Author
Listed:
- Gianni Avilan-Losee
(School of Engineering and Computer Science, PEMD Group, Washington State University Vancouver, Vancouver, WA 98686, USA)
- Hang Gao
(School of Engineering and Computer Science, PEMD Group, Washington State University Vancouver, Vancouver, WA 98686, USA)
Abstract
Grid-forming (GFM) inverters have recently seen wider adoption in microgrids and inverter-based-resource (IBR)-penetrated grids, and are primarily used to establish grid voltage under a wide array of conditions. In the existing literature, GFM control is almost exclusively applied using voltage-source inverters (VSIs). However, due to the inherent limitations of available semiconductor devices’ current ratings, inverter-side current must be limited in VSIs, particularly during grid-fault conditions. These limitations complicate the real-world application of GFM functionality in VSIs, and complex control methodologies and tuning parameters are required as a result. In the following study, GFM control is instead applied to a buck-type current-source inverter (CSI) using a combination of linear droop-control and finite-control-set (FCS) mode-predictive control (MPC) that will be referred to herein as hybrid model-predictive control (HMPC). The resulting inverter features a simple topology, inherent current limiting capabilities, and a relatively simple and intuitive control structure. Verification was performed on a 1MVA/630V system via MATLAB/Simulink, and the simulation results demonstrate strong performance in voltage establishment, power regulation, and low-voltage ride through under-grid-fault conditions, highlighting its potential as a competent alternative to VSIs in GFM applications, and lacking the inherent limitations and/or complexity of existing GFM control methodologies.
Suggested Citation
Gianni Avilan-Losee & Hang Gao, 2025.
"Grid-Forming Buck-Type Current-Source Inverter Using Hybrid Model-Predictive Control,"
Energies, MDPI, vol. 18(15), pages 1-17, August.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:15:p:4124-:d:1716993
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