A day-ahead industrial load forecasting model using load change rate features and combining FA-ELM and the AdaBoost algorithm

A day-ahead industrial load forecasting model using load change rate features and combining FA-ELM and the AdaBoost algorithm

Industrial customers consume a large part of the total electricity demand. In the operation of industrial energy systems, accurate prediction of electric loads is a prerequisite to help industrial users adjust their electric load dispatch and improve energy efficiency. Therefore, this paper proposes...

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Bibliographic Details
Main Authors: Ziwei Zhu, Mengran Zhou, Feng Hu, Shenghe Wang, Jinhui Ma, Bo Gao, Kai Bian, Wenhao Lai
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Energy Reports
Subjects:
Short-term load forecast
Industrial customers
Spearman correlation coefficient
Extreme learning machine
Ensemble learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484722026440

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http://www.sciencedirect.com/science/article/pii/S2352484722026440

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