基于双向长短期记忆网络的区域电网新能源消纳预测算法

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Abstract In view of the increasingly serious problem of new energy consumption in regional power grids, and the technical difficulty, low efficiency and long consumption time of using optimization algorithms to evaluate the new energy consumption in regional power grids, this paper proposes a new energy consumption prediction method based on bidirectional long short term memory network (BiLSTM) for regional power grids. Firstly, the factors that affect the new energy consumption of regional power grid are analyzed, and the new energy consumption forecast data is prepared. Then, a new energy consumption prediction algorithm for regional power grids based on BiLSTM is proposed, and the historical power grid operation data training model is used to realize fast and accurate online prediction of new energy consumption in regional power grids. Finally, the validity of the method proposed in this paper is verified by actual power grid data, which provides reference for power grid operators.

Key words： bidirectional long short term memory network (BiLSTM) new energy consumption in regional power grid power system analysis artificial intelligence

Received: 04 January 2023

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	Articles by authors
	HE Anming
	ZHAO Xin
	WU Ligang
	SUN Fei
	WANG Chunyan

Cite this article:

HE Anming,ZHAO Xin,WU Ligang等. Prediction algorithm of new energy consumption in regional power grid based on bidirectional long short term memory network[J]. Electrical Engineering, 2023, 24(3): 23-30.

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http://dqjs.cesmedia.cn/EN/Y2023/V24/I3/23

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