Load Forecasting Based on Multiple Load Features and TCN-GRU Neural Network

Traditional load forecasting does not deeply consider the impact of load sequence on model forecasting accuracy. To improve the prediction accuracy, a multi-load feature combination (MLFC) is proposed, and a load prediction framework is constructed by combining Temporal Convolutional Network (TCN) a...

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Detalles Bibliográficos

Autores principales:	Haofeng ZHENG, Guohua YANG, Wenjun KANG, Zhiyuan LIU, Shitao LIU, Hong WU, Honghao ZHANG
Formato:	Artigo
Lenguaje:	Chinês
Publicado:	State Grid Energy Research Institute 2022-11-01
Colección:	Zhongguo dianli
Materias:	load forecasting ensemble empirical mode decomposition temporal convolutional network gated recurrent unit
Acceso en línea:	https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202012107
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