基于大数据挖掘的电网设备运行风险预警方法

Risk Early Warning Method of Power Grid Equipment Operation Based on Big Data Mining

为减少电网设备运行风险预警偏差,设计基于大数据挖掘的电网设备运行风险预警方法。首先,基于大数据挖掘算法,挖掘电网设备运行风险与预警的隐性关系,根据隐性数据的周期性变化,开展机器学习与监督训练,从而得到风险预警数据的强相关关系;其次,聚合电网设备运行风险数据,建立风险预警网络,评估电网设备运行风险,并通过横向、纵向、专项协调的机制,形成电网设备运行风险的闭环预警;最后,进行实验分析。实验结果表明,该方法的预警效果优于传统方法,具有一定的应用价值。

In order to reduce the early warning deviation of power grid equipment operation risk,the early warning method of power grid equipment operation risk based on big data mining is designed.Firstly,based on the big data mining algorithm,the implicit relationship between the operation risk of power grid equipment and early warning is mined.According to the periodic changes of the implicit data,machine learning and supervision training are carried out to obtain the strong correlation between the risk early warning data.Secondly,aggregate the operational risk data of power grid equipment,establish a risk warning network,evaluate the operational risks of power grid equipment,and form a closed-loop warning system for the operational risks of power grid equipment through horizontal,vertical,and specialized coordination mechanisms.Finally,conduct experimental analysis.The experimental results show that the warning effect of this method is superior to traditional methods and has certain application value.