Recent Advances in Control and Optimization in Microgrids

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 15 February 2026 | Viewed by 977

Special Issue Editors


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Guest Editor
Department of Engineering, Edge Hill University, St Helens Road, Ormskirk, Lancashire L39 4QP, UK
Interests: microgrids; flexible AC distribution devices; power quality; converter control
Department of Engineering, Edge Hill University, St Helens Road, Ormskirk, Lancashire L39 4QP, UK
Interests: future smart grids; sensors and instrumentation; robotics
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Special Issue Information

Dear Colleagues,

Many countries have promised to reduce greenhouse gas emissions and meet the net zero target. To achieve this, the usage of renewable energy resources needs to be increased. For attaining the widespread usage and adoption of renewable energy resources, all countries need to build more and more microgrids. Microgrids are self-controllable entities that consist of a combination of several renewable energy sources, battery systems, and power electronic devices, all integrated together in an efficient and reliable manner. Controlling and optimizing the resources in a microgrid form the two major objectives to bring about a cleaner and greener world. A microgrid consists of several converters such as rectifiers, inverters, and choppers. These converters are used to interface the renewable energy resources, such as photovoltaic (PV) systems, storage battery systems, and wind turbine generator systems, with different types of AC and DC loads. One of the major objectives is to control these converters, to regulate their output voltage and frequency, and to maintain the satisfactory operation of the different loads in a microgrid. The other vital objective is to optimize the microgrid performance by efficient energy management, operating cost reduction, emission reduction, profit maximization, etc. Therefore, the aim of this Special Issue is to cover these two objectives in a microgrid—converter control and system-level optimization. Areas to be covered in this Special Issue may include recent and novel research trends related, but not limited, to the following objectives:

  • Design and development of AC, DC, and hybrid microgrids and multi-microgrids.
  • Interconnection strategies for distributed energy resources (DERs).
  • Advanced control strategies (e.g., model predictive control, AI-driven approaches).
  • Optimization of energy management systems to enhance efficiency and reliability.
  • Challenges and solutions for integrating solar, wind, and other renewable energy sources.
  • Management of intermittency and energy storage systems.
  • Role of batteries, supercapacitors, and other storage technologies.
  • Economic and environmental impacts of storage in microgrid setups.
  • Transition mechanisms and control during grid-connected to islanded mode.
  • Operational strategies for stand-alone microgrids in remote or disaster-prone areas.
  • Implementation of microgrids in urban, rural, and industrial settings.
  • Lessons learned from real-world deployments.

Dr. Thomas John
Dr. Umar Khan
Guest Editors

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Keywords

  • converter control
  • grid-connected microgrids
  • islanded microgrids
  • proportional–integral control
  • model predictive control
  • neural network-based control
  • renewable energy integration
  • smart grid
  • energy storage systems

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Published Papers (2 papers)

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Research

20 pages, 3116 KB  
Article
A Residential Droop-Controlled AC Nanogrid with Power Quality Enhancement
by Ayesha Wajiha Aslam, Víctor Minambres-Marcos and Carlos Roncero-Clemente
Electronics 2025, 14(16), 3306; https://doi.org/10.3390/electronics14163306 - 20 Aug 2025
Viewed by 334
Abstract
Harmonic distortion from non-linear loads poses a significant challenge to power quality in residential nanogrids, often requiring complex control strategies and communication between distributed resources. This paper presents a parallel hybrid inverter system for an AC nanogrid that enhances power quality using only [...] Read more.
Harmonic distortion from non-linear loads poses a significant challenge to power quality in residential nanogrids, often requiring complex control strategies and communication between distributed resources. This paper presents a parallel hybrid inverter system for an AC nanogrid that enhances power quality using only decentralized droop-based primary control, without the need for secondary control or communication links. The system features two inverters with strategic placement: one maintains voltage stability at the point of common coupling, while the other directly supplies the harmonic and reactive current demanded by non-linear loads. A compensation mechanism allows the second inverter to dynamically switch from supplying sinusoidal current to injecting targeted harmonic components, effectively isolating distortion from the main grid. Simulation results confirm that this approach significantly reduces voltage distortion at the PCC and ensures balanced power sharing, all while simplifying the control architecture. The proposed method offers a scalable, cost-effective solution for residential nanogrids seeking to integrate diverse loads and distributed energy resources while maintaining high power quality. Full article
(This article belongs to the Special Issue Recent Advances in Control and Optimization in Microgrids)
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18 pages, 4058 KB  
Article
A Transferable DRL-Based Intelligent Secondary Frequency Control for Islanded Microgrids
by Sijia Li, Frede Blaabjerg and Amjad Anvari-Moghaddam
Electronics 2025, 14(14), 2826; https://doi.org/10.3390/electronics14142826 - 14 Jul 2025
Viewed by 360
Abstract
Frequency instability poses a significant challenge to the overall stability of islanded microgrid systems. Deep reinforcement learning (DRL)-based intelligent control strategies are drawing considerable attention for their ability to operate without the need for previous system dynamics information and the capacity for autonomous [...] Read more.
Frequency instability poses a significant challenge to the overall stability of islanded microgrid systems. Deep reinforcement learning (DRL)-based intelligent control strategies are drawing considerable attention for their ability to operate without the need for previous system dynamics information and the capacity for autonomous learning. This paper proposes an intelligent frequency secondary compensation solution that divides the traditional secondary frequency control into two layers. The first layer is based on a PID controller and the second layer is an intelligent controller based on DRL. To address the typically extensive training durations associated with DRL controllers, this paper integrates transfer learning, which significantly expedites the training process. This scheme improves control accuracy and reduces computational redundancy. Simulation tests are executed on an islanded microgrid with four distributed generators and an IEEE 13-bus system is utilized for further validation. Finally, the proposed method is validated on the OPAL-RT real-time test platform. The results demonstrate the superior performance of the proposed method. Full article
(This article belongs to the Special Issue Recent Advances in Control and Optimization in Microgrids)
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