基于粗糙熵加权密度的电网调控系统异常检测

针对调控系统运行过程中出现的异常状态，提出基于粗糙熵加权密度的智能电网调控系统运行异常数据检测方法。采用粗糙集对电网调控系统运行数据进行分析和推理；利用隶属度的割关系方法，将复杂的不确定关系转化为布尔数据并排序；基于对象加权密度对智能电网调控系统运行中出现的异常数据进行检测，实现对调控系统各种功能异常状态数据准确识别。采用真实电网调控系统数据对所提方法进行验证，结果表明：该方法与传统异常状态识别方法相比，具有更高准确率和更低漏判率。

Anomaly Detection of Power Grid Control System Based onWeighted Density of Rough Entropy

Aiming at the abnormal state in the operation process of the control system, a detection method of abnormaldata in the operation of smart grid control system based on rough entropy weighted density is proposed. The rough set isused to analyze and reason the operation data of power grid control system. The complex uncertain relationship istransformed into Boolean data and sorted by using the cut relationship method of membership degree. The abnormal data inthe operation of smart grid control system are detected based on the weighted density of objects, and the abnormal data ofvarious functions of the control system are accurately identified. The proposed method is verified by the real power gridcontrol system data, and the results show that the proposed method has higher accuracy and lower omission rate comparedwith the traditional abnormal state identification method.