A distribution network state estimation method based on distribution generation output mode discrimination. (12th August 2021)

• Record Type: Journal Article
• Authors: Jin, Zhaoyang; Cai, Deyu; Wang, Chen; Ding, Lei
• Is Part Of: International transactions on electrical energy systems. Volume 31:Number 11(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-12
• Subjects: distributed generator -- distribution system -- k‐means cluster method -- state estimation; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.13036
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: In recent years, the penetration rate of distributed generation (DG) in the distribution network is increasing, which significantly adds the uncertainty for state estimation. To tackle this problem, in this paper, a state estimation method based on DG output mode discrimination is proposed. The historical output data of DG are analyzed offline by the k‐means clustering algorithm, and the output modes are identified by the pre‐state estimation results before the measurements are updated. The obtained pseudo measurements are used to perform the secondary state estimation based on the model information and the measurements. The proposed method can effectively improve the state estimation of distributed generation buses, which is verified by MATLAB simulations in the PE&G‐69 bus system. Abstract : In this paper, a state estimation method based on DG output mode discrimination is proposed. The historical output data of DG are analyzed offline by the k‐means clustering algorithm, and the output modes are identified by the pre‐state estimation results before the measurements are updated. The obtained pseudo measurements are used to perform the secondary state estimation based on the model information and the measurements. The proposed method can effectively improve the state estimation of distributed generation buses.