风速相关性对最优潮流的影响

Impact of Wind Speed Correlation on Optimal Power Flow

电网内的多个风电场风速往往因为其地理位置的远近而有着不同程度的相关性,采用Nataf逆变换技术即可建立不同风电场之间具有相关性的风速分布样本空间,进而得到具有相关性的风电场出力。在仿真过程中考虑风速的不确定性,将每个风电场出力视为一个负的满足威布尔随机分布的负荷,根据历史数据,用方差—协方差矩阵描述不同风电场相关系数,建立最优潮流模型。最后,在风电接入改进IEEE 30及IEEE 118节点系统中应用蒙特卡洛仿真计算,定量研究随着风电场之间相关性的增强,最优潮流结果各项指标的波动情况。

There are always some different correlations between wind farms in a power grid.This paper uses inverse Nataf transformation to generate correlated wind speed samples to get the correlating wind farms’ generations.Considering the uncertainty of wind speed,the actual production of each wind power plant is considered as a negative Weibull random distribution load and characterized by its historical time series data.The spatial correlations of wind power plants are properly modeled through stationary variance-covariance matrices.Wind farms are included in modified IEEE 30-bus and IEEE 118-bus systems.Monte Carlo simulation is adopted to quantitatively analyze how the indicators of optimal power flow results volatilities as a result of an increasing correlation among wind farms.