考虑新能源出力相关性的电网电压暂降随机预估

针对含有风电、光伏及电动汽车充电站的新能源电力系统，提出了一种考虑新能源出力相关性的电网电压暂降随机预估方法。首先构建了故障信息随机模型及新能源出力随机模型，采用拉丁超立方采样（Latin hypercube sampling，LHS）得到故障信息样本，利用皮尔森相关分析法确定同一类型新能源出力的相关系数后，采用Nataf变换及LHS法得到含有相关性的新能源随机出力样本；然后通过故障仿真模拟，得到一系列暂降事件，计算各节点电压暂降指标，预估各节点电压暂降情况；最后以IEEE 30节点为例进行了仿真分析，研究相关系数变化下的新能源出力及不同类型新能源的接入对电网电压暂降的影响。

Stochastic Estimation of Voltage Sag Considering Output Correlation of Renewable Energy Sources

For the electric power system with renewable energy sources such as wind power and photovoltaic power, a stochastic estimation method for voltage sag considering output correlation of renewable energy sources is proposed. Firstly, the stochastic models of short circuit fault information and the output stochastic models of renewable energy sources are established. Secondly, the fault information samples are obtained using the Latin hypercube sampling （LHS）. The correlation coefficient of the renewable energy sources output of the same type is determined by the Pearson correlation analysis method, and then the output samples of renewable energy sources are obtained through the Nataf transformation and LHS. Thirdly, through the fault simulation, a series of voltage sag events can be got, the sag indices of each node can be calculated, and sags at each node can be estimated. The IEEE 30-bus system is taken as an example, the influences of the renewable energy sources output under the change of correlation coefficient and different types of renewable energy sources on the voltage sag are studied.