机电工程技术2025，Vol.54Issue(18)：35-41,58,8.DOI:10.3969/j.issn.1009-9492.2025.18.007
基于灰狼-粒子群算法的VSG参数自适应控制策略研究
Research on VSG Parameter Adaptive Control Strategy Based on Grey Wolf Particle Swarm Optimization
黄希宇 1彭钟1
作者信息
- 1. 长江大学电子信息工程学院,湖北 荆州 434023
- 折叠
摘要
Abstract
The adaptive control strategy based on the particle swarm optimization algorithm yields damping inertia parameters with limited precision in the strategy and exhibits significant transient frequency response overshoot.Therefore,this study focuses on optimizing the adaptive control parameters of damping inertia using the grey wolf particle swarm optimization approach.By analyzing the angular frequency oscillation curve of the active frequency link in the VSG system during transient states,an adjustment method for VSG parameter adaptive control based on oscillation laws is identified,and a range of values for damping and inertia is determined based on optimal second-order systems.The optimal initial value for the control strategy is obtained using the gray wolf particle swarm optimization.A simulation model of grid-connected inverter of the VSG system under different control strategies is established.Simulation results demonstrate that compared with the conventional VSG control,the proposed control strategy reduces frequency response overshoot by 37.84%.Furthermore,compared with the PSO-based parameter adaptive control,it reduces the overshoot by 8%,which validates the superiority of the damping inertia adaptive control strategy based on the gray wolf particle swarm optimization algorithm.关键词
灰狼-粒子群算法/虚拟同步发电机/阻尼惯量/自适应控制/粒子群优化算法Key words
gray wolf particle swarm optimization/virtual synchronous generator/damping inertia/adaptive control/particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
黄希宇,彭钟..基于灰狼-粒子群算法的VSG参数自适应控制策略研究[J].机电工程技术,2025,54(18):35-41,58,8.
