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Energies
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Microgrids and Distributed Energy Resources: Planning, Design, Protection, and Operation
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Microgrids and Distributed Energy Resources: Planning, Design, Protection, and Operation

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: 25 December 2026 | Viewed by 1984

Special Issue Editors

Dr. Guodong Liu

E-Mail Website
Guest Editor
Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Interests: power system operation and planning; renewable energy; microgrids; distribution management system; demand response
Special Issues, Collections and Topics in MDPI journals
Dr. Maximiliano F. Ferrari

E-Mail Website
Guest Editor
Electrification and Energy Infrastructures Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Interests: microgrids; controls of solar and wind energy systems; protection

Special Issue Information

Dear Colleagues,

Driven by regulatory orders and customer expectations for efficient, economic, sustainable, reliable, and resilient electricity supply, microgrids and distributed energy resources (DERs) have been increasingly deployed worldwide, which brings unprecedented opportunities and challenges to the electric power systems, especially distribution grids. Microgrids provide a platform for the aggregation and optimization of mixed asset fleets of DERs, energy storage systems, electric vehicles (EVs), and controllable loads at the grid-edge to provide cost-efficient power supply with enhanced resilience and reliability. Nevertheless, these grid-edge asset fleets motivate the need for integrated models and tools for microgrid planning, design, and operations at increasing levels of complexity, ranging from the inclusion of control and stability of grid forming/following inverters to integration with other interdependent systems like thermal, natural gas, buildings, etc.

This Special Issue aims to present and disseminate the most recent advances related to the plan, design, and operation of microgrids (or aggregations of microgrids and DERs) for various needs and stakeholders (e.g., utilities, developers, aggregators, and campuses). In this Special Issue, original research articles and reviews are welcome.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • Microgrid conceptual design and operation approaches and tools.
  • Approaches that support microgrids to interact with utility management systems.
  • Tools and approaches that support microgrids to provide flexibility and grid services.
  • Tools and approaches that support microgrids to participate in energy and ancillary markets.
  • Grid restoration and recovery considering microgrids and DERs.
  • Grid reliability and resilience enhancement with microgrids and DERs.
  • Tools and approaches that support aggregated design and operation of microgrids and DERs.
  • Approaches for microgrid stability analysis.
  • Tools and approaches that enable microgrids to interact with thermal, natural gas, water and building systems.
  • Networked/nested microgrids.
  • Hierarchical and distributed control of microgrids.
  • Artificial intelligence (AI) supported decision making for microgrids.

Dr. Guodong Liu
Dr. Maximiliano F. Ferrari
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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

  • microgrids and distributed energy resources (DERs)
  • microgrid planning, operation, and control
  • grid resilience and reliability
  • market participation of microgrids
  • optimization for microgrids and DERs
  • modelling and simulation techniques for microgrids and DERs
  • networked microgrid interactions and controllers
  • regulatory and technoeconomic aspects of microgrids

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Published Papers (2 papers)

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Research

22 pages, 4762 KB  
Article
A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions
by Guodong Liu and Michael Starke
Energies 2026, 19(6), 1521; https://doi.org/10.3390/en19061521 - 19 Mar 2026
Viewed by 439
Abstract
With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the [...] Read more.
With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification. Full article
(This article belongs to the Special Issue Microgrids and Distributed Energy Resources: Planning, Design, Protection, and Operation)
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38 pages, 783 KB  
Article
A Review on Protection and Cybersecurity in Hybrid AC/DC Microgrids: Conventional Challenges and AI/ML Approaches
by Farzaneh Eslami, Manaswini Gangineni, Ali Ebrahimi, Menaka Rathnayake, Mihirkumar Patel and Olga Lavrova
Energies 2026, 19(3), 744; https://doi.org/10.3390/en19030744 - 30 Jan 2026
Viewed by 1074
Abstract
Hybrid AC/DC microgrids (HMGs) are increasingly recognized as a solution for the transition toward future energy systems because they can combine the efficiency of DC networks with an AC system. Despite these advantages, HMGs still have challenges in protection, cybersecurity, and reliability. Conventional [...] Read more.
Hybrid AC/DC microgrids (HMGs) are increasingly recognized as a solution for the transition toward future energy systems because they can combine the efficiency of DC networks with an AC system. Despite these advantages, HMGs still have challenges in protection, cybersecurity, and reliability. Conventional protection schemes often fail due to reduced fault currents and the dominance of power electronic converters in islanded or dynamically reconfigured topologies. At the same time, IEC 61850 protocols remain vulnerable to advanced cyberattacks such as Denial of Service (DoS), false data injection (FDIA), and man-in-the-middle (MITM), posing serious threats to the stability and operational security of intelligent power networks. Previous surveys have typically examined these challenges in isolation; however, this paper provides the first integrated review of HMG protection across three complementary dimensions: traditional protection schemes, cybersecurity threats, and artificial intelligence/machine learning (AI/ML)-based approaches. By analyzing more than 100 studies published between 2012 and 2024, we show that AI/ML methods in simulation environments can achieve detection accuracies of 95–98% with response times under 10 ms, while these values are case-specific and depend on the evaluation setting such as network scale, sampling configuration, noise levels, inverter control mode, and whether results are obtained in simulation, hardware in loop (HIL)/real-time digital simulator (RTDS), or field conditions. Nevertheless, the absence of standardized datasets and limited field validation remain key barriers to industrial adoption. Likewise, existing cybersecurity frameworks provide acceptable protection timing but lack resilience against emerging threats, while conventional methods underperform in clustered and islanded scenarios. Therefore, the future of HMG protection requires the integration of traditional schemes, resilient cybersecurity architectures, and explainable AI models, along with the development of benchmark datasets, hardware-in-the-loop validation, and implementation on platforms such as field-programmable gate array (FPGA) and μPMU. Full article
(This article belongs to the Special Issue Microgrids and Distributed Energy Resources: Planning, Design, Protection, and Operation)
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