Advanced Distributed Control and Optimization Technologies for Microgrids
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".
Deadline for manuscript submissions: 15 May 2026 | Viewed by 397
Special Issue Editors
Interests: modelling and simulation; operation optimization; decision analysis for complex systems including cascaded hydropower systems, active distribution systems, microgrids, and unmanned systems
Special Issues, Collections and Topics in MDPI journals
Interests: energy management for microgrids; optimal PMU placement in distribution systems; distributed optimization
Special Issues, Collections and Topics in MDPI journals
Interests: modeling and optimization control for complex systems including unmanned aerial vehicle power systems, ro-bot power systems, and other hybrid power systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Distributed optimization and control of microgrids play important roles in advancing modern energy systems toward sustainability and robustness. By enabling decentralized decision-making among distributed energy resources (DERs), such as solar PV, wind turbines, and energy storage, these strategies eliminate the reliance on centralized controllers, thereby enhancing operational flexibility and reducing the vulnerability of the grid. Distributed control frameworks allow users to autonomously adjust generation and consumption while maintaining grid stability through peer-to-peer coordination, even under communication constraints or component failures. They also improve scalability for expanding microgrids and support plug-and-play compatibility with new DERs. Furthermore, distributed optimization ensures efficient real-time operation by balancing supply–demand mismatches, minimizing energy costs, and integrating renewable variability without compromising voltage or frequency. These advancements are critical for achieving low-carbon energy transitions, ensuring smart grids operate reliably in islanded or grid-connected modes while promoting community-level energy autonomy.
This Special Issue focuses on the distributed optimization and control of microgrids in order to handle the increasing complexity of modern power systems. It seeks contributions that explore distributed planning, modelling, and analysis techniques aimed at enhancing microgrid stability and efficiency. Emphasis is placed on innovative scheduling optimization methods, robust control strategies, advanced energy management systems, and the use of parallel computing to handle large scale data and real-time decision-making. By these aspects, this Special Issue aims to present comprehensive solutions for the coordinated operation of distributed energy resources, ensuring reliable and sustainable energy supply in diverse application scenarios.
We look forward to receiving your contributions.
Dr. Jingrui Zhang
Dr. Tengpeng Chen
Dr. Po Li
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- distributed optimization
- distributed control
- microgrid planning
- modeling analysis
- stability assessment
- scheduling optimization
- control strategies
- energy management
- parallel computing
- distributed energy systems
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