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基于适应性权重遗传算法的多目标无功优化研究 被引量:14

Study on multi-objective reactive power optimization based on genetic algorithm with adaptive weight
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摘要 研究一种多目标无功优化问题的求解方法。基于无功分层分区平衡以及保证紧急情况下电网安全的原则,给出了在电网正常情况下优先投切电容器、调节变压器分接头,然后设定机端电压的优化调控顺序,进一步提出将优化问题分解为连续变量优化和离散变量优化问题,并分别求解,迭代直至收敛的求解思路。鉴于多目标无功优化模型的复杂性,以及连续、离散控制变量并存,采用遗传算法求解,重点研究了控制变量的编码方案以及选择、交叉、变异以及保留操作策略。针对于多目标无功优化各个目标权重难以确定问题,又进一步引入了适应性权重遗传算法,随着遗传代数的进化算法能自适应地给出各个目标权重。仿真算例验证了文中所提的多目标无功优化求解方法的合理性。 The solution for multi-objective reactive power optimization is studied.Based on the principle of hierarchical and regional balance of reactive power and guarantee for power system stability in emergency cases,regulation order is confirmed,that capacitor switching and transformer tap adjusting are first,and generator terminal voltage setting follows.Furthermore,the solving thinking is presented,that optimization problem is decomposed into continuous variable optimization and discrete variable optimization,then they are solved respectively and cross iteration until convergence.In view of the optimization complexity and the coexistence of discrete variables and continuous variables,genetic algorithm is presented for finding global optimal solution.The coding of control variables and strategies for the selection,cross,mutation and retention operation are mainly studied.Aiming at determining each objective weight of multi-objective optimization,the genetic algorithm with adaptive weight is introduced further,with genetic evolution each objective weight is given adaptively by the algorithm.Case studies show that the proposed thinking and algorithm for solving multi-objective reactive power optimization are reasonable.
出处 《电力系统保护与控制》 EI CSCD 北大核心 2010年第6期1-7,25,共8页 Power System Protection and Control
关键词 多目标无功优化 电容器投切 变压器分接头调节 机端电压设定 适应性权重遗传算法 multi-objective reactive power optimization capacitor switching transformer tap adjusting generator terminal voltage setting genetic algorithm with adaptive weight
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