Using enhanced crow search algorithm optimization-extreme learning machine model to forecast short-term wind power

作者：

Highlights：

• The enhanced crow search algorithm outperforms the state-of-the-art variants.

• The proposed algorithm optimizes the parameters of extreme learning machine.

• The proposed wind power forecast model outperforms comparison models.

• Accurate wind power prediction reduces the operating cost of the power system.

摘要

•The enhanced crow search algorithm outperforms the state-of-the-art variants.•The proposed algorithm optimizes the parameters of extreme learning machine.•The proposed wind power forecast model outperforms comparison models.•Accurate wind power prediction reduces the operating cost of the power system.

论文关键词：Extreme learning machine,Forecasting,Short-term wind power,Clean energy,Enhanced crow search algorithm optimization

论文评审过程：Received 3 August 2020, Revised 30 June 2021, Accepted 6 July 2021, Available online 11 July 2021, Version of Record 19 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115579