Integrated Intelligent Energy ›› 2026, Vol. 48 ›› Issue (3): 27-36.doi: 10.3969/j.issn.2097-0706.2026.03.003

• Power System Modeling and Control • Previous Articles     Next Articles

Modeling and stability analysis of grid-forming energy storage systems based on dynamic phasors

ZENG Yunrui(), WANG Zeqi*(), XU Bo(), JIANG Tianyu(), LI Xijun(), LI Tingyi()   

  1. State Grid Sichuan Electric Power Company Tianfu New Area Power Supply CompanyChengdu 610213, China
  • Received:2024-08-28 Revised:2024-11-12 Published:2026-03-25
  • Contact: WANG Zeqi E-mail:zengyunrui97@163.com;295353451@qq.com;15801486809@qq.com;360166898@qq.com;daphne_epic@163.com;651558105@qq.com

Abstract:

With the increasing penetration of new energy in the power grid, the parallel operation of grid-forming energy storage (GFS) devices has become crucial for ensuring power system stability. However, the parallel operation of traditional GFS devices mainly relies on the droop control characteristics of controllers, and droop control alone is insufficient to ensure system stability when the system experiences disturbances. Therefore, a small-signal modeling method based on dynamic phasors was proposed, combined with eigenvalue analysis to identify key factors affecting the interactions among parallel GFS devices. Compared with traditional single frequency-domain or time-domain methods, this method could more precisely characterize the high-frequency dynamic response characteristics of inverters and quantify the coupling effects of control and network parameters on system stability, thereby expanding the stable operation region of the system without introducing additional damping. Moreover, the modular design of this method facilitated adaptation to different system topologies, significantly improving the adaptability of the model and the accuracy of stability prediction. Simulation verification using Matlab/Simulink showed that the proposed method could effectively evaluate system stability under various operating conditions, offering higher accuracy and flexibility compared with traditional methods.

Key words: grid-forming energy storage, droop control, dynamic phasor, eigenvalue analysis, small-signal modeling

CLC Number: