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Energies
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Advances in Power Converters and Microgrids
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Advances in Power Converters and 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: 10 October 2025 | Viewed by 238

Special Issue Editor

Dr. Vikram Roy Chowdhury

E-Mail Website
Guest Editor
Power Systems Engineering Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
Interests: grid support; modular multilevel converter; control architecture; energy function; grid-forming converter; solid state transformer; microgrid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the immense advancements in the field of renewable energy sources, a fully centralized grid is no longer just a dream. In today’s applications, scenarios such as these are more discrete and decentralized in terms of both power production and operation. The power converters used for such environments need to follow a wide range of rules in terms of IEEE codes, current ripples, operational limits, etc. Therefore, it is first necessary to understand the challenges in this scenario, before trying to solve them with new converter topologies, new granular-level control modifications, or with bigger system-level impacts, and then mitigating them.

This Special Issue aims to present new advances in converter topologies, their operation, and their major impact in the field of microgrids.

Topics of interest for publication include, but are not limited to, the following:

  • New converter topologies applied for DC/AC systems for renewable applications;
  • Applications based on solid-state transformers for renewable energy systems;
  • Advanced linear/nonlinear control architecture for renewable energy resources;
  • Impacts of using grid-forming converters in a microgrid and their operation;
  • Different topologies of grid-forming converters and their operation;
  • Application of grid-forming technologies to existing systems and their impacts.

Dr. Vikram Roy Chowdhury
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • DC/AC systems
  • converters
  • microgrid
  • grid-forming technologies

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Published Papers (1 paper)

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Review

33 pages, 6831 KiB  
Review
Machine Learning and Artificial Intelligence Techniques in Smart Grids Stability Analysis: A Review
by Arman Fathollahi
Energies 2025, 18(13), 3431; https://doi.org/10.3390/en18133431 - 30 Jun 2025
Abstract
The incorporation of renewable energy sources in power grids has necessitated innovative solutions for effective energy management. Smart grids have emerged as transformative systems which integrate consumer, generator and dual-role entities to deliver secure, sustainable and economical electricity supplies. This review explores the [...] Read more.
The incorporation of renewable energy sources in power grids has necessitated innovative solutions for effective energy management. Smart grids have emerged as transformative systems which integrate consumer, generator and dual-role entities to deliver secure, sustainable and economical electricity supplies. This review explores the important role of artificial intelligence and machine learning approaches in managing the developing stability characteristics of smart grids. This work starts with a discussion of the smart grid’s dynamic structures and subsequently transitions into an overview of machine learning approaches that explore various algorithms and their applications to enhance smart grid operations. A comprehensive analysis of frameworks illustrates how machine learning and artificial intelligence solve issues related to distributed energy supplies, load management and contingency planning. This review includes general pseudocode and schematic architectures of artificial intelligence and machine learning methods which are categorized into supervised, semi-supervised, unsupervised and reinforcement learning. It includes support vector machines, decision trees, artificial neural networks, extreme learning machines and probabilistic graphical models, as well as reinforcement strategies like dynamic programming, Monte Carlo methods, temporal difference learning and Deep Q-networks, etc. Examination extends to stability, voltage and frequency regulation along with fault detection methods that highlight their applications in increasing smart grid operational boundaries. The review underlines the various arrays of machine learning algorithms that emphasize the integration of reinforcement learning as a pivotal enhancement in intelligent decision-making within smart grid environments. As a resource this review offers insights for researchers, practitioners and policymakers by providing a roadmap for leveraging intelligent technologies in smart grid control and stability analysis. Full article
(This article belongs to the Special Issue Advances in Power Converters and Microgrids)
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