Abstract: Electricity businesses use load forecasting to predict how much power or energy they'll need to keep supply and demand balanced at all times. It is required for the proper operation of the electrical industry. Load forecasting uses previous data from the electrical system to predict future electric load. For the planning and operation of the utility, precise models for forecasting the electric power load are required. Load forecasting can also be used to support an electric utility's future system operations, such as load switching, demand-side management, and identifying and forecasting energy consumption patterns. It can be classed as short-term (a few hours), medium-term (a few weeks to a year), or long-term (a year or more) (over a year). An econometric technique is utilised for medium-and long-term forecasting. For short-term forecasting, techniques such as regression models, time series, neural networks, statistical learning algorithms, and fuzzy logic are utilised.
keywords: Load forecasting, regression models, time series, neural networks, ARIMA model, statistical learning algorithms and fuzzy logic.
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