total sales are projected to grow by 3.0 percent a year for the period 2005-2025, compared to 3.8 percent which was projected in the 2004 load forecast for the period 2004-2024. Results shown in Table 1-2 and Figure 1-1. • Winter and summer peak demands for the same period indicate annual growth of 3.4 and 2.6 percent, respectively. Annual peaks shown in Figure 1-2. • Load factor will remain steady at 51% for the forecast period. See Figure 1-3.

12. Executive SummaryOverall Results (continued)

13. Figure 1-1 Average Annual Growth in Sales 2005-2025

14. Figure 1-2Peak Demand Forecast Winter and Summer

15. Figure 1-3Annual System Load Factor

16. NarrativeTerritory Owen Electric Cooperative headquarters are located in Owenton, Kentucky. Owen Electric serves nearly 54,000 members over approximately 4,900 miles of electric line. Owen serves regions in Boone, Campbell, Carroll, Gallatin, Grant, Kenton, Owen, Pendleton, and Scott Counties.

17. Narrative (continued)Counties Served Owen Electric provides service to members in 9 counties. Figure 1-4

18. Narrative (continued)Local Economy and Customer GrowthResidential A major portion of Owen EC’s residential growth continues to come from the large-scale developments in the northern service area. The local economy continues to remain strong. Much of the growth takes place around the Northern Kentucky/ Greater Cincinnati Airport and the middle of Kenton County south of the Ft. Mitchell area. These areas have had two new substations added in recent years and four substations in the area have been upgraded. Two additional substations are being evaluated in the area. The Alexandria area in Campbell County has continued to expand and with the new Hwy. 27 relocation the growth in the area will remain strong. Several other road projects will open up areas for development and they include the Turkeyfoot Road realignment (Kenton), Hwy 17 (Kenton), Hwy 42 (Boone) and the I-71/Markland Dam Connector (Gallatin).

19. Narrative (continued)Local Economy and Customer GrowthCommercial Commercial connects have remained strong with OEC adding several large loads last several years. Airpark International is a 300 acre site with only two or three lots remaining. There is property available that could be encompassed in this park in the future. IDI Inc. has developed a 125 acre, Parkwest, tract in the Hebron area. Parkwest is a combination of warehouse and light industrial loads. There are no more lots to be developed in this park and the Hebron Substation was constructed to accommodate the loads in the area and in Parkwest. Airpark West and Gateway Industrial Park, located near Bullitsville Substation, have three large loads presently located there with many lots available. Several large loads have been inquiring about lots in these parks.

20. Narrative (continued)Local Economy and Customer GrowthIndustrial Parks Circleport II and Riverview Business Park, located in and around the Smith Substation, have been active with one or two buildings being added every year or so. Smith Substation has been expanded to a dual station to accommodate the load in the area. Circleport has several large lots remaining as does Riverview. Enterprise V in Kenton County and Richwood Industrial Park in Boone have several lots available. Other areas in the nine counties serve large loads and are dispersed throughout the OEC service territory and much of the land along the Ohio River Valley continues to be viable for large industrial/commercial locations.

21. Narrative (continued)Owen Electric MembersDemographic Information • There is an average of 2.63 people per household. • 43% of all homes are headed by someone age 55 or greater. • 15% of homes have farm operations, with beef cattle being most prevalent. • 38% of all homes served are less than 10 years old.

22. Key AssumptionsPower Cost and Rates • EKPC’s wholesale power cost forecast used in this load forecast comes from the following report: “Twenty-Year Financial Forecast, Equity Development Plan, 2006-2025”, dated January 2006.

23. Key Assumptions (continued)Economic EKPC’s source for economic forecasts is DRI-WEFA.

24. Key Assumptions (continued)Share of Regional Homes Served Figure 1-5 Owen Electric’s market share will increase for the forecast period.

25. Key Assumptions (continued)Household IncomeMembers’ Greatest Sources Figure 1-6

26. Key Assumptions (continued)Appliance Saturations • Room air conditioner saturation is declining due to customers choosing central air conditioning systems. • Appliance efficiency trends are accounted for in the model. The data is collected from Energy Information Administration, (EIA). See Figure 1-7.

27. Key Assumptions (continued)Saturation Rates Non HVAC Appliances • Microwave Oven 99% • Electric Range 89% • Dishwasher 73% • Freezer 49% • Clothes Dryer 99% • Personal Computer 74%

28. Key Assumptions (continued) Figure 1-7 All of the projections are very similar to what was used in the 2004 Load Forecast. However, the 2004 Load Forecast assumption was just below 8 by 2024 whereas this update shows the trend continuing above 8. Source: Energy Information Administration (EIA) Efficiency Trend Update, 2005

29. Key Assumptions (continued)Weather • Weather data is from the Covington weather station. • Normal weather, a 30-year average of historical temperatures, is assumed for the forecast years.

30. Methodology and ResultsIntroduction This section briefly describes the methodology used to develop the load forecast and presents results in tabular and graphical form for residential and commercial classifications. Table 1-3 through Table 1-5 shows historical data for Owen Electric as reported on RUS Form 736 and RUS Form 5. A preliminary forecast is prepared during the first quarter depending on when Owen Electric experiences its winter peak. The first step is modeling the regional economy. Population, income, and employment are among the areas analyzed. The regional model results are used in combination with the historical billing information, appliance saturation data, appliance efficiency data, and weather data to develop the long range forecast.

31. Table 1-3

32. Table 1-4

33. Table 1-5

34. Methodology and Results (continued) The preliminary forecast was presented to Owen Electric staff, and reviewed by the Rural Utilities Services (RUS) Field Representative. Changes were made to the forecast as needed based on new information, such as new large loads or subdivisions. In some instances, other assumptions were changed based on insights from Owen Electric staff. Input from EKPC and Owen Electric results in the best possible forecast.

35. Methodology and Results (continued)Residential Forecast Residential customers are analyzed by means of regression analysis with resulting coefficients used to prepare customer projections. Regressions for residential customers are typically a function of regional economic and demographic variables. Two variables that are very significant are the numbers of households by county in each member system's economic region and the percent of total households served by the member system. Table 1-6 and Figure 1-8 report Owen Electric’s customer forecast. The residential energy sales were projected using a statistically adjusted end-use (SAE) approach. This method of modeling incorporates end-use forecasts and can be used to allocate the monthly and annual forecasts into end-use components. This method, like end-use modeling, requires detailed information about appliance saturation, appliance use, appliance efficiencies, household characteristics, weather characteristics, and demographic and economic information. The SAE approach segments the average household use into heating, cooling, and water heating end-use components. See Figure 1-9. This model accounts for appliance efficiency improvements. Table 1-6 reports Owen Electric’s energy forecast.

36. Table 1-6

37. Figure 1-8Annual Change in Residential Customers

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39. Figure 1-9

40. Methodology and Results (continued)Public Building Forecast Public building sales are projected using two equations, a customer equation and an energy equation. Both are determined through regression analysis and utilize inputs relating to the economy, electric price, and the residential customer forecast. Projections are reported in Table 1-7.

41. Table 1-7

42. Methodology and Results (continued)Small Commercial Forecast Small commercial sales are projected using two equations, a customer equation and a small commercial sales equation. Both are determined through regression analysis and utilize inputs relating to the economy, electric price, and the residential customer forecast. Small commercial projections are reported in Table 1-8.

43. Table 1-8

44. Methodology and Results (continued)Large Commercial Forecast Large commercial customers are those with loads 1 MW or greater. Owen Electric currently has 36 customers reported in this class and is projected to increase to 42 customers by 2025. Large commercial results are reported in Table 1-9.

45. Table 1-9

46. Methodology and Results (continued)Other Forecast Owen Electric serves street light accounts which are classified in the ‘Other’ category. This class is modeled separately. Results are reported in Table 1-10.

47. Table 1-10

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49. Methodology and Results (continued)Peak Day Weather Scenarios Extreme temperatures can dramatically influence Owen Electric’s peak demands. Table 1-11 and Figure 1-10 reports the impact of extreme weather on system demands.

50. Table 1-11