灾变遗传算法在配电系统最优时变重构中应用

Application of catastrophic genetic algorithm to optimal network reconfiguration in distribution system

提出一种灾变遗传算法来求解中压配电网最优时变重构问题,以达到网损最小和负荷平衡的目的.首先采用协调方法将多目标规划问题转化为单目标寻优问题,并给出了协调后的数学模型.求解过程采用灾变遗传算法以提高种群个体的多样性,防止局部收敛.通过对南方某城区配电系统的计算,证实该算法在求解速度和全局收敛能力上较普通遗传算法均有较大幅度的改善.

A dynamic distribution network reconfiguration method based on catastrophic genetic algorithm is presented. The objectives of this method include minimizing the power losses and achieving load balance. First, an interactive compromissary method is introduced to convert the multiple objectives programming problem into single objective optimization problem. Then the mathematical model of reconfiguration is constructed. An improved genetic algorithm (GA) is proposed to solve the optimization problem. In this stage, catastrophic technique is introduced into the genetic algorithm to keep the diversity of population by the operation of catastrophe, which can avoid the premature convergence problem in simple genetic algorithm. A real power distribution system in a city of south China is selected as numerical example to validate the effectiveness of the algorithm. The results show that the proposed algorithm can enhance the search efficiency, and is easier to reach the global convergence.