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Reliability evaluation method for distribution network with distributed generations considering feeder fault recovery and network reconfiguration.

Authors :
Wang, Haipeng
Lu, Hongchang
Sun, Kai
Wu, Xuewei
He, Yuling
Du, Xiaodong
Source :
IET Renewable Power Generation (Wiley-Blackwell); Oct2023, Vol. 17 Issue 14, p3484-3495, 12p
Publication Year :
2023

Abstract

This paper presents a reliability evaluation method for distribution network with distributed generations considering feeder fault recovery and network reconfiguration, and mainly addresses issues: 1) insufficient consideration of the characteristics for the components and distributed generations (DGs) of distribution network such as time sequences, randomness and intermittency; 2) changes in the feeder area of the distribution network after the access of DGs; and 3) multi‐dimensional reliability index for distribution network with DGs has not been formed perfectly. Firstly, Markov reliability model for distribution network components/DGs is established in our study. Then, considering the fault recovery and network reconfiguration of the feeder area, island partitioning method of distribution network with DGs is also proposed. Moreover, a reliability evaluation model is presented for distribution network with DGs based on sequential Monte Carlo method. Case study is performed on the improved IEEE RBTS BUS6 F4 feeder system, and the research results indicate the validity and effectiveness of the proposed method. In addition, the system reliability indicators, such as system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), customer average interruption duration index (CAIDI), and average system availability index (ASAI), are studied and discussed in detail from three dimensions: the access of DGs, the types of DGs, and the capacity of DGs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17521416
Volume :
17
Issue :
14
Database :
Complementary Index
Journal :
IET Renewable Power Generation (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
173182474
Full Text :
https://doi.org/10.1049/rpg2.12863