Optimization of Impedance-Accelerated Inverse-Time Over-Current Protection Based on Improved Quantum Genetic Algorithm

Xia Zhang (), Xiaohua Wang, Zhedong Li, Jingguang Huang and Yupeng Zhang
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Xia Zhang: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 433002, China
Xiaohua Wang: State Grid Zhejiang Shaoxing Power Supply Company, Shaoxing 312000, China
Zhedong Li: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 433002, China
Jingguang Huang: College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 433002, China
Yupeng Zhang: State Grid Zhejiang Shaoxing Power Supply Company, Shaoxing 312000, China

Energies, 2023, vol. 16, issue 3, 1-19

Abstract: This paper proposes an impedance-accelerated inverse-time over-current protection optimization scheme based on the improved quantum genetic algorithm. First, the speed of remote backup protection is improved by increasing the optimization level of backup protection. Second, to ensure the coordination of protection when the distributed generation is connected to the distribution network, a mathematical model for the optimization of inverse time protection parameters is established. The mathematical model takes the minimum total action time of the optimized main and backup protection as the objective function, and the selectivity and sensitivity requirements of the protection as the constraints. In addition, the genetic algorithm is improved from four aspects: coding method, population initialization, quantum revolving gate, and variational evolution. The theoretical analysis and simulation results show that the proposed scheme can effectively improve the selectivity and operation speed of the protection.

Keywords: inverse-time over-current protection; improved impedance acceleration; speed; parameter optimization; backup protection optimization stages; quantum genetic algorithm (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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