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• W108113704 abstract "Regression and econometric models are appropriate for forecasting the sales to residential and large customers ... the impact of weather on electric sales increases as the weather gets hotter ... for effective forecasting, forecasting model must be up to date at the time of forecast. Every utility company has a unit consisting of experts who perform the forecasting functions. The importance of forecasting cannot be over emphasized. A utility company requires forecasts of sales for its operating budget, for its financial planning and for its rate case proceedings. It needs peak load forecasts for long-term system planning and short-term purchases of electric power and gas supply. Although the sophistication of forecasting varies somewhat from company to company, the fundamental goals and procedures of forecasting are pretty much the same. The objective of this article is to summarize the common forecasting practices and make a few suggestions on forecasting techniques. FORECAST PROCESS Most major utility companies in the United States have a well-structured forecasting group. The group is responsible for the full range of forecast functions - database compilation, modeling, forecast preparation, and after-the-fact reconciliation. The functions are as follows: FORECAST REQUIREMENTS Sales forecasting is usually done by customer type: residential, commercial, industrial, etc. Peak load forecasting is usually done for the service area and load network areas. For an operating budget, companies require sales forecasts for one to three years ahead. For power purchase and facility dispatch, the companies require daily peak load forecast for a week ahead. For long-term planning, they need annual sales and peak load forecast for up to 20 years. These different types of forecasts require different database and different modeling techniques. Database Compilation Most utility companies have good records of their operations because of the nature of their business: their sales and peak load are metered. However, it is up to the forecasting group to compile and maintain the database suitable for forecast modeling. Sales data come from the accounting department, but the accounting department is not responsible for maintaining the data for a long period of time. Accounting data may contain billing irregularities, which need to be weeded out. Peak load data come from the system operation department, but it sends out raw data only, which are not always suitable for modeling. Forecasting personnel must maintain a database for each type of modeling and forecasting. For example, since the forecast of sales is required by customer type, the database should be maintained that way. If a monthly model is to be developed, the database should be maintained on a monthly basis. If a quarterly model is more appropriate, the data should be aggregated into quarterly data. Sales and peak load data are available internally, but external data may be required too. In econometric or regression modeling, data for independent variables, such as inflation rate, employment data, GDP, and others, must come from outside sources. Again, it is the responsibility of the forecasting personnel to collect and evaluate these outside data. In addition, independent variables must be projected for the forecast horizon. This projection is also an important function of the forecasting personnel. Forecasting Model Different situations require different types of models. In the utility industry, the following model types have been applied in forecasting: 1. Regression And Econometric Models: These types of models are appropriate for forecasting sales to residential and large commercial customers. Key variables driving these types of models include number of customers, electric and gas prices, and employment level. Data for these variables are readily available. 2. ARMAX Models: Regression and econometric models may include ARMA terms to account for the effects of those driving variables, which are not included in the model. …" @default.
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• W108113704 date "2004-04-01" @default.
• W108113704 modified "2023-09-23" @default.
• W108113704 title "Forecasting Practices in Electric and Gas Utility Companies" @default.
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