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Evaluation Algorithm of Disaster Response Capability of Intelligent Distribution Network Based on Fuzzy Comprehensive Evaluation.

Authors :
Ouyang, Jianna
Li, Shan
Zhou, Yangjun
Zhang, Yubo
Wu, Rongrong
Source :
Mathematical Problems in Engineering; 10/4/2022, Vol. 2022, p1-10, 10p
Publication Year :
2022

Abstract

Because most of the production and transmission components of the power system are exposed to the natural environment, they are vulnerable to the threat of natural disasters for a long time and the resulting circuit damage is also large. With the improvement of people's living standards and the improvement of electricity demand, more and more attention has been paid to the normal operation of the power system. Improving the disaster resistance ability of the power system is an important prerequisite to ensure the national economy and life. In view of the above problems, in order to solve and improve the power supply recovery ability of the distribution network in the face of various disasters, this paper focuses on the analysis of the disaster response stage of the intelligent distribution network under natural disasters and the comprehensive data and related indicators of the power grid system, so as to establish the evaluation index system of the power grid's predisaster tolerance and postdisaster resilience and, through the introduction of the fuzzy comprehensive evaluation theory, quantifying the disaster response capability of the distribution network. Finally, through the introduction of case analysis, the case results show that the intelligent distribution network disaster response ability evaluation algorithm based on fuzzy comprehensive evaluation constructed in this paper can accurately calculate the disaster response ability of the distribution network and has an important guiding role in the disaster prevention and reduction of the distribution network. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1024123X
Volume :
2022
Database :
Complementary Index
Journal :
Mathematical Problems in Engineering
Publication Type :
Academic Journal
Accession number :
159720623
Full Text :
https://doi.org/10.1155/2022/4722215