A Taxonomy of Robust Control Techniques for Hybrid AC/DC Microgrids: A Review
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| Publicado en: | Eng vol. 6, no. 10 (2025), p. 267-298 |
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| Otros Autores: | , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 024 | 7 | |a 10.3390/eng6100267 |2 doi | |
| 035 | |a 3265896506 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Parvizi Pooya |u Department of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; pxp046@alumni.bham.ac.uk | |
| 245 | 1 | |a A Taxonomy of Robust Control Techniques for Hybrid AC/DC Microgrids: A Review | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Hybrid AC/DC microgrids have emerged as a promising solution for integrating diverse renewable energy sources, enhancing efficiency, and strengthening resilience in modern power systems. However, existing control schemes exhibit critical shortcomings that limit their practical effectiveness. Traditional linear controllers, designed around nominal operating points, often fail to maintain stability under large load and generation fluctuations. Optimization-based methods are highly sensitive to model inaccuracies and parameter uncertainties, reducing their reliability in dynamic environments. Intelligent approaches, such as fuzzy logic and ML-based controllers, provide adaptability but suffer from high computational demands, limited interpretability, and challenges in real-time deployment. These limitations highlight the need for robust control strategies that can guarantee reliable operation despite disturbances, uncertainties, and varying operating conditions. Numerical performance indices demonstrate that the reviewed robust control strategies outperform conventional linear, optimization-based, and intelligent controllers in terms of system stability, voltage and current regulation, and dynamic response. This paper provides a comprehensive review of recent robust control strategies for hybrid AC/DC microgrids, systematically categorizing classical model-based, intelligent, and adaptive approaches. Key research gaps are identified, including the lack of unified benchmarking, limited experimental validation, and challenges in integrating decentralized frameworks. Unlike prior surveys that broadly cover microgrid types, this work focuses exclusively on hybrid AC/DC systems, emphasizing hierarchical control architectures and outlining future directions for scalable and certifiable robust controllers. Also, comparative results demonstrate that state of the art robust controllers—including H∞-based, sliding mode, and hybrid intelligent controllers—can achieve performance improvements for metrics such as voltage overshoot, frequency settling time, and THD compared to conventional PID and droop controllers. By synthesizing recent advancements and identifying critical research gaps, this work lays the groundwork for developing robust control strategies capable of ensuring stability and adaptability in future hybrid AC/DC microgrids. | |
| 653 | |a Proportional integral derivative | ||
| 653 | |a Robust control | ||
| 653 | |a Dynamic response | ||
| 653 | |a Distributed generation | ||
| 653 | |a Adaptability | ||
| 653 | |a Parameter sensitivity | ||
| 653 | |a Voltage | ||
| 653 | |a Optimization techniques | ||
| 653 | |a Fuzzy logic | ||
| 653 | |a Taxonomy | ||
| 653 | |a Control systems | ||
| 653 | |a Systems stability | ||
| 653 | |a Parameter uncertainty | ||
| 653 | |a Efficiency | ||
| 653 | |a Electric power systems | ||
| 653 | |a Control algorithms | ||
| 653 | |a Electric potential | ||
| 653 | |a Decision making | ||
| 653 | |a Renewable energy sources | ||
| 653 | |a Optimization | ||
| 653 | |a Design | ||
| 653 | |a Sliding mode control | ||
| 653 | |a Performance indices | ||
| 653 | |a Real time | ||
| 653 | |a Controllers | ||
| 653 | |a H-infinity control | ||
| 653 | |a Comparative analysis | ||
| 700 | 1 | |a Amidi, Alireza Mohammadi |u Department of Electrical Engineering, Razi University, Kermanshah 6714414971, Iran; alireza.moamidi@gmail.com | |
| 700 | 1 | |a Zangeneh, Mohammad Reza |u Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran; m.zangeneh@alumni.sbu.ac.ir (M.R.Z.); jalilianm70@gmail.com (M.J.) | |
| 700 | 1 | |a Jordi-Roger, Riba |u Department of Electrical Engineering, Universitat Politècnica de Catalunya, 08222 Terrassa, Spain | |
| 700 | 1 | |a Jalilian Milad |u Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran; m.zangeneh@alumni.sbu.ac.ir (M.R.Z.); jalilianm70@gmail.com (M.J.) | |
| 773 | 0 | |t Eng |g vol. 6, no. 10 (2025), p. 267-298 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
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