基于混沌并行差分进化算法的含风电配电网无功优化

Reactive Power Optimization of Distribution Network with Wind Power Based on Chaotic Parallel Differential Evolution Algorithm

将风电机组接入配电网,其出力的间歇性、随机性使得传统无功优化模型不再适用。为此,采用场景分析法对双馈异步发电机(doubly fed induction generator,DFIG)的出力情况进行探讨,建立了含DFIG的配电网无功优化场景模型。考虑DFIG的灵活无功调节能力,建立以降低系统网损、抑制电压波动为综合目标的模糊无功优化模型。通过蒙特卡罗仿真对配电网系统进行无功补偿选址,采用带反馈的混沌并行差分进化算法(chaotic parallel differential evolution algorithm w ith feedback,CPDEF)求解含DFIG的配电网无功优化问题。通过IEEE 33节点系统对所提出的无功优化模型进行仿真计算,结果表明系统网损得以明显降低,电压水平明显改善,并证明了所提方法的可行性和有效性。

After the wind power generators are connected to the distribution network, traditional reactive power optimization model no longer applies as a result of its intermittent and random output.Therefore,the scenario analysis method was adopted to deal with the output power of the doubly fed induction generator （DFIG）,and the scenario model was established for reactive power optimization of distribution network with DFIG.Considering the flexible reactive power regulation capability of DFIG,a model for fuzzy reactive power optimization was presented with a comprehensive objective function of reducing the network loss and restricting node voltage variations of distribution network.The location of reactive power compensation device for distribution network was determined by Monte Carlo simulation.Chaotic parallel differential evolution algorithm with feedback （CPDEF）was used to solve the reactive power optimization of distribution network with DFIG.Finally,the IEEE 33-bus system was used as a test case to simulate the proposed optimization model of reactive power.Simulation results show that the active power loss of distribution network is reduced significantly,and its voltage profile is improved.It also proves that the proposed method is feasible and effective.