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VSG Frequency Modulation Strategy Based on Adaptive Parameter Adjustment and Model Predictive Control
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Shidong ZHANG  Student Member, CPSS, Peiqiang LI
Journal of Power Supply | 2026, 24(9) : 108 - 120
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Journal of Power Supply | 2026, 24(9): 108-120
• Renewable Energy Generation and Energy Storage •
VSG Frequency Modulation Strategy Based on Adaptive Parameter Adjustment and Model Predictive Control
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Shidong ZHANG  Student Member, CPSS, Peiqiang LI
Affiliations
  • College of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou 350118, China
Published: 2026-09-30 doi: 10.13234/j.issn.2095-2805.2026.9.108
Outline
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Virtual synchronous generator (VSG) has become an effective means to solve the problem of grid-connected frequency fluctuation of new energy by simulating the inertia characteristics of traditional generators. However, in the traditional VSG method, the moment of inertia and damping coefficient are usually fixed, which may lead to frequency deviation when the load changes. Therefore, a method combining adaptive parameter adjustment and model predictive control (MPC) is proposed to optimize the frequency performance of VSG. By analyzing the small-signal model of VSG, an adaptive adjustment strategy is proposed to suppress frequency fluctuation. At the same time, MPC is used to dynamically adjust the input power of VSG to enhance the response of power generation units to the change of power demand. Simulation results show that the proposed method effectively improves the frequency stability of the system.

Virtual synchronous generator  /  adaptive parameter adjustment  /  model predictive control  /  system frequency characteristics
张世栋中国电源学会学生会员, 李培强. 基于自适应参数调节与模型预测控制结合的VSG调频策略. 电源学报, 2026 , 24 (9) : 108 -120 . DOI: 10.13234/j.issn.2095-2805.2026.9.108
Shidong ZHANG, Peiqiang LI. VSG Frequency Modulation Strategy Based on Adaptive Parameter Adjustment and Model Predictive Control[J]. Journal of Power Supply, 2026 , 24 (9) : 108 -120 . DOI: 10.13234/j.issn.2095-2805.2026.9.108
Funding
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  • National Basic Research Program (973 Program)(2021YFB2601504)
  • National Natural Science Foundation of China(52377097)
Appendix
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Year 2026 volume 24 Issue 9
49
9
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.9.108
  • Receive Date：2024-12-17
  • Online Date：2026-10-29
  • Published：2026-09-30
Article Data
Affiliations
History
  • Received：2024-12-17
  • Revised：2025-03-17
  • Accepted：2025-04-06
Funding
National Basic Research Program (973 Program)(2021YFB2601504)
National Natural Science Foundation of China(52377097)
Affiliations
    College of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou 350118, China
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