A fast method for identifying bad data of massive power network data
Shunjiang Wang, Anlong Su, Chaonan Ji, Weichun Ge, Yujue Xia, Chunsheng Yan · 2017
In this paper, we propose a new fast and bad data detection and identification technology and model as the research goal, to achieve fast and accurate and efficient data detection and identification. This paper analyzes the influence of single, multiple and multi-correlation bad data on the state estimation results in the actual power grid. Based on the characteristics of its influence and the research status of the bad data detection and identification methods at home and abroad, according to the characteristics of the bad data distribution, The object of the power grid rapid partition method, and further proposed two-layer fine bad data detection and identification model and rapid solution method.