Jinseok Kim1, Babar Shah2, Ki-Il Kim3,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 283-301, 2021, DOI:10.32604/cmc.2021.016042
Abstract Load forecasting has received crucial research attention to reduce peak load and contribute to the stability of power grid using machine learning or deep learning models. Especially, we need the adequate model to forecast the maximum load duration based on time-of-use, which is the electricity usage fare policy in order to achieve the goals such as peak load reduction in a power grid. However, the existing single machine learning or deep learning forecasting cannot easily avoid overfitting. Moreover, a majority of the ensemble or hybrid models do not achieve optimal results for forecasting the maximum load duration based on time-of-use.… More >
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