Evaluating of Short-Term Electrical Load Forecasting System Using Fuzzy Logic Control: A Study Case in Sudan
Abstract
Generation, Transmission and Distribution sections of the electric power grid system are a function of electric load forecasting. This is because, many benefits can be obtained by using load forecasting, such as reduction in the generating cost and increasing the reliability of the power system due to improving energy management. The objective of this study is therefore to design a fuzzy logic system for short-term electric load forecasting to reduce power losses particularly in times where the electric power generation is higher than the electric load demand. In this study, the independent variables that were applied to the developed short-term load forecasting Simulink model were time, temperature, and similar previous electric day load demand, and they were collected from the specific area load control center in Sudan. Fuzzy rules were prepared using Mamdani implication. The obtained fuzzy logic results were compared with the actual load demand, and it was found that there was an error that ranged between 12% and 0.09%.
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