Online prediction and correction control of static voltage stability index based on Broad Learning System

作者：

Highlights：

• Broad Learning System is used to predict the voltage stability index online.

• The voltage stability index forecast model outperforms comparison models.

• The importance of input features is explained by SHAP-XGBoost algorithm.

• Characteristic approximate sensitivity correction voltage stability L-index.

摘要

•Broad Learning System is used to predict the voltage stability index online.•The voltage stability index forecast model outperforms comparison models.•The importance of input features is explained by SHAP-XGBoost algorithm.•Characteristic approximate sensitivity correction voltage stability L-index.

论文关键词：Artificial intelligence,Voltage stability,Broad Learning System,SHAP-XGBoost model,Correction the power system

论文评审过程：Received 4 August 2021, Revised 10 January 2022, Accepted 1 April 2022, Available online 4 April 2022, Version of Record 22 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117184