摘要
建立以有功网损和节点电压偏差最小为目标的有源配电网无功优化模型,计及分布式电源和负荷功率的不确定性,采用两点估计法(two-point estimate method,TPEM)计算有源配电网随机潮流,并求解优化模型中的目标函数。正态分布交叉(normal distribution crossover,NDX)算子引入到带精英策略的快速非支配排序遗传算法(NSGA2)中,扩大了算法搜索范围、加强了算法全局搜索能力,对有源配电网多目标无功优化模型进行求解。通过IEEE 33节点系统中的算例验证了所提出有源配电网多目标无功优化方法的正确性和有效性。
A reactive power optimization model of the active distribution network aiming at minimization of active power loss and node voltage deviation is established under consideration of the uncertainties of the DG and load power. The two-point estimate method is adopted to calculate probabilistic load flow of the active distribution network and to obtain objective function values of the optimization model. The normal distribution crossover operator is introduced into the NSGA2 algorithm with elitist strategy to extend its search scope and enhance its global search capability. The proposed algorithm is used to solve the multi-objective reactive power optimization model. The examples given in the IEEE 33 node system verify the correctness and effectiveness of the proposed multi-objective reactive power optimization method for the active distribution network.
出处
《电气自动化》
2018年第1期70-73,共4页
Electrical Automation
关键词
分布式电源
两点估计法
有源配电网
多目标无功优化
快速非支配排序遗传算法
distributed generator （DG）
two-point estimate method
active distribution network
multi-objective reactive power optimization
NSGA2
