This paper first summarizes the challenges brought by the high proportion of new energy generation to smart grids and reviews the classification of existing energy storage technologies in the smart grid environment and the practical application functions of energy . . This paper first summarizes the challenges brought by the high proportion of new energy generation to smart grids and reviews the classification of existing energy storage technologies in the smart grid environment and the practical application functions of energy . . Additionally, the demand for electricity from electric vehicles (EVs) is expected to grow by 6%, reaching approximately 2 TWh by 2040 [2]. Based on the Bloomberg New Energy Finance (BNEF) report examining the global power generation mix, fossil fuels dominated the energy supply from 1970 to 2017. . Therefore, this paper proposes a method that combines PSO-GRU (particle swarm Optimization (PSO)-gated recurrent unit (GRU)) and Multihead-Attention to realize smart grid energy storage capacity planning. And scheduling optimization. First, PSO-GRU models and predicts power grid data by searching. . Smart grids are the ultimate goal of power system development. With access to a high proportion of renewable energy, energy storage systems, with their energy transfer capacity, have become a key part of the smart grid construction process. This paper first summarizes the challenges brought by the.
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