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Shelby Energy Cooperative, Inc. 2006 Load Forecast Prepared by: East Kentucky Power Cooperative, Inc. Forecasting and Market Analysis Department July 2006.

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Presentation on theme: "Shelby Energy Cooperative, Inc. 2006 Load Forecast Prepared by: East Kentucky Power Cooperative, Inc. Forecasting and Market Analysis Department July 2006."— Presentation transcript:

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

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3 3 Table of Contents Introduction and Executive Summary 5 Narrative17 Key Assumptions22 Methodology and Results30 –Residential Forecast35 –Small Commercial40 –Large Commercial42 –Other44 –Peak Day Weather Scenarios47 RUS Form 34150 Page Number

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5 5 Introduction Executive Summary Shelby Energy Cooperative, Inc., (Shelby Energy), located in Shelbyville, Kentucky, is an electric distribution cooperative that serves members in ten counties. This load forecast report contains Shelby Energy’s long-range forecast of energy and peak demand. Shelby 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 Shelby Energy for reasonability. Final projections reflect a rigorous analysis of historical data combined with the experience and judgment of the manager and staff of Shelby Energy. Key assumptions are reported beginning on page 22.

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7 7 Executive Summary (continued) The load forecast is prepared biannually as part of the overall planning cycle at EKPC and Shelby Energy. Cooperation helps to ensure that the forecast meets both parties’ needs. Shelby 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 Shelby 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 11 Executive Summary (continued) Overall Results Total sales are projected to grow by 2.2 percent a year for the period 2005-2025, compared to a 3.4 percent growth 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 2.6 and 2.0 percent, respectively. Annual peaks shown in Figure 1-2. Load factor will remain steady at approximately 52% for the forecast period. See Figure 1-3.

12 12 Executive Summary Overall Results (continued)

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

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

15 15 Figure 1-3 Annual System Load Factor

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17 17 Narrative Shelby Energy Cooperative is located in North Central Kentucky between Louisville and Lexington. The cooperative serves major portions of Carroll, Henry, Shelby and Trimble Counties with a few members in six surrounding counties. The headquarters is located in Shelbyville, Kentucky (Shelby County), with an office in Bedford, Kentucky (Trimble County).

18 18 Narrative (continued) Counties Served Shelby Energy provides service to members in 10 counties. Figure 1-4

19 19 Narrative (continued) Three of the principal counties served by Shelby Energy are strictly rural with a high percentage of people relying on agricultural enterprises for income. Agricultural products include tobacco, dairy, corn, beef cattle and swine. Tobacco and beef cattle are the prime sources of farm income. Shelby County has grown significantly in the commercial and industrial classification. Approximately 40 percent of the Cooperative’s energy sales are from large industrial consumers in the Shelby County area. Shelby County is centrally located and has interstate highway and rail ties to major automotive manufacturing facilities in Indiana, Ohio, Tennessee, and Kentucky. Automotive component manufacturers have built plants in industrial parks in the area. Other industries have also chosen the area due to its central location. Attracting small and medium-sized plants with a diversity of product lines has helped develop additional financial stability. Future expansion of these industrial parks will occur primarily in Shelby Energy’s territory as defined by certified territorial agreements established in 1972. The industrial jobs will generate a greater need for residences and consumer services provided by commercial establishments.

20 20 Narrative (continued) A near “natural unemployment rate” in Shelby County continues to challenge further industrial growth. A shortage of skilled laborers is challenging existing industries as they plan expansions. The location of a new technical school/community college near Shelbyville is expected to help alleviate this problem. The lack of available, affordable housing may also stand in the way of attracting the work force needed for existing industries to expand and new industries to continue to locate in the area. The other counties serve as “bedroom” communities to surrounding metropolitan areas. Commercial and industrial growth is expected to be limited in these counties. Henry County, however, is developing an active, if not aggressive commercial and industrial development group that is experiencing some success in attracting commercial and industrial activity to its communities. Access to Interstate highway and rail service are two of Henry County’s key assets. Henry County also has a semi-skilled to non-skilled workforce that has yet to be fully developed and utilized in light and heavy industry.

21 21 Narrative (continued) Shelby Energy Members Demographic Information There is an average of 2.34 people per household. 56% of all homes are headed by someone age 55 or greater. Nearly 36% of homes have farm operations, with beef cattle most prevalent. 30% of all homes served are less than 10 years old.

22 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, 2006-2025”, dated January 2006.

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

24 24 Key Assumptions (continued) Share of Regional Homes Served Figure 1-5

25 25 Key Assumptions (continued) Household Income Members’ Greatest Sources Figure 1-6

26 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 27 Key Assumptions (continued) Saturation Rates Non HVAC Appliances Microwave Oven99% Electric Range95% Dishwasher65% Freezer64% Clothes Dryer97% Personal Computer64%

28 28 Figure 1-7 Key Assumptions (continued) 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 29 Key Assumptions (continued) Weather Weather data is from the Louisville weather station. Normal weather, a 30-year average of historical temperatures, is assumed for the forecast years.

30 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 Shelby Energy as reported on RUS Form 736 and RUS Form 5. A preliminary forecast is prepared during the first quarter depending on when Shelby 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 31 Table 1-3

32 32 Table 1-4

33 33 Table 1-5

34 34 Methodology and Results (continued) The preliminary forecast was presented to Shelby Energy staff, and reviewed by 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 Shelby Energy staff. Input from EKPC and Shelby Energy results in the best possible forecast.

35 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 Shelby 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 Shelby Energy’s energy forecast.

36 36 Table 1-6

37 37 Figure 1-8 Annual Change in Residential Customers

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39 39 Figure 1-9

40 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 41 Table 1-7

42 42 Methodology and Results (continued) Large Commercial Forecast Large commercial customers are those with loads 1 MW or greater. Shelby Energy currently has 8 customers in this class and is projected to increase to 9 customers by 2025. Large commercial results are reported in Table 1-8.

43 43 Table 1-8

44 44 Methodology and Results (continued) Other Forecast Shelby Energy reports an ‘Other’ class which includes street lighting accounts. Results are reported in Table 1-9.

45 45 Table 1-9

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47 47 Methodology and Results (continued) Peak Day Weather Scenarios Extreme temperatures can dramatically influence Shelby Energy’s peak demands. Table 1-10 and Figure 1-10 reports the impact of extreme weather on system demands.

48 48 Table 1-10

49 49 Figure 1-10

50 50 RUS Form 341

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