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  • 标题:Short-term power load forecasting based on I-GWO-KELM algorithm
  • 本地全文:下载
  • 作者:Xiaoyu Chen ; Xiangli Dong ; Li Shi
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2021
  • 卷号:336
  • 页码:1-5
  • DOI:10.1051/matecconf/202133605021
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:In this paper, I-GWO-KELM algorithm is used for short-term power load forecasting. Normalize the power data and meteorological data of the short-term power load, and use GWO to optimize the regularization coefficient of KELM and the RBF kernel parameters. To apply the model to short-term power load forecasting to obtain simulations for the next 24 hours and 168 hours curve. Experiments show that the improved model I3-GWO-KELM proposed in this paper has the best effect. The improvement of GWO in this paper is effective and feasible. In the application of short-term power load forecasting, the IGWO-KELM model is more accurate than the ELM and KELM models.
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