基于实测PMU数据的风电综合负荷参数辨识

根据配网侧负荷特点,构建含风力发电机的综合负荷数学模型。以实测PMU数据为基础,利用总体测辨法进行模型参数辨识。将负荷节点输入电压和负荷模型参数代入数学模型,通过改进Euler法求解模型的状态方程,得出负荷节点电流,将其与实测电流误差加权最小作为目标函数,采用遗传算法辨识出负荷模型的参数。以华北电网某线路实测PMU数据为依据,辨识出考虑风电综合负荷的模型参数。辨识结果体现了负荷中以双馈异步发电机为主体的特征,与负荷特点相吻合,由此说明了辨识方法的有效性与辨识结果的合理性。

Wind power comprehensive load parameter identification based on PMU data

The comprehensive load model with wind power generation involved is established based on the load model of distribution network. The overall measuring identification method is then used for parameter identification with measured node voltages. Substituting the node voltage into mathematical model of load, the corresponding current can be calculated through solving its state equation with improved Euler method. The weighted error between measured and calculated currents is selected as the objective function, which can be solved with the genetic algorithm to determine the parameters of the load model. Given measured PMU data from north China power grid, parameters of comprehensive load model are identified with the method proposed above considering wind power generation. The identified results reflect that the main part of load are double fed induction generators for wind power generation, which is in good agreement with the characteristic of load and verifies both the validity of identification method and rationality of identification results.