A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks

Yang, Mingshuo; Zhang, Lixia; Song, Xiaoying; Kang, Wei; Kang, Zhongjian

doi:10.3390/electronics14040785

Open AccessArticle

A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks

by

Mingshuo Yang

¹,

Lixia Zhang

^1,*,

Xiaoying Song

²,

Wei Kang

¹

and

Zhongjian Kang

¹

College of New Energy, China University of Petroleum (East China), Qingdao 266580, China

²

State Grid Shandong Electric Power Company Qingdao Power Supply Company, Qingdao 266000, China

^*

Author to whom correspondence should be addressed.

Electronics 2025, 14(4), 785; https://doi.org/10.3390/electronics14040785

Submission received: 16 January 2025 / Revised: 11 February 2025 / Accepted: 12 February 2025 / Published: 17 February 2025

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Abstract

This paper proposes a grid-forming (GFM) photovoltaic system transient control strategy based on the combination of dynamic virtual impedance and the radial basis function (RBF) algorithm. First, the virtual synchronous generator (VSG) model is analyzed to understand how virtual impedance affects current surges and system stability during faults. By using dynamic virtual impedance throughout the fault, the strategy suppresses current spikes and improves stability. The RBF neural network dynamically adjusts virtual inertia and damping coefficients to optimize transient power-angle characteristics and speed up recovery during fault restoration. Simulation results show that the strategy reduces transient current surges, improves angle recovery, and boosts system stability during voltage sag. This approach offers an effective solution for low-voltage ride-through (LVRT) and transient control in photovoltaic grid-connected systems, ensuring the resilience and stability of renewable energy integration into the grid.

Keywords: grid-forming photovoltaic system; virtual synchronous generator; virtual impedance; radial basis function neural network; low-voltage ride-through

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MDPI and ACS Style

Yang, M.; Zhang, L.; Song, X.; Kang, W.; Kang, Z. A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks. Electronics 2025, 14, 785. https://doi.org/10.3390/electronics14040785

AMA Style

Yang M, Zhang L, Song X, Kang W, Kang Z. A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks. Electronics. 2025; 14(4):785. https://doi.org/10.3390/electronics14040785

Chicago/Turabian Style

Yang, Mingshuo, Lixia Zhang, Xiaoying Song, Wei Kang, and Zhongjian Kang. 2025. "A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks" Electronics 14, no. 4: 785. https://doi.org/10.3390/electronics14040785

APA Style

Yang, M., Zhang, L., Song, X., Kang, W., & Kang, Z. (2025). A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks. Electronics, 14(4), 785. https://doi.org/10.3390/electronics14040785

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A Transient Control Strategy for Grid-Forming Photovoltaic Systems Based on Dynamic Virtual Impedance and RBF Neural Networks

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