基于配网量测数据的静态负荷模型参数辨识

电力负荷作为电力系统的终端用户,其模型的准确程度直接影响着电力系统运行分析的准确性.近年来,配电网中的量测装置记录了大量稳态数据,能否利用稳态量测数据实现静态负荷模型参数的辨识已成为新的研究问题.提出了基于配网量测数据的静态负荷参数辨识方法.首先,对专变和公变的有功量测数据进行聚类,得到日负荷特性类似的同类负荷曲线;然后,在假设同类负荷的负荷模型参数相似的基础上,建立静态负荷模型参数辨识的数学优化模型,并通过优化算法求解静态负荷模型的日时变参数;最后,通过算例验证了所提方法的可行性和有效性.

arameter identification for static load model based on distribution network measurement data

As the terminal user of power system, the model accuracy of power load has profound influence on the accuracy of power system operation analysis. In recent years, a large amount of steady-state data has been collected by measuring devices in distribution networks. How to realize the parameters identification for static load with these measured data becomes a new research problem. A static load parameters identification method based on distribution network measured data is proposed. Firstly, the measured active power data is clustered to obtain the similar load curves with similar load characteristic. Then, under the assumption that similar load characteristic corresponds to similar load parameters, a model for static load parameters identification is established, and solved by optimization algorithm to get the parameters of daily static load.Lastly, case studies demonstrate the feasibility and effectiveness of the proposed methodt extent.