220 kV Circuit Breaker Modeling and Its Parameter Determination Based KEMA Arc Model

Zhang, Xun; Dai, Kai; Zhao, Lijin; Fu, Zhengzheng; Zeng, Huarong; Wen, Yumei; Xie, R. X.; Ma, Xinbin; Sima, Wenxia

doi:10.1109/ichve.2018.8642087

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Heuristic algorithms regard arc parameters determination as an optimization process to find the optimal parameters by minimizing arc voltage or conductance error by adjusting the parameters with random initial values. Compared to other methods, heuristic algorithms have advantages of fast speed and wide applicability in determining arc parameters [15] optimized the arc parameters for a 220 kV circuit breaker by PSO [16,17] optimized the parameters of KEMA model for SF6 circuit breaker by Genetic Algorithm (GA). And the performance of different algorithms like GA and PSO are compared in arc parameters determination [18,19].…”

Section: Introductionmentioning

confidence: 99%

Black-box models for liquid nitrogen arc and its parameters optimization by PSO algorithm

et al. 2023

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Sulphur Hexafluoride (SF6) has been widely utilized in the Gas Insulated Switchgear (GIS) due to its great insulation ability. However, SF6 has great greenhouse effect. Liquid nitrogen (LN2) has been considered as a promising substitute for the SF6 gas because of its good insulation, arc quenching and cost effectiveness. To accurately simulate the LN2 switch, it is essential to establish a mathematical model for the LN2 arc. Black-box models have been commonly used in describing the dynamic characteristics of gas arc in circuit breaker simulations. There are many kinds of black-box models for gas arc, yet there is no literature available about the application of black-box models for the LN2 arc. This paper aims to establish the black-box model for the LN2 arc. Based on the experimental data, several kinds of black-box models including the Mayr, Cassie, Schwarz, Habedank and TP KEMA models were established, and their parameters were optimized by the Particle Swarm Optimization (PSO) algorithm. The performance of these black-box models was evaluated by the arc conductance error. The results showed that black-box models can be utilized for LN2 arc simulations, and the TP KEMA model exhibits the best performance with minimal conductance errors throughout the arcing process.

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