基于动态插值粒子群算法的VSG鲁棒性优化策略

Robust Optimization Strategy of VSG Based on Dynamic Interpolation Particle Swarm Optimization （DI-PSO） Algorithm

中文关键词:虚拟同步发电机  小信号模型  动态插值粒子群算法  阻尼比  鲁棒性优化

keywords:virtual synchronous generator  small signal model  dynamic interpolation particle swarm optimization algorithm  damping ratio  robustness optimization

中文摘要:针对虚拟同步发电机（virtual synchronous generator，VSG）的参数选择缺乏系统性优化方法，传统策略难以在多约束条件下兼顾动态性能与运行鲁棒性，提出一种基于动态插值粒子群算法（dynamic interpolation particle swarm optimization，DI-PSO）的VSG鲁棒性优化策略。基于系统小信号（small signal，SS）模型构建适应度函数，通过DI-PSO结合特征值分析对VSG参数进行优化，重点解决参数选择过程中动态稳定性与多工作点适应性的协调问题。该方法在确保系统稳定裕度的前提下，利用特征值实部最小化策略提升动态响应性能，并通过电磁暂态仿真验证了优化参数在不同运行条件下的有效性。仿真结果表明，相较于传统参数整定方法，所提策略显著增强了VSG在复杂电网环境中的动态调节能力与运行弹性。

Abstract:Owing to the lack of systematic optimization methods for parameter selection of virtual synchronous generators （VSG），it is difficult to use traditional strategies to balance dynamic performance and operational robustness under multiple constraints. This paper proposes a robust optimization strategy for VSG based on dynamic interpolation particle swarm optimization （DI-PSO） Algorithm. A fitness function is established based on the system's small-signal （SS） model，and VSG parameters are optimized via DI-PSO integrated with eigenvalue analysis. The core focus is resolving the trade-off between dynamic stability and adaptability to multiple operating points during parameter tuning. On the premise of ensuring the system's stability margin，the proposed method adopts the strategy of minimizing the real parts of eigenvalues to enhance dynamic response performance. The effectiveness of the optimized parameters under various operating conditions is verified through electromagnetic transient simulation.Simulation results demonstrate that compared with traditional parameter tuning methods，the proposed strategy significantly enhances the dynamic regulation performance and operational resilience of VSG in complex power grid environments.