Power Grid Structure Performance Evaluation Based on Complex Network Cascade Failure Analysis

Di Zhang, Limin Jia (), Jin Ning, Yujiang Ye, Hao Sun and Ruifeng Shi
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Di Zhang: State Key Laboratory of Rail Transit Control and Safety, Beijing Jiaotong University, Beijing 102206, China
Limin Jia: State Key Laboratory of Rail Transit Control and Safety, Beijing Jiaotong University, Beijing 102206, China
Jin Ning: School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Yujiang Ye: School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Hao Sun: School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Ruifeng Shi: China Institute of Energy and Transportation Integration Development, Beijing 102206, China

Energies, 2023, vol. 16, issue 2, 1-15

Abstract: A safe and stable operation power system is very important for the maintenance of national industrial security and social economy. However, with the increasing complexity of the power grid topology and its operation, new challenges in estimating and evaluating the grid structure performance have received significant attention. Complex network theory transfers the power grid to a network with nodes and links, which helps evaluate the system conveniently with a global view. In this paper, we employ the complex network method to address the cascade failure process and grid structure performance assessment simultaneously. Firstly, a grid cascade failure model based on network topology and power system characteristics is constructed. Then, a set of performance evaluation indicators, including invulnerability, reliability, and vulnerability, is proposed based on the actual functional properties of the grid by renewing the power-weighted degree, medium, and clustering coefficients according to the network cascade failure. Finally, a comprehensive network performance evaluation index, which combines the invulnerability, reliability, and vulnerability indicators with an entropy-based objective weighting method, is put forward in this study. In order to confirm the approach’s efficacy, an IEEE-30 bus system is employed for a case study. Numerical results show that the weighted integrated index with a functional network could better evaluate the power grid performance than the unweighted index with a topology network, which demonstrates and validates the effectiveness of the method proposed in this paper.

Keywords: complex networks; grid structure performance; evaluation methodology; cascade failure; weak point identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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