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Load forecasting is a technique used by power or energy-providing companies to predict the power/energy needed to meet the demand and supply equilibrium. The accuracy of forecasting is of great significance for the operational and managerial loading of a utility company.
Most forecasting methods use numerical techniques or AI algorithms such as recession, neural networks and indistinct logic. Load forecasting can be short-term (a few hours), medium-term (a few weeks up to a year) or long-term (over a year). The end-use and econometric approach is used for medium- and long-term forecasting, whereas the similar-day approach, various regression models, time series, neural networks, statistical learning algorithms and fuzzy logic have been devised for short-term forecasting. Depending on the time-series forecasting, the results can be categorized as: