基于粒子群算法的三相不平衡换相策略研究

Research on Three Phase Imbalance Commutation Strategy Based on Particle Swarm Optimization Algorithm

三相不平衡作为一种无法消除的现象长期存在于低压配网中,严重的不平衡现象会导致线损的急剧增加,甚至影响用电设备的正常运行。针对低压台区的三相不平衡现象,提出一种基于粒子群算法的智能换相策略。根据三相的负荷和电量信息,将换相次数和三相不平衡度作为优化目标,再基于粒子群算法求出最优换相方案。通过电力系统计算机辅助设计(PSCAD)软件仿真和算例分析,结果表明三相不平衡都有较大幅度的下降,验证了此换相策略的可行性。

Three phase imbalance,as an inevitable phenomenon,exists in low-voltage distribution network for a long time.Serious imbalance will lead to a sharp increase in line loss,and even affect the normal operation of electrical equipment.An intelligent commutation strategy based on Particle Swarm Optimization(PSO)algorithm is proposed to solve the problem of three phase imbalance in low-voltage substations.According to the three phase load and electricity information,the commutation times and three-phase imbalance degree are taken as the optimization objectives,and then the optimal commutation scheme is obtained based on the Particle Swarm Optimization Algorithm.Through the power system computer aided design(PSCAD)software simulation and example analysis,the results show that the three phase imbalance has been greatly reduced,which verifies the feasibility of this commutation strategy.