Enhanced Model Predictive Control for Voltage Source Inverters in Photovoltaic Microgrids with Unbalanced Loads and Wide Frequency Ranges

This study investigates power injection management in photovoltaic systems integrated into microgrids with voltage unbalances. An advanced technique of modulated predictive control is implemented to address variations in voltage frequency and amplitude, incorporating new algorithms based on the study of the operational region, allowing for an expanded operational range of the system. The findings show notable improvements in the system’s availability under these adverse conditions. It’s concluded that such strategies are essential for ensuring effective integration and sustainability of renewable energies in contemporary microgrids, which are subject to network fluctuations.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10906049
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Enhanced Model Predictive Control for Voltage Source Inverters in Photovoltaic Microgrids with Unbalanced Loads and Wide Frequency Ranges

José Espinoza, Jaime Rohten, Matías Garbarino
Microgrid Control and Optimization
article

Enhanced Model Predictive Control for Voltage Source Inverters in Photovoltaic Microgrids with Unbalanced Loads and Wide Frequency Ranges

José Espinoza, Jaime Rohten, Matías Garbarino
article en

Abstract

This study investigates power injection management in photovoltaic systems integrated into microgrids with voltage unbalances. An advanced technique of modulated predictive control is implemented to address variations in voltage frequency and amplitude, incorporating new algorithms based on the study of the operational region, allowing for an expanded operational range of the system. The findings show notable improvements in the system’s availability under these adverse conditions. It’s concluded that such strategies are essential for ensuring effective integration and sustainability of renewable energies in contemporary microgrids, which are subject to network fluctuations.

University of Concepción (CL), University of Bío-Bío (CL)
Affordable and clean energy
Openalex Percentile: Top 65%
Microgrid Control and Optimization
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