Optimal Design Parameters for Hybrid DC Circuit Breakers Using a Multi-Objective Genetic Algorithm

The primary function of hybrid direct current circuit breakers (HCBs) is to quickly interrupt fault currents to protect high-voltage direct current (HVDC) systems. To enhance the reliability and stability of HVDC systems, optimal design of HCBs is required to minimize the peak fault current, interruption time, and recovery time. Therefore, this study develops a multi-objective genetic algorithm (MOGA)-based optimization model to identify the optimal parameters for HCBs. The MOGA model consists of three objective functions that provide trade-offs among reductions in the peak fault current, the interruption time, and the recovery time. The proposed algorithm is verified with a novel HCB topology using inverse current injection techniques. The performance of the HCB topology with the optimal parameters is validated in the MATLAB/Simulink environment. In addition, a comparison study between the optimal design of an HCB using the proposed algorithm and a typical HCB model is presented in this study to show the effectiveness of the proposed optimization method. Our simulation results show that the optimal parameter design of HCBs significantly reduces the magnitude of the peak fault current and operating time, thus maintaining the safe and stable operation of the entire system.

Automated summary

This study develops a multi-objective genetic algorithm-based optimization model to identify the optimal parameters for hybrid direct current circuit breakers (HCBs). The proposed algorithm is verified with a novel HCB topology, and simulation results show that the optimal parameter design significantly reduces the magnitude of the peak fault current and operating time, ensuring the safe and stable operation of the entire system.