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针对静止同步串联补偿器(static synchronous series compensator,SSSC)在选址定容方面研究不足的问题,提出了一种灾变变速量子遗传算法用于SSSC的选址定容优化。推导了包含SSSC的电力系统潮流方程,建立了SSSC在电网中的数学模型;通过潮流计算得到系统的有功损耗、电压偏移率和负荷裕度,使用归一化的处理方法将不同量纲的量同时考虑,并赋以权重,得到目标函数;使用所提灾变变速量子遗传算法求取目标函数的最优解。在Matlab下分析了不同权重下最优解的分布情况,为权重的选择提供了依据。同时与另外2种算法进行对比,结果表明提出的算法在寻优结果稳定性、收敛速度和全局寻优能力上有所改善。
In order to solve the problem that the static synchronous series compensator (SSSC) is not enough for the site sizing, a catastrophic variable-speed quantum genetic algorithm is proposed for the site-sizing optimization of SSSC. The power system power flow equation including SSSC is deduced and the mathematical model of SSSC in the power network is established. The power loss, voltage deviation rate and load margin of the system are calculated by power flow calculation. And take the weights into account to obtain the objective function. The optimal solution to the objective function is obtained by using the quasi-variable genetic algorithm. In Matlab, the distribution of the optimal solution under different weights is analyzed, which provides the basis for the choice of weights. At the same time, compared with the other two algorithms, the results show that the proposed algorithm improves the stability, convergence speed and global optimization ability of the optimal solution.