考虑波动趋势和相关性的多风电场模拟出力数据生成方法

Wind Power Time Series Modeling Method for Multiple Wind Farms Considering Fluctuation Tendency and Correlation Characteristics

为构建多风电场出力序列以便为电力系统规划与运行提供依据,在深入分析风电场出力波动特性的基础上,提出了一种考虑多风电场出力波动趋势和相关性的模拟出力序列建模方法。首先,将各风电场出力序列划分为多个顺序连接的风过程,将其定义为局部的波动过程,并定量表达得到反应出力局部极值和变化趋势等特征的拟合参数;然后,在对特性相近月份聚合后,统计拟合参数,并从拟合参数的角度分析各风电场出力的相关性,构建描述互相关性的Copula函数;最后,结合Copula函数序贯抽样多风电场的拟合参数,构建具有显著相关性的模拟趋势序列,并重构为模拟出力序列。提出的方法从波动过程的角度考虑了局部相关特性,避免了以往只关注整体相关性而不能很好模拟局部特性的问题。对中国某省两风电场进行了仿真模拟,在满足局部相关特性的同时,两风电场的历史与模拟序列的互相关性和统计特性基本一致,验证了方法的有效性,为电力系统随机生产模拟、电力系统风电接纳能力评估等奠定了基础。

A new wind power modeling method is proposed for multiple wind farms considering fluctuation tendency and correlation characteristics for planning and operation of power system.These wind power time series are divided into several wind processes,which are defined as local fluctuation processes and are quantitatively expressed.Classifying the months with similar characteristics,the correlations of these fitting parameters are analyzed,and the Copula function is established.Combining with Copula function,the fluctuation parameters are sampled sequentially,hence the constructed similar time series have remarkable correlation characteristics.This method focuses on the local correlation characteristics with fluctuation feature and avoids concerning only the entire correlation.A simulation for some wind farms in China is performed and comparisons of correlation between two wind farms and between historical and simulated time series show that the proposed method is effective and the local correlation is well considered.