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Abstract

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.

Details

1009240
Title
A Taxonomy of Robust Control Techniques for Hybrid AC/DC Microgrids: A Review
Author
Parvizi Pooya 1 ; Amidi, Alireza Mohammadi 2   VIAFID ORCID Logo  ; Zangeneh, Mohammad Reza 3 ; Jordi-Roger, Riba 4   VIAFID ORCID Logo  ; Jalilian Milad 5   VIAFID ORCID Logo 

 Department of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; [email protected] 
 Department of Electrical Engineering, Razi University, Kermanshah 6714414971, Iran; [email protected], Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran; [email protected] (M.R.Z.); [email protected] (M.J.) 
 Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran; [email protected] (M.R.Z.); [email protected] (M.J.) 
 Department of Electrical Engineering, Universitat Politècnica de Catalunya, 08222 Terrassa, Spain 
 Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran; [email protected] (M.R.Z.); [email protected] (M.J.), Department of Physics, Faculty of Science, Lorestan University, Khorramabad 4431668151, Iran 
Publication title
Eng; Basel
Volume
6
Issue
10
First page
267
Number of pages
32
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
26734117
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-10-06
Milestone dates
2025-09-02 (Received); 2025-09-28 (Accepted)
Publication history
 
 
   First posting date
06 Oct 2025
ProQuest document ID
3265896506
Document URL
https://www.proquest.com/scholarly-journals/taxonomy-robust-control-techniques-hybrid-ac-dc/docview/3265896506/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-11-03
Database
ProQuest One Academic