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为了保证在配电网中的电压质量和电力系统的稳定性,解决以往遗传算法在计算无功优化时产生的时间过长弊端,本文提出了基于改进的遗传算法并与灵敏度相结合的算法计算配电网的无功优化模型。在灵敏度的基础上对初始种群的确定,提高了初始种群的质量和搜索的目标性,并采用均匀分布将种群覆盖空间扩展至全局最优解内。应用改进的交叉和自适应概率变异使遗传操作得到改善。通过算例对比分析表明,改进后的无功优化算法优越,计算速度得到提升。
In order to ensure the voltage quality and the stability of power system in distribution network and to solve the shortcomings of previous genetic algorithms in calculating reactive power optimization, this paper proposes an algorithm based on improved genetic algorithm combined with sensitivity Reactive power optimization model of distribution network. On the basis of sensitivity, the initial population is determined, the quality of the initial population and the target of the search are improved, and the uniform distribution is used to extend the population coverage to the global optimal solution. Improved genetic manipulation is improved by applying improved crossover and adaptive probability mutation. The comparative analysis shows that the improved reactive power optimization algorithm is superior and the calculation speed is improved.