考虑柔性负荷无功调节能力的配网日前两阶段无功随机优化调度

Day-ahead two-stage stochastic reactive power scheduling optimization for a distribution network considering the reactive power regulation capability of flexible loads

针对高比例分布式光伏接入配网所引起的电压控制问题,利用柔性负荷的无功调节能力,并考虑光伏和负荷的不确定性,提出了配网日前两阶段无功随机优化调度方法。首先,在第1阶段根据光伏和负荷的预测值,优化反映电容器组动作和柔性负荷无功调度的离散决策变量。其次,在第2阶段考虑光伏和负荷的不确定性,优化光伏的无功出力和柔性负荷的无功调度量。在优化模型中,设置了电压偏差最小化和柔性负荷的无功调度次数最小化两种目标函数,采用ε约束法对多目标优化问题进行求解,并利用熵权优劣解距离(technique for order preference by similarity to ideal solution,TOPSIS)法选择最优折衷解。在修改的IEEE33节点系统进行仿真,结果表明所提方法能有效缓解由高比例分布式光伏并网所引起的电压越限问题。

To solve the voltage control problem caused by the high penetration of photovoltaics(PVs)in distribution networks,a day-ahead two-stage stochastic reactive power scheduling optimization method is proposed.This uses the reactive power regulation capability of flexible loads(FLs)and considers PVs and load uncertainties.In the first stage,the discrete decision variables reflecting operation of capacitor banks and scheduling of FL reactive power are optimized based on the predicted PV generation and load power.In the second stage,the continuous decision variables reflecting PV reactive output and FL scheduled reactive power are optimized considering the uncertainties from PVs and loads.Two objective functions are set in the proposed model.They minimize the voltage deviation and the amount of FL reactive power scheduling simultaneously.Theε-constraint method is adopted to tackle the multi-objective optimization model,and the entropy weight TOPSIS method is used to select the optimal compromise solution.Case studies of the modified IEEE 33-bus system show that the proposed method can effectively alleviate the voltage over-limit problem caused by PV integration.