Saqib Ali1,2, Shazia Riaz2,3, Safoora2, Xiangyong Liu1, Guojun Wang1,*
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1783-1800, 2023, DOI:10.32604/cmc.2023.035736
Abstract Short-term load forecasting (STLF) is part and parcel of the efficient working of power grid stations. Accurate forecasts help to detect the fault and enhance grid reliability for organizing sufficient energy transactions. STLF ranges from an hour ahead prediction to a day ahead prediction. Various electric load forecasting methods have been used in literature for electricity generation planning to meet future load demand. A perfect balance regarding generation and utilization is still lacking to avoid extra generation and misusage of electric load. Therefore, this paper utilizes Levenberg–Marquardt (LM) based Artificial Neural Network (ANN) technique to forecast the short-term electricity load… More >
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