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ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Smart Grids
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1526992
This article is part of the Research Topic Advances in Renewable Energy System Monitoring, Situational Awareness, and Control View all 21 articles
An Improved Model-Free Predictive Voltage Control for Grid-Forming Inverter with Adaptive Ultra-Local Data Model in Renewable Energy System
Provisionally accepted- 1 State Grid Fujian Electric Power Company, Gulou, China
- 2 Putian Electric Power Supply Company of State Grid Fujian Electric Power Co., Ltd., Putian, China
Conventional model-based predictive voltage control (MBPVC) for grid-forming inverters (GFIs) in renewable energy system is sensitive to parametric accuracy. To address this issue, an improved model-free predictive voltage control (MFPVC) is proposed for grid-forming inverter. First, the parametric impact on MBPVC is analyzed in GFI. Then, the adaptive ultra-local data-model (ULDM) of the GFI is established for model-free voltage prediction. The ULDM of GFI is updated in each control period by combining the capacitor voltage gradient relationship. The linear extendedstate-observer with the adaptive strengthening factor is designed to enhance the performance of the ULDM. Additionally, the optimal switching sequence is proposed for further reducing voltage ripples. The duration of each voltage vector in corresponding optimal switching sequence is calculated based on the deadbeat principle. The proposed MFPVC method effectively eliminates parametric effect and improve the accuracy of model-free voltage prediction. Finally, the conventional MBPVC, conventional MFPVC and proposed MFPVC are compared by the designed hardware experimental platform of GFI.
Keywords: grid-forming inverter1, model-free predictive voltage control2, adaptive ultra-local data-model3, optimal switching sequence4, parameter robustness5
Received: 12 Nov 2024; Accepted: 10 Mar 2025.
Copyright: © 2025 Lin, Zhu and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yifu Lin, State Grid Fujian Electric Power Company, Gulou, China
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