Optimization of distribution network reconfiguration based on Markov chain Monte Carlo method. (November 2022)

• Record Type: Journal Article
• Authors: Li, Jiaqiao; Wang, Guobang; Tang, Tiancheng; Fan, Jinjin; Liu, Shengyuan; Lin, Zhenzhi
• Is Part Of: Energy reports. Volume 8(2022)Supplement 10
• Page Start: 679
• Page End: 685
• Publication Date: 2022-11
• Subjects: Markov chain -- Monte Carlo method -- Distribution network reconfiguration; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2022.05.156
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: Peak load shaving and load balancing are of great significance to reduce distribution network loss and improve resource utilization. Given this background, an optimization strategy for distribution network reconfiguration based on Markov chain Monte Carlo method is proposed. In this strategy, a load characteristic curve clustering method considering DBI index is proposed to obtain the typical load curves of each public transformer and special transformer user under low voltage distribution line based on the historical load curves. Then, an optimization model for distribution network reconfiguration based on Markov chain Monte Carlo method is proposed to minimize the average peak–valley difference of the distribution line, and the line connection modification scheme is obtained. Finally, case studies on two 10 kV distribution lines in Zhejiang province are performed for verifying the effectiveness of the proposed model. The results show that the proposed method can improve the line load rate and realize the peak load shaving and valley load filling of line load, which provides a reference for distribution network reconfiguration.