随着风电在电力系统中占比提高，其一次调频特性对电力系统频率稳定性的影响增大。为了实现风电场一次调频模型的参数辨识，设计了以实际功率响应数据为依据的辨识方法，基于多工况功率响应数据并采用狼群算法对模型参数进行全局最优辨识。应用所设计的参数辨识方法对某双馈风电场进行了参数辨识，模型仿真值与实测值的对比结果表明：采用该方法辨识得到的模型参数能够较好地反映风电场一次调频功率响应实际特性。

Since wind power percentage is becoming high in power system, its characteristics of primary frequency modulation has more and more important influence on frequency stability analysis of power system. Through analyzing model parameter identification of wind farm′s primary frequency modulation, the identification method is designed based on actual power response data under multiple load conditions, and the wolf pack algorithm is developed as calculation method for global optimal solution of parameter identification. Then parameter identification is applied to a doublyfed wind farm by using the proposed method. The comparison between simulation data and actual data shows that the model parameters identified by the method can reflect the actual characteristics of power response of primary frequency modulation better.

TK761

国网湖南省电力有限公司科技项目（5216A520000A）