Fuzzy short-term load forecasting models based on load curve-shaped prototype fuzzy clustering

A modeling method is suggested in this paper which permits building fuzzy models for short-term load forecasting (STLF). The model building process is divided in two parts: a) the structure identification based on the fuzzy C-regression method and b) fine tuning which is achieved using a hybrid genetic/least squares algorithm. The method creates daily models that provide a physical insight of the forecast process. The simulation results demonstrate the efficiency of the suggested model.

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