Identification of Key Components in Power System Based on Improved Multi-Objective Genetic Algorithm

In recent years, extreme weather events have become increasingly frequent worldwide, greatly threatening the normal operation of power grids. The impact of disaster weather on switching equipment in power grids, particularly circuit breakers in overhead lines and utility poles, may trigger cascading...

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Vydáno v:2025 2nd International Symposium on New Energy Technologies and Power Systems (NETPS) s. 633 - 636
Hlavní autoři: Zhang, Ying, Chen, Yunfeng, Zhang, Kefu, Shi, Jin, Jin, Guohua
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 23.05.2025
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Abstract In recent years, extreme weather events have become increasingly frequent worldwide, greatly threatening the normal operation of power grids. The impact of disaster weather on switching equipment in power grids, particularly circuit breakers in overhead lines and utility poles, may trigger cascading failures throughout the entire system, leading to large-scale blackouts. To study the effects of disaster weather on power grid components, it is necessary to quantify the impact of failures in different overhead lines and nodes on the grid through multiple objectives, reflecting the degree of damage caused by disaster weather to the power grid and providing a reliable reference standard for pre-disaster prevention work. This paper proposes an improved multi-objective optimization algorithm based on power flow betweenness index, which takes into account the number of overloaded lines in case of cascading faults, the load loss rate of the grid, and the connectivity loss rate of the grid's functional zones, is proposed specifically for the fast and efficient identification of combinations of critical components that have the most severe impact on the grid when subjected to catastrophic weather. The results show that the methodology achieves an accurate assessment of the critical components of the distribution grid.
AbstractList In recent years, extreme weather events have become increasingly frequent worldwide, greatly threatening the normal operation of power grids. The impact of disaster weather on switching equipment in power grids, particularly circuit breakers in overhead lines and utility poles, may trigger cascading failures throughout the entire system, leading to large-scale blackouts. To study the effects of disaster weather on power grid components, it is necessary to quantify the impact of failures in different overhead lines and nodes on the grid through multiple objectives, reflecting the degree of damage caused by disaster weather to the power grid and providing a reliable reference standard for pre-disaster prevention work. This paper proposes an improved multi-objective optimization algorithm based on power flow betweenness index, which takes into account the number of overloaded lines in case of cascading faults, the load loss rate of the grid, and the connectivity loss rate of the grid's functional zones, is proposed specifically for the fast and efficient identification of combinations of critical components that have the most severe impact on the grid when subjected to catastrophic weather. The results show that the methodology achieves an accurate assessment of the critical components of the distribution grid.
Author Zhang, Kefu
Zhang, Ying
Jin, Guohua
Shi, Jin
Chen, Yunfeng
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  givenname: Ying
  surname: Zhang
  fullname: Zhang, Ying
  email: 19818000914@163.com
  organization: State Grid Shanghai Jinshan Power Company,Shanghai,China
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  givenname: Yunfeng
  surname: Chen
  fullname: Chen, Yunfeng
  organization: State Grid Shanghai Jinshan Power Company,Shanghai,China
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  givenname: Kefu
  surname: Zhang
  fullname: Zhang, Kefu
  organization: State Grid Shanghai Jinshan Power Company,Shanghai,China
– sequence: 4
  givenname: Jin
  surname: Shi
  fullname: Shi, Jin
  organization: State Grid Shanghai Jinshan Power Company,Shanghai,China
– sequence: 5
  givenname: Guohua
  surname: Jin
  fullname: Jin, Guohua
  organization: Shanghai University of Electric Power,Shanghai,China
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Snippet In recent years, extreme weather events have become increasingly frequent worldwide, greatly threatening the normal operation of power grids. The impact of...
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StartPage 633
SubjectTerms cascading failures
disaster weather
Disasters
Genetic algorithms
Heuristic algorithms
Load flow
Meteorology
multi-objective optimization
Optimization
power flow betweenness
power grid
Power grids
Power system faults
Power system protection
Prevention and mitigation
Title Identification of Key Components in Power System Based on Improved Multi-Objective Genetic Algorithm
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