基于灰色模型的变电倒闸操作风险预测方法研究  

Grey-model-based Prediction of Switching Operation Risk of Substations

作　　者：代荣家 DAI Rongjia(Beijing Tiecheng Construction Supervision Co.,Ltd.,Beijing 100039,China)

机构地区：[1]北京铁城建设监理有限责任公司,北京100039

出　　处：《电工技术》2024年第2期121-123,共3页Electric Engineering

摘　　要：为了降低变电站倒闸操作导致的事故发生率,需要对倒闸操作风险进行预测。近几年大数据及人工智能发展迅速,将数据挖掘技术与风险预测相结合,搭建倒闸操作风险可视化模型,并提取倒闸过程的风险特征值和故障逻辑的关系,从而得到高精度的预测结果。基于此,提出一种基于灰色模型的倒闸操作风险预测方法,通过对风险趋势进行分解来掌握其变化趋势。该预测方法的推广应用为变电倒闸操作提供了安全保障,有效提高了倒闸风险预测的准确性,具有很好的应用前景和现实的应用价值。Risk prediction of switching operation is of significance to reducing switching-induced accidents in substations.In view of the rapid development of big data and artificial intelligence in recent years,the present work established a visual model of switching operation risk by combining data mining technology with risk prediction.Through extracting the relationship between switching operation risk eigenvalue and fault logic,the model can obtain high-precision prediction results.On this basis a grey model-based risk prediction method for switching operation was proposed,which helps in detecting the variation of risk by decomposing risk trend.The application of this prediction method may help in guaranteeing operation safety of substation switching and improving accuracy of the risk prediction.

关 键 词：灰色模型 倒闸 操作风险 预测方法 

分 类 号：TM63[电气工程—电力系统及自动化]