Using Spreadsheet Simulation to Generate a Distribution of Forecasts for Electric Power Demand

Electric utilities commonly use econometric modelling for energy and power forecasting. In order to accommodate the uncertainties contained in the input variables, such forecasts are frequently made in three parts: a base forecast, assumed to be the most likely, and a high and a low forecast, often arbitrarily spaced on either side of the base forecast, giving a band of possible values for the forecast. Usually, a single point value forecast is then utilized rather than a distribution of possible forecast values. This paper describes how commercially available spreadsheet software was utilized to convert an econometric energy forecast into probabilistic demand and energy forecasts that incorporate weather variation, as well as other uncertain inputs.