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一种用于抑制功率振荡的风电机组构网型控制参数优化整定算法

A Novel Optimized Parameter Tuning Algorithm for Wind Turbine Grid-Forming Control to Mitigate Power Oscillations

作者 Duc-Tung Trinh · Yuan-Kang Wu · Manh-Hai Pham
期刊 IEEE Transactions on Sustainable Energy
出版日期 2025年7月
卷/期 第 17 卷 第 1 期
技术分类 风电变流技术
技术标签 构网型GFM 下垂控制 模型预测控制MPC 系统并网技术
相关度评分 ★★★★ 4.0 / 5.0
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中文摘要

本文针对构网型风电机组(GFM-WT)因内外环控制耦合引发的功率振荡问题,建立线性化状态空间模型,开展小信号灵敏度分析,并提出兼顾阻尼比与带宽约束的自动参数整定算法,在WSCC 9节点和NE 39节点系统中验证其有效抑制振荡、提升系统稳定性的能力。

English Abstract

As the transition from synchronous generators (SGs) to renewable energy sources (RESs) accelerates, grid forming wind turbines (GFM-WTs) are increasingly expected to play a critical role in maintaining power system stability. However, the integration of GFM without thoroughly considering the interaction between the outer and inner control loops can induce power oscillations. Therefore, this paper offers a systematic sensitivity analysis to explicitly reveal how the control parameters contribute to power oscillations in the GFM-WT system. This analysis is based on a linearized state-space model for the GFM-WT system, incorporating comprehensive system dynamics and control strategies. Furthermore, an optimized control algorithm is developed based on a comprehensive small-signal model, incorporating essential constraints such as the eigenvalue damping ratio and the control loop bandwidth. The algorithm autonomously tunes the control parameters of both the inner and outer loop systems, resulting in optimal parameter values. A comprehensive stability analysis was conducted to validate the effectiveness of the proposed algorithm in ensuring system stability. The proposed method is verified through various scenario in modified WSCC 9-bus and New England 39-bus systems. Simulation results indicate that the proposed algorithm effectively mitigates power oscillations in the WT output, subsequently reducing power oscillations in the SG.
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SunView 深度解读

该研究对阳光电源风电变流器产品线(如SG225HX等大功率风电变流器)的构网型控制升级具有直接参考价值。其内外环协同优化思路可迁移至ST系列PCS在风光储混合构网场景中的参数自适应整定,增强PowerTitan系统在弱电网下的振荡抑制能力。建议将该算法嵌入iSolarCloud平台,实现风电/储能变流器的远程智能参数优化与在线稳定性评估。