Clustering method of fuzzy equivalence matrix to bad-data detection and identification
Year: 2011
Type: article
Abstract: Fuzzy mathematics method is used to identify the bad-data in power system real-time data.By use of clustering analysis method based on fuzzy equivalence matrix,and regarding the normalized residual difference and the difference value between adjacent sampling times data as the eigen values,measured items are clustered dynamically by searching the best threshold value.According to individual given good-data and'like attracts like' principle,the good-dataset will be found,and thus the bad-data will be identified.Finally,the traditional instance model and power system real-time data in some place are simulated respectively.The results show that the proposed method not only can identify the bad-data quickly and exactly,but also can avoid residual pollution and residual submersion effectively.It is better to be used in the actual power systems.
Author: Xiangdong Wang
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2359748347