基于电压稳定极限曲面法向量的风电接入配电网随机无功优化

Stochastic reactive power optimization based on normal vector of voltage stability limit surface for distribution network with wind power

利用电压稳定极限曲面法向量指标对配电网无功补偿节点进行选址,在此基础上利用遗传算法对配电网进行无功优化。首先对风电机的出力进行建模,然后利用基于拉丁超立方采样的蒙特卡洛方法得到系统的节点电压、风电机无功出力、电压稳定裕度等变量的期望与标准差。IEEE 33节点系统的计算结果表明,所提方法可以改善配电网无功分布,提高电压水平,降低配电网运行的风险。数值分析的结果表明,该方法可以有效选择系统的薄弱节点,使得系统各个节点电压分布更加均匀,同时能够给系统运行留出更多裕量。

The normal vector of voltage stability limit surface is adopted in the site selection of reactive power compensation node for distribution network,based on which,the genetic algorithm is applied in the reactive power optimization. The output of wind power generator is modelled and the Monte Carlo method based on Latin hypercube sampling is adopted to obtain the expectation and standard deviation of variables,such as node voltage,reactive output of wind power generator,voltage stability margin,etc. The calculative results for IEEE 33-bus system show that,the proposed method can be used to improve the reactive power distribution of distribution network,enhance its voltage level,and decrease its operational risk.The results of numerical analysis show that,the proposed method can be used to effectively select the vulnerable node,unify the voltage distribution among nodes,and remain more margins for system operation.