PMU小扰动信号下的综合负荷模型参数辨识方法

电力系统日常运行过程中时刻存在类似噪声的小扰动信号,利用小扰动信号开展负荷参数辨识可解决传统总体测辨法无法处理的负荷时变性和分布性难题。基于PMU实测小扰动信号提出一种“Z+IM”综合负荷模型参数辨识方法。该方法采用PMU量测数据滚动识别框架,滚动识别主要包括数据处理和负荷参数辨识两个步骤。首先,针对PMU量测小扰动信号的特点,通过厂站初筛、预处理、可辨识集粗筛和去噪等步骤得到较为优质的PMU小扰动数据集。然后,基于预报误差思想通过两阶段辨识策略辨识负荷时变参数、电磁参数和机电参数。所提方法得到的负荷参数无需折算可直接应用于PSASP、BPA等国内主流仿真程序,具有实际工程应用价值。最后,算例通过3机9节点系统仿真和湖南实际电网验证所提方法的有效性和鲁棒性。

Parameter identification method of composite load model using small disturbance signal of PMU

Small disturbance signals similar to noise always exist in the daily operation of power systems, and their use for load parameter identification can solve a problem of time-varying and distributed loads that cannot be handled by traditional overall measurement and identification methods. This paper proposes a parameter identification method of a "Z+IM" comprehensive load model based on a small perturbation signal measured by PMU. This method adopts the rolling identification framework of PMU measurement data, and divides rolling identification into two steps: data processing and load parameter identification. First, from the characteristics of small disturbance signals measured by PMUs, relatively high quality small disturbance data sets of PMUs are obtained through the steps of initial screening, preprocessing, coarse screening of identifiable sets and denoising. Then, the time-varying, electromagnetic and mechanical parameters of the load are identified by a two-stage identification strategy based on the idea of prediction error. The load parameters obtained by the proposed method can be directly applied to domestic mainstream simulation programs such as PSASP and BPA without conversion. This has practical engineering application value. Finally, the effectiveness and robustness of the proposed method are verified by the simulation of a 3-machine 9-bus system and the actual grid in Hunan province.