| 引用本文: | 张子星,赵晋斌,曾志伟,等.基于RBF的VSG虚拟惯量和动态阻尼补偿自适应控制[J].电力系统保护与控制,2024,52(2):155-164. |
| ZHANG Zixing,ZHAO Jinbin,ZENG Zhiwei,et al.VSG virtual inertia and dynamic damping compensation adaptive control based on RBF[J].Power System Protection and Control,2024,52(2):155-164 |
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| 摘要: |
| 虚拟同步机(virtual synchronous generator, VSG)技术可以使并网逆变器具有与同步发电机类似的外特性。VSG系统暂态稳定性的主要影响因素是虚拟惯量和阻尼系数，但现有的控制策略在参数调节过程中存在灵活性不足的缺点，不能有效解决系统暂态稳定性和暂态恢复时间的问题。针对这一问题，提出动态调节阻尼补偿量的概念。将阻尼系数和阻尼补偿量共同作为系统的等效阻尼系数，设计了基于径向基函数(radial basis function, RBF)的VSG虚拟惯量和动态阻尼补偿自适应控制策略，实现了参数之间的解耦，使系统的阻尼随着系统频率的变化进行动态调整。通过建立VSG数学模型，确定了参数的具体取值范围。最后，在仿真平台上搭建VSG系统，分别在出力波动和低压穿越两种工况下验证了所提控制策略相较于传统RBF控制策略的优越性。 |
| 关键词: 虚拟同步机 虚拟惯量 动态阻尼补偿 RBF神经网络 自适应控制 |
| DOI：10.19783/j.cnki.pspc.230854 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(52177184) |
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| VSG virtual inertia and dynamic damping compensation adaptive control based on RBF |
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ZHANG Zixing1, ZHAO Jinbin2, ZENG Zhiwei1, MAO Ling1, ZHANG Yongli3
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1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. Offshore Wind Power Research Institute, Shanghai University of Electric Power, Shanghai 200090, China;
3. Shanghai Institute of Space Power-Sources, Shanghai 200245, China
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| Abstract: |
| Virtual synchronous generator (VSG) technology enables grid-connected inverters to exhibit external characteristics similar to synchronous generators. The primary factors influencing the transient stability of the VSG system are virtual inertia and damping coefficients. However, existing control strategies suffer from a lack of flexibility during parameter adjustment, failing to effectively address transient stability and recovery time issues in the system. To address this issue, this paper proposes the concept of dynamically adjusting the damping compensation amount. It considers the damping coefficient and damping compensation amount together as the equivalent damping coefficient of the system. A RBF-based VSG virtual inertia and dynamic damping compensation adaptive control strategy is designed to achieve decoupling among parameters. This strategy enables the damping of the system to be dynamically adjusted as the system frequency changes. By establishing a mathematical model for the VSG, specific parameter ranges are determined. Finally, this paper builds a VSG system on a simulation platform and validates the superiority of the proposed control strategy over traditional RBF control strategies in conditions of output fluctuation and low-voltage ride through. |
| Key words: virtual synchronous generator (VSG) virtual inertia dynamic damping compensation radial basis function neural network (RBFNN) adaptive control |
