@article{LIN2026, 
author = {Bingying LIN and Lin GUAN and Haoying CHEN and Hancheng GONG},
title = {Two-stage parameter identification of composite load model in large power system dynamic simulation for active distribution system},
year = {2026},
journal = {Electric Power Engineering Technology},
volume = {45},
number = {10},
pages = {1-13},
keywords = {generalized composite load model, two-stage parameter identification, dynamic feature, distributed photovoltaic source, dynamic bipartite genetic algorithm (DBGA), active distribution network, load modeling},
url = {https://www.sciopen.com/article/10.12158/j.2096-3203.2026.10.001},
doi = {10.12158/j.2096-3203.2026.10.001},
abstract = {The development of distributed photovoltaic sources changes the dynamic characteristics of distribution system under the main power grid faults. Security and stability simulation analysis of large power systems require a more accurate equivalent load model to incorporate the influence of the distribution system. Firstly, the electromagnetic transient simulation model including both the transmission and the distribution systems is constructed. Degree of dynamic bias with traditional load model is simulated and analyzed under variation of the photovoltaic sources and induction motor proportions in the distribution networks. Then, the generalized composite load model with photovoltaic is adopted and the trajectory sensitivity method is applied to identify the core parameters of the model. Subsequently, based on the physical meaning of parameters, a two-stage parameter identification scheme is proposed to identify both the dynamic-related and static-related parameters. Furthermore, a dynamic bipartite genetic algorithm (DBGA) is proposed to search for the accurate parameters efficiently. Finally, the effectiveness of the proposed approach is validated by comparisons in both the electromagnetic and electromechanical simulations with the detailed model.}
}