计及源荷不确定性的新能源电站无功电压控制

Voltage/Var Optimization for Renewable Power Plants Considering Uncertainties of Source and Load

针对新能源电站并网带来的电压波动和网损偏高的问题,本文提出一种计及源荷不确定性的新能源电站无功电压控制策略,该策略将新能源电站和并网变电站作为一个整体进行优化控制,首先建立风电/光伏功率贝塔分布预测模型,同时利用自回归滑动平均方法预测母线电压值和变电站负荷,然后对预测值通过拉丁超立方采样生成离散化的场景,利用K-means聚类算法获取典型场景集,以此建立目标函数为预测区间内网损和电压偏移期望值最小的优化控制模型,并采用二阶锥规划方法求解。最后仿真表明该策略能够合理安排无功出力,维持电压稳定性,降低区域网损。

With increasing renewable energy resources integrated, the problem of voltage fluctuation and network losses is brought in the grid. A novel voltage/var optimization for renewable power plants is proposed in this paper. The uncertainties of wind turbines and PV power stations are taken into account in the proposed strategy, and the renewable power plant and the connected substation are treated as an electric island to be optimized. The beta function is used to fit the probability density distribution of the PV and wind turbine power prediction firstly, and the bus voltage and substation loads are predicted by the ARMA. Then the LHS is used to generate scenarios for the bus volt-age, plant output and substation loads, and the typical scenario sets could be acquired through the K - means cluster. Thus the optimization model is developed for the voltage deviation and the net loss in the predicted window, the model could be solved by second-order cone programming. Finally, the effectiveness and feasibility of the proposed strategy are verified by the results of the case.