基于基尔霍夫定律,采用遗传算法对不同优化目标下换流参数进行计算.通过MATLAB软件,对不同优化目标及其参数进行仿真分析.研究结果表明:若将"开断性能最佳"作为优化目标,换流回路电感L以及充电电容C最大,鞘层发展时间为95μs,成本消耗为93312 FV2;若将"换流回路成本最低"为优化目标时,鞘层发展时间为98μs,成本消耗为55858 FV2;若将"鞘层间隙发展时间最短"作为优化目标,鞘层发展时间为92μs,成本消耗为116250 FV2.%According to Kirchhoff's law, using genetic algorithm calculate the flow parameters under different optimization objectives. Through the MATLAB software, the simulation and analysis of different optimization objectives and parameters are carried out. The results show that if use the "interruption performance best "as the optimization objective, commutation circuit inductance L and charging capacitor C maximum, the sheath development time was 95 μs, and the cost of consumption was 93312 FV2;if use the"commutation loop cost minimum"as the optimization objective, the sheath development time was 98μs, and the cost of consumption was 55858 FV2;if use the "sheath gap development time shortest" as the optimization objective, the sheath development time was 92 μs,and the cost consumption was 116250 FV2.
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