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

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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Bibliographic Details
Main Authors: Haofeng ZHENG, Guohua YANG, Wenjun KANG, Zhiyuan LIU, Shitao LIU, Hong WU, Honghao ZHANG
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2022-11-01
Series:Zhongguo dianli
Subjects:
load forecasting
ensemble empirical mode decomposition
temporal convolutional network
gated recurrent unit
Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202012107
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