新息图状态估计中多相关不良数据辨识

Multiple Interacting Bad Data Identification for Innovation Graph Technique

新息图状态估计处理坏数据较传统状态估计方法有优越性。文中研究了新息图状态估计中多相关不良数据的辨识问题,分析了多相关不良数据条件下新息差向量的表现特征,为新息图法准确排除测量系统中的多相关不良数据提供了理论依据,使得新息图能准确辨识状态估计中与拓扑变化(包括拓扑错误)相关的多相关不良数据,提高了新息图法识别不良数据的能力。IEEE 30节点系统中不同类型的多相关坏数据识别结果表明了算法的有效性。

The innovation graph technique has advantage on dealing with bad data compared with typical state estimation. This paper studies multiple interacting bad data identification in innovation graph technique. The performance feature of the innovation difference vector in the multiple interacting bad data situation and the theoretical principle of innovation graph technique to eliminate the multiple interacting measurement bad data are analyzed, which can identify the multiple interacting bad data correlating with topology errors （including topology changes）, and can enhance the identification capability of the innovation graph technique. The identification results of the variety combinations of multiple interacting bad data demonstrate the effectiveness of the proposed method by using IEEE 30-bus system.