Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator
As a key element to connect renewable energy sources, grid-forming inverters (GFIs) mostly use droop control as an outer loop, but it can cause a swift change in the system frequency when disturbances arise. In the role of the inner loop control, the traditional model predictive control (MPC) is wid...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10945863/ |
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| author | Min Huang Huiying Zhang Kangan Wang Zhilei Yao Weimin Wu |
| author_facet | Min Huang Huiying Zhang Kangan Wang Zhilei Yao Weimin Wu |
| author_sort | Min Huang |
| collection | DOAJ |
| description | As a key element to connect renewable energy sources, grid-forming inverters (GFIs) mostly use droop control as an outer loop, but it can cause a swift change in the system frequency when disturbances arise. In the role of the inner loop control, the traditional model predictive control (MPC) is widely employed in converters, but it is heavily dependent on model parameters. To overcome the above drawbacks, a model-free predictive control with virtual synchronous generator (VSG-MFPC) is proposed in this study. The scheme uses an autoregressive MFPC based on an auto-regressive with exogenous input (ARX) model as an inner-loop control structure for voltage prediction, combined with a simplified virtual synchronous generator (VSG) as an outer-loop control structure for power sharing and inertial support control systems. The implementation of MFPC improves the parameter robustness of the system. Building on this, the improvement schemes of algorithmic parameter initialization, delay compensation and current limiting capability are further investigated. Additionally, incorporating the VSG into the outer loop strengthens the stability of the system’s frequency and voltage while also enhancing the system’s dynamic characteristics. The aforementioned advantages, along with the efficacy and feasibility of the proposed control method, are validated through simulation and experimental results. |
| format | Article |
| id | doaj-art-e8d49e055e7b444da81e51a940a9a63e |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-e8d49e055e7b444da81e51a940a9a63e2025-08-20T03:16:57ZengIEEEIEEE Access2169-35362025-01-0113579215793110.1109/ACCESS.2025.355608910945863Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous GeneratorMin Huang0https://orcid.org/0000-0002-2424-5315Huiying Zhang1Kangan Wang2https://orcid.org/0000-0003-3323-0630Zhilei Yao3https://orcid.org/0000-0003-3991-4929Weimin Wu4https://orcid.org/0000-0002-1567-7917Department of Electrical Engineering, Shanghai Maritime University, Shanghai, ChinaDepartment of Electrical Engineering, Shanghai Maritime University, Shanghai, ChinaDepartment of Electrical Engineering, Shanghai Maritime University, Shanghai, ChinaDepartment of Electrical Engineering, Shanghai Maritime University, Shanghai, ChinaDepartment of Electrical Engineering, Shanghai Maritime University, Shanghai, ChinaAs a key element to connect renewable energy sources, grid-forming inverters (GFIs) mostly use droop control as an outer loop, but it can cause a swift change in the system frequency when disturbances arise. In the role of the inner loop control, the traditional model predictive control (MPC) is widely employed in converters, but it is heavily dependent on model parameters. To overcome the above drawbacks, a model-free predictive control with virtual synchronous generator (VSG-MFPC) is proposed in this study. The scheme uses an autoregressive MFPC based on an auto-regressive with exogenous input (ARX) model as an inner-loop control structure for voltage prediction, combined with a simplified virtual synchronous generator (VSG) as an outer-loop control structure for power sharing and inertial support control systems. The implementation of MFPC improves the parameter robustness of the system. Building on this, the improvement schemes of algorithmic parameter initialization, delay compensation and current limiting capability are further investigated. Additionally, incorporating the VSG into the outer loop strengthens the stability of the system’s frequency and voltage while also enhancing the system’s dynamic characteristics. The aforementioned advantages, along with the efficacy and feasibility of the proposed control method, are validated through simulation and experimental results.https://ieeexplore.ieee.org/document/10945863/Grid forming invertersmodel predictive controlmodel free predictive controlvirtual synchronous generator |
| spellingShingle | Min Huang Huiying Zhang Kangan Wang Zhilei Yao Weimin Wu Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator IEEE Access Grid forming inverters model predictive control model free predictive control virtual synchronous generator |
| title | Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator |
| title_full | Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator |
| title_fullStr | Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator |
| title_full_unstemmed | Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator |
| title_short | Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator |
| title_sort | model free predictive control based on rls algorithm for grid forming inverters with virtual synchronous generator |
| topic | Grid forming inverters model predictive control model free predictive control virtual synchronous generator |
| url | https://ieeexplore.ieee.org/document/10945863/ |
| work_keys_str_mv | AT minhuang modelfreepredictivecontrolbasedonrlsalgorithmforgridforminginverterswithvirtualsynchronousgenerator AT huiyingzhang modelfreepredictivecontrolbasedonrlsalgorithmforgridforminginverterswithvirtualsynchronousgenerator AT kanganwang modelfreepredictivecontrolbasedonrlsalgorithmforgridforminginverterswithvirtualsynchronousgenerator AT zhileiyao modelfreepredictivecontrolbasedonrlsalgorithmforgridforminginverterswithvirtualsynchronousgenerator AT weiminwu modelfreepredictivecontrolbasedonrlsalgorithmforgridforminginverterswithvirtualsynchronousgenerator |