基于改进DE的含风电机组配电网多目标无功优化

Multi-objective Reactive Power Optimization for Distribution Network with Wind Power Generators Based on Improved Differential Evolution

电网无功优化是保障电网安全、经济、可靠运行的基本手段,普遍方法是应用智能优化算法以确定电网无功设备投切方案,为此引入差分进化算法解决含风电机组的配电网无功优化问题。考虑风电机组出力的随机性,采用基于场景概率方法,建立了全场景下计及有功网损、静态电压稳定指标、无功补偿设备投资成本的多目标无功优化模型。针对基本差分进化算法的不足,结合免疫原理和二次变异思想改进了差分算法,改进后算法在充分利用进化过程中优良信息的同时,又能保持种群多样性。算例分析结果验证了所建模型与改进方法的可行性和有效性。

Reactive power optimization is the basic means to ensure the safety,economic and reliable operation of power grid.The general method is to apply intelligent optimization algorithm to determine the reactive power equipment switching scheme.Therefore,differential evolution algorithm is introduced to study the reactive power optimization of distribution network with wind power generators.In order to consider the randomness of wind power generators,a multi-objective reactive power optimization model that is based on scenario analysis is established in the all scene.This model is composed of active network loss,static voltage stability and investment cost of reactive compensation.Aiming to overcome the drawbacks of traditional differential evolution algorithm,an improved algorithm is proposed,which utilizes the excellent information of the group in evolutionary learning process and simultaneously maintains the population's diversity.The case analysis shows the feasibility and effectiveness of the model and the improved algorithm.