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- W4319430679 abstract "With the increasingly serious energy and environmental problems, renewable energy has been favored all over the world. In order to ensure the safe and stable operation of the power grid when wind power and photovoltaic are connected to the grid, the power system often takes some technical means and measures to absorb the output from wind power and photovoltaic. This paper mainly studies the smart grid scheduling algorithm based on artificial neural network. In this paper, a BP neural network model based on load prediction is constructed. By integrating the learning network rate, elastic method is adopted to modify and optimize the BP neural network model. The load data obtained from the modified model is used for power grid dispatching. The experimental results show that the BP neural network is far superior to the traditional dispatching model in load prediction and power grid dispatching." @default.
- W4319430679 created "2023-02-09" @default.
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- W4319430679 date "2022-12-02" @default.
- W4319430679 modified "2023-10-01" @default.
- W4319430679 title "Intelligent Grid Scheduling Algorithm based on Artificial Neural Network" @default.
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- W4319430679 doi "https://doi.org/10.1109/icmnwc56175.2022.10031879" @default.
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