电力系统保护与控制2026，Vol.54Issue(15)：95-106,12.DOI:10.19783/j.cnki.pspc.251265
基于双层优化迭代模数并联双驱的电力系统负荷建模方法
A power system load modeling method based on dual-layer optimization iteration and parallel model-data dual-driven architecture
摘要
Abstract
To address the issues of insufficient modeling accuracy and weak generalization capability of traditional load modeling methods in emerging power systems,a novel power system load modeling method based on a dual-layer optimization iterative framework and a parallel model-data dual-driven architecture is proposed.By integrating physics-based and data-driven models through collaborative modeling,the limitations of single modeling approaches are overcome.First,the total load current is decomposed into two components based on an initial current decomposition strategy.Then,the load model is equivalently represented as a parallel structure with two branches,which are modeled by a physical model and a data-driven model,respectively.A dual-layer optimization iterative model is further employed to dynamically adjust the distribution of the input current and output power between the two branches,enabling mutual correction and collaborative optimization of the two models to construct a unified load model.Finally,the proposed method is validated using PMU measurement data from a power substation in Yunnan Province,China.The simulation results demonstrate that,compared with traditional methods,the proposed method achieves higher modeling accuracy and stronger generalization capability.关键词
电力系统/负荷建模/模数并联双驱/双层优化迭代/PMU数据Key words
power system/load modeling/parallel model-data dual-driven architecture/dual-layer optimization iteration/PMU data引用本文复制引用
杨楠,张智祥,邢超,周明睎,王灿,李黄强,郭婷,黄悦华..基于双层优化迭代模数并联双驱的电力系统负荷建模方法[J].电力系统保护与控制,2026,54(15):95-106,12.基金项目
This work is supported by the National Natural Science Foundation of China(No.62233006). 国家自然科学基金项目资助(62233006) （No.62233006）
