【摘要】 考虑可再生分布式电源(Renewable Distributed Generation,RDG)和负荷的不确定性,建立了以系统有功网损、负荷均衡指标和节点电压偏移指数期望值均为最小的多目标配电网重构模型。采用基于Pareto准则的二进制量子粒子群算法,并对其进行双变异优化改进。对Pareto最优解集进行满意度评估以供决策者选择最佳方案。对简化后的IEEE33节点系统进行仿真测试,结果验证了该方法的有效性和可行性。更多还原

【Abstract】 Considering the renewable distributed generation(RDG)and load uncertainty,the system active power loss,load balance index and node voltage offset index expectation are established as the minimum multi-objective distribution network reconstruction model. The binary quantum particle swarm optimization algorithm based on Pareto criterion is used in reconstruction,and the double mutation optimization is improved. The Pareto optimal solution set is evaluated for satisfaction,and the decision makers can choose the best solution. The simplified IEEE33 bus system is simulated and tested. The results show that the method is effective and feasible.更多还原