Tuning of Virtual Inertia Loop Parameters in DC Microgrids with Constant Power Loads Using Model Predictive Control

Nowadays, with the increasing global demand for renewable energy sources and their inherent fluctuations, the design of power electronic converter control system in DC microgrids has become more important. The presence of converter-based sources in microgrids introduces challenges such as lack of inertia. This research proposes a model predictive control approach to improve the dynamic response of low-inertia DC microgrids by controllable power sources. Using the concept of virtual inertia, the systems' stability and responsiveness to load changes and disturbances are enhanced. Simulation results derived in the MATLAB environment demonstrate the effectiveness of the proposed method in improving the dynamic performance of the DC microgrids.

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Publication Details

Published
2024-12-31
DOI
https://doi.org/10.1109/sgc64640.2024.10983444
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Tuning of Virtual Inertia Loop Parameters in DC Microgrids with Constant Power Loads Using Model Predictive Control

Hassan Bevrani, Sharara Rehimi, Qobad Shafiee, Sirwan Shazdeh et al.
Microgrid Control and Optimization
article

Tuning of Virtual Inertia Loop Parameters in DC Microgrids with Constant Power Loads Using Model Predictive Control

Hassan Bevrani, Sharara Rehimi, Qobad Shafiee, Sirwan Shazdeh, Ramin Abdoli
article en

Abstract

Nowadays, with the increasing global demand for renewable energy sources and their inherent fluctuations, the design of power electronic converter control system in DC microgrids has become more important. The presence of converter-based sources in microgrids introduces challenges such as lack of inertia. This research proposes a model predictive control approach to improve the dynamic response of low-inertia DC microgrids by controllable power sources. Using the concept of virtual inertia, the systems' stability and responsiveness to load changes and disturbances are enhanced. Simulation results derived in the MATLAB environment demonstrate the effectiveness of the proposed method in improving the dynamic performance of the DC microgrids.

University of Kurdistan (IR), Nagoya University (JP)
Affordable and clean energy
Openalex Percentile: Top 62%
Microgrid Control and Optimization
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