Xing Deng1, 2, Haijian Shao1, *, Chunlong Hu1, Dengbiao Jiang1, Yingtao Jiang3
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 273-301, 2020, DOI:10.32604/cmes.2020.08768
Abstract Accurate wind power forecasting in wind farm can effectively reduce the
enormous impact on grid operation safety when high permeability intermittent power
supply is connected to the power grid. Aiming to provide reference strategies for relevant
researchers as well as practical applications, this paper attempts to provide the literature
investigation and methods analysis of deep learning, enforcement learning and transfer
learning in wind speed and wind power forecasting modeling. Usually, wind speed and
wind power forecasting around a wind farm requires the calculation of the next moment
of the definite state, which is usually achieved based on the state of… More >
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