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METHODS article
Front. Energy Res.
Sec. Smart Grids
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1574038
Control Parameter Identification Method for Virtual Synchronous Generator Considering Electric Vehicles Based on Dynamic Particle Swarm Optimization
Provisionally accepted
Dongqi Wu 1*
Yong Hu 2- 1 Zhejiang Economic and Technological Research Institute, State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, China
- 2 State Grad AKSU Electric Power Supply Company, Aksu, China
To address the issues of insufficient control parameter identification accuracy and convergence speed during the grid connection of distributed power sources, a control parameter identification method for the Virtual Synchronous Generator (VSG) converter model considering the integration of electric vehicles (EVs) based on the dynamic particle swarm optimization algorithm is proposed. By constructing a VSG inverter control model suitable for distributed power sources and EV charging systems, analyzing the interactions between active and reactive power control loops under EV integration scenarios, selecting parameters and observations to be identified, and improving the Particle Swarm Optimization (PSO) algorithm based on actual conditions, the method ensures enhanced system adaptability. Simulation results demonstrate that the proposed method exhibits higher dynamic response capabilities, system stability, and adaptability under varying load conditions and uncertainties introduced by EV charging behaviors, highlighting its significant engineering application value.
Keywords: VSG Converter, EV charging, Generator control model, Parameter identification, Particle Swarm Optimization
Received: 10 Feb 2025; Accepted: 21 Mar 2025.
Copyright: © 2025 Wu and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Dongqi Wu, Zhejiang Economic and Technological Research Institute, State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, China
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