CAJ | 학술논문

本文采用区间值来描述负荷并计算三相潮流。由于粒子群算法存在早熟的问题，采取非线性递减惯性权重的策略，使惯性权重随着迭代次数的增加而减小，同时，采用种群适应度方差判断算法是否陷入早熟，以便对早熟的种群进行自适应变异，动态的变异数目先大后小地控制了变异过程，保证了前期粒子的多样性和后期粒子算法的收敛。改进的粒子群算法保证了粒子在迭代初期有较强的全局搜索能力和后期有较高的搜索精度，保证了算法能够得到全局最优解，并提高了搜索速度。算例表明，基于区间三相潮流的改进粒子群算法能够有效地解决配电网故障恢复的问题，具有一定的工程价值。
본문채용구간치래묘술부하병계산삼상조류。유우입자군산법존재조숙적문제，채취비선성체감관성권중적책략，사관성권중수착질대차수적증가이감소，동시，채용충군괄응도방차판단산법시부함입조숙，이편대조숙적충군진행자괄응변이，동태적변이수목선대후소지공제료변이과정，보증료전기입자적다양성화후기입자산법적수렴。개진적입자군산법보증료입자재질대초기유교강적전국수색능력화후기유교고적수색정도，보증료산법능구득도전국최우해，병제고료수색속도。산례표명，기우구간삼상조류적개진입자군산법능구유효지해결배전망고장회복적문제，구유일정적공정개치。
This paper introduces interval value to describe the load and calculate the three-phase trend. To solve the problem of precocious problem in the particle swarm optimization algorithm ( PSO ), the nonlinear decreasing strategy is applied in selecting PSO?s inertia weight so that the inertia weight can decrease gradually with the increase in the number of iterations. At the same time,it adopts the fitness variance of population to decide if the algorithm is premature inorganic in order to make adaptively mutation for premature population and the dynamic number of variation gradually becomes less. The improved PSO ensures that it has a strong global search capability in iteration initial stage and the higher search accuracy in late stage. The example shows that the improved PSO based on the interval three phase power flow can effectively solve the problem of distribution network service restoration and it has the practical value.