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。(Multiple wind speed within the grid often because of their geographical proximity and have different degrees of relevance, Nataf inverse transform using technology to build wind speed distribution between the sample space with different wind farms correlation, and then get relevant The wind farm output. Consider wind uncertainty in the simulation process, the output of each wind farm to meet the load as a negative Weibull random distribution, based on historical data, variance- covariance matrix of correlation coefficients describing different wind farms, the establishment of optimal fashion models. Finally, to improve access to wind power IEEE 30 and IEEE 118-node system Monte Carlo simulation, quantitative research with enhanced correlation between wind farms, OPF result of fluctuations in the indicators.)

风速相关性对最优潮流的影响_潘雄.pdf,654944,2014-03-03