不平衡配电网中电容器组的单目标概率最优分配

Optimal Distribution of Single Target Probability of Capacitor in Imbalanced Distribution Network

电容器组作为电力系统的枢纽设备,其重要性不言而喻。配电网负荷的不平衡性导致了电容器存在分配问题。模拟退火、禁忌搜索和遗传算法等被用于实现分配问题的最优化,但上述方法均将配电网视为不变系统。然而配电系统其本质是时变系统,具有概率性,这导致最优分配的结果具有的不确定性。基于上述问题,本文提出一种基于微遗传算法的单目标概率方法,其考虑了负荷的随机性,为电容器组的最优分配提供了更合理的估计。最后,在IEEE 34节点非平衡配电网中对该方法进行了测试,实验证明本文提出的算法具有一定的有效性且计算速度明显优于其他寻优算法。

The importance of capacitor bank as a hub device of power system is self-evident.The imbalance of load of the distribution network leads to the distribution problem of capacitor.Simulated annealing,tabu search and genetic algorithm are used to achieve optimization of the distribution,but the above methods treat the distribution network as an invariant system.However,the distribution system is time-varying system in nature and is probabilistic,which leads to the uncertainty of the optimal distribution results.In view of above problem,a kind of single-target probability method based on micro-genetic algorithm considering the randomness of the load is proposed in this paper,which provides more reasonable estimation for the optimal distribution of the capacitor bank.Finally,the method is tested in the IEEE 34-node imbalance distribution network.The experiments prove that the algorithm proposed in this paper has certain effectiveness and the calculation speed is significantly superior to other optimization algorithms.