Inter-County Energy Cooperative Corporation 2006 Load Forecast Prepared by: East Kentucky Power Cooperative, Inc. Forecasting and Market Analysis Department June 2006

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3 Table of Contents Introduction and Executive Summary 5 Narrative16 Key Assumptions22 Methodology and Results30 –Residential Forecast35 –Small Commercial40 –Large Commercial42 –Peak Day Weather Scenarios44 RUS Form Page Number

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5 Introduction Executive Summary Inter-County Energy Cooperative Corporation (Inter-County Energy), located in Danville, Kentucky, is an electric distribution cooperative that serves members in 12 counties. This load forecast report contains Inter-County Energy’s long- range forecast of energy and peak demand. Inter-County Energy 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 Inter-County Energy for reasonability. Final projections reflect a rigorous analysis of historical data combined with the experience and judgment of the manager and staff of Inter-County Energy. 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 Inter-County Energy. Cooperation helps to ensure that the forecast meets both parties’ needs. Inter-County Energy 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 Inter-County Energy 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 2.6 percent a year for the period , compared to a 3.4 percent growth projected in the 2004 load forecast for the period Results shown in Table 1-2 and Figure 1-1. Winter and summer peak demands for the same period indicate annual growth of 2.9 and 2.4 percent, respectively. Annual peaks shown in Figure 1-2. Load factor will increase slightly to approximately 42% for the forecast period. See Figure 1-3.

12 Executive Summary Overall Results (continued)

13 Figure 1-1 Average Annual Growth in Sales

14 Figure 1-2 Peak Demand Forecast Winter and Summer

15 Figure 1-3 Annual System Load Factor

16 Narrative Inter-County Energy is a Touchstone Energy Cooperative with its headquarters in Danville, Kentucky and a district office in Lebanon, Kentucky. With over 3,500 miles of distribution lines, the cooperative serves nearly 25,000 customers in the rural areas of the following central Kentucky counties: Boyle, Garrard, Lincoln, Casey, Marion, Mercer, Washington, Taylor, Madison, Rockcastle, Larue, and Nelson. Kentucky Utilities Company, an investor owned utility, provides electric service to all of the urban and small towns in the area.

17 Narrative (continued) Counties Served Inter-County Energy provides service to members in 12 counties. Figure 1-4

18 Narrative (continued) In recent years, changes have taken place in the economy of the area. Traditionally, tobacco, dairy and beef cattle farming were the financial backbone of the communities served by the cooperative. Hardwood timber, fruits and vegetables supplemented the agricultural base of the area. More recently, employment opportunities have increased in the urban centers due to recruitment of commercial, industrial, retail, medical and service employers. As a result many of the small farms that previously operated and supported the economy of the area have become part-time operations or have been purchased by adjoining land owners to form larger farms. Most of the counties served by Inter-County Energy have one or more industrial parks. The Danville/Boyle County Industrial Park functions as a regional hub for employment in the area served by Inter-County Energy. The Danville/Boyle County Industrial Foundation has been very successful in attracting light industry as well as Fortune 500 Companies to the park. The majority of existing industry in the Danville/Boyle County Park is served by Kentucky Utilities. However, the park has numerous available properties that will be served by the cooperative when they are developed. The Lebanon/Marion County Industrial Foundation also has been successful in recruiting commercial and industrial customers to Marion County. The largest industrial customers served by Inter-County Energy have facilities in the Lebanon/Marion County Industrial Park. Those industries are: NSU, Morton Plastics, Montebello, TBMK, and Joy Mining.

19 Narrative (continued) There is a new industrial park in Lincoln County. Inter-County Energy, working closely with the Industrial Development Director of Lincoln County, has been very active in recruiting customers to this area. A speculative building is being considered for this park. In addition to the industrial growth, there has been substantial additions to the large commercial class in large part due to Wal-Mart. Stanford ’ s new Super Wal-Mart opened in July of 2005 and two additional Super Centers will be opening their doors by the first quarter of 2007, in Harrodsburg and Lebanon. Makers Mark Distillery is another major commercial customer of Inter-County Energy. Located in Loretta, Kentucky, Makers Mark Distillery has been a customer since Several new highway projects have been completed in the cooperative ’ s service area that should benefit the cooperative. Improvements in Highway 68 from Danville to Lebanon provide a much safer route to the western portion of Inter-County Energy ’ s service area. A new section of Highway 127 from Danville into Casey County has created a good corridor to the south and a new section of Highway 150 east of Stanford offers direct access to a new fishing and recreation lake in the Cedar Creek area of eastern Lincoln County.

20 Narrative (continued) Plans to link the eastern section of the service territory to Interstate 75 near Mt. Vernon are being studied by the state and a new section of Highway 27 from Jessamine County through Garrard County and into Lincoln County has been proposed by the state. An improved highway system will enhance and grow the economy of the area. The customer base of Inter-County Energy is overwhelmingly residential and is likely to remain that way for the foreseeable future. Since kWh usage is so dominated by the residential class, future kWh projections for the cooperative are quite reliable. Inter-County Energy should continue a steady rate of growth in sales and customers. Efforts by the cooperative and local industrial leaders to promote economic development in the area served by the cooperative will result in greater power sales to all classes of customers including the commercial and industrial sectors.

21 Narrative (continued) Inter-County Energy Members Demographic Information There is an average of 2.37 people per household. Approximately 50% of all homes are headed by someone age 55 or greater. 24% of homes have farm operations, with beef cattle being most popular. Nearly 30% of all homes served are less than 10 years old.

22 Key Assumptions Power 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, ”, 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 Inter-County Energy’s market share will steadily increase for the forecast period. See Figure 1-5 below.

25 Key Assumptions (continued) Household Income Members’ 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 Oven94% Electric Range93% Dishwasher54% Freezer58% Clothes Dryer96% Personal Computer54%

28 Key Assumptions (continued) Figure 1-7 Source: Energy Information Administration (EIA) Efficiency Trend Update, 2005

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

30 Methodology and Results Introduction 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 Inter-County Energy as reported on RUS Form 736 and RUS Form 5. A preliminary forecast is prepared during the first quarter depending on when Inter-County Energy 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 Note: Reclassifications in 2004 and 2005

33 Table 1-5

34 Methodology and Results (continued) The preliminary forecast was presented to Inter-County Energy staff. 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 Inter-County Energy staff. The forecast was reviewed by the Rural Utilities Services (RUS) Field Representative. Input from EKPC and Inter-County Energy 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 Inter-County Energy’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 Inter-County Energy’s energy forecast.

36 Table 1-6 Note: Reclassifications in 2004 and 2005

37 Figure 1-8 Annual Change in Residential Customers

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39 Figure 1-9

40 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 1-7.

41 Table 1-7

42 Methodology and Results (continued) Large Commercial Forecast Large commercial customers are those with loads 1 MW or greater. Inter-County Energy currently has 1 customer in this class and is projected to increase to 5 customers by Large commercial results are reported in Table 1-8.

43 Table 1-8

44 Methodology and Results (continued) Peak Day Weather Scenarios Extreme temperatures can dramatically influence Inter-County Energy’s peak demands. Table 1-9 and Figure 1-10 reports the impact of extreme weather on system demands.

45 Table 1-9

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47 Figure 1-10

48 RUS Form 341