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Energies
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Cyber Security in Microgrids and Smart Grids—2nd Edition
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Cyber Security in Microgrids and Smart Grids—2nd Edition

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 August 2026 | Viewed by 2861

Editors

Dr. Sen Tan

E-Mail Website
Guest Editor
Energy Department, Aalborg University, 9220 Aalborg, Denmark
Interests: power management system; energy storage; security detection and cooperative control of microgrids; motor drive technologies
Special Issues, Collections and Topics in MDPI journals
Dr. José Matas

grade E-Mail Website
Guest Editor
Electric Engineering Department, Barcelona East School of Engineering (EEBE), Polytechnic University of Catalonia (UPC), Barcelona, Spain
Interests: power electronics; power quality; grid monitoring; renewable energy systems; nonlinear control of power electronics and microgrids
Special Issues, Collections and Topics in MDPI journals
Dr. Jorge El Mariachet

E-Mail Website
Guest Editor
Electrical Engineering Department, Polytechnic University of Catalonia (EEBE-UPC), Avinguda Eduard Maristany 16, Building A, Office A9.7, 08019 Barcelona, Spain
Interests: energy transition; energy management systems; renewable energies; biomass; hydrogen; microgrids; smart grid; power quality; power calculation; space microgrids; lunar microgrids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The modern electric grid heavily relies on the extensive deployment of communication and information technologies across multiple systems, connecting consumer premises to electricity distribution, transmission, and generation facilities. This transformation, known as grid digitization, has revolutionized grid automation and control systems, which enables better control, monitoring, and maintenance prediction of power grid components, facilitates the integration of distributed energy resources (DERs), and enhances customer services. However, cyberattacks pose significant risks to security and results in substantial economic losses.

Recent reports indicate a rise in the frequency and severity of cyberattacks targeting critical infrastructures, among which are conventional grid networks, smart grids and microgrids. This necessitates the development and implementation of innovative solutions by smart grid operators and electricity industry stakeholders to enhance grid resilience and the ability to detect, neutralize, and respond to cyberattacks.

This Special Issue is dedicated to presenting new concepts, methods, strategies, technologies, and implementation experiences in grid cybersecurity. The aim of this Issue is to establish clear procedures for cyberattack detection, mitigation, and correction, as well as cybersecurity in power systems planning, operation, and control.

The topics of interest include, but are not limited to:

  • Cyberattack detection and prevention techniques for microgrids or smart grids;
  • Mitigation and correction strategies for cyberattacks in microgrids or smart grids;
  • Cybersecurity considerations in microgrids or smart grids planning, operation, and control;
  • Application of blockchain and distributed ledger technologies for cybersecurity;
  • Protection schemes against coordinated cyber–physical attacks on microgrids or smart grids;
  • Secure communication protocols and authentication mechanisms for microgrids or smart grids;
  • Data analytics and information sharing for improved situational awareness in microgrids or smart grids;
  • Case studies and real-world implementation experiences of cyber-secure microgrids or smart grids;
  • Evaluation and testing methodologies for validating the effectiveness of cybersecurity solutions in microgrids or smart grids.

Dr. Sen Tan
Dr. José Matas
Dr. Jorge El Mariachet
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-anonymized 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

  • cybersecurity
  • microgrids
  • smart grids
  • cyberattack detection
  • distributed energy resources (DERs)
  • grid resilience

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Related Special Issue

Published Papers (3 papers)

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Research

18 pages, 1679 KB  
Article
A Novel MBSE-Driven Multi-Agent Framework for Enhancing Cyber-Physical Security in Smart Grids
by Yuantao Wang, Dingyu Yan, Xiyu Lu and Guohua Gao
Energies 2026, 19(10), 2420; https://doi.org/10.3390/en19102420 - 18 May 2026
Viewed by 321
Abstract
The paradigm shift towards highly distributed renewable energy integration has exponentially increased the topological complexity of Smart Grids. Consequently, the tight coupling between operational and information networks exposes these systems to severe cyber threats, including data breaches and malicious intrusions. Conventional centralized dispatch [...] Read more.
The paradigm shift towards highly distributed renewable energy integration has exponentially increased the topological complexity of Smart Grids. Consequently, the tight coupling between operational and information networks exposes these systems to severe cyber threats, including data breaches and malicious intrusions. Conventional centralized dispatch paradigms struggle with delayed responses, suboptimal coordination, and opaque design lifecycles. To overcome these limitations, this study introduces an innovative Multi-Agent System architecture engineered via Model-Based Systems Engineering methodologies. By employing SysML, we established a comprehensive digital twin encompassing system requirements, functional layouts, and logical boundaries. The proposed framework deploys a decentralized hierarchy of four specialized agents—perception, decision making, execution, and collaboration—to execute collaborative defense protocols strictly bounded by electrical safety constraints. Validation through IEEE 33-node distribution network simulations confirms that the framework rapidly identifies and mitigates Denial of Service, data falsification, and unauthorized device access. This MBSE-MAS paradigm demonstrates exceptional scalability and resilience, offering a highly practical blueprint for safeguarding next-generation power infrastructure. Full article
(This article belongs to the Special Issue Cyber Security in Microgrids and Smart Grids—2nd Edition)
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67 pages, 7998 KB  
Article
Neural Network Method for Detecting UDP Flood Attacks in Critical Infrastructure Microgrid Protection Systems with Law Enforcement Agencies’ Rapid Response
by Serhii Vladov, Łukasz Ścisło, Anatoliy Sachenko, Jan Krupiński, Victoria Vysotska, Maksym Korniienko, Oleh Uhrovetskyi, Vyacheslav Krykun, Kateryna Levchenko and Alina Sachenko
Energies 2026, 19(1), 209; https://doi.org/10.3390/en19010209 - 30 Dec 2025
Viewed by 925
Abstract
This article develops a hybrid neural network method for detecting UDP flooding in critical infrastructure microgrid protection systems. This method combines sequential statistics (CUSUM) and a multimodal convolutional 1D-CNN architecture with a composite scoring criterion. Input features are generated using packet-aggregated one-minute vectors [...] Read more.
This article develops a hybrid neural network method for detecting UDP flooding in critical infrastructure microgrid protection systems. This method combines sequential statistics (CUSUM) and a multimodal convolutional 1D-CNN architecture with a composite scoring criterion. Input features are generated using packet-aggregated one-minute vectors with metrics for packet count, average size, source entropy, and HHI concentration index, as well as compact sketches of top sources. To ensure forensically relevant incident recording, a greedy artefact selection policy based on the knapsack problem with a limited forensic buffer is implemented. The developed method is theoretically justified using a likelihood ratio criterion and adaptive threshold tuning, which ensures control over the false alarm probability. Experimental validation on traffic datasets demonstrated high efficiency, with an overall accuracy of 98.7%, a sensitivity of 97.4%, an average model inference time of 5.3 ms (2.5 times faster than its LSTM counterpart), a controlled FPR of 0.96%, and a reduction in asymptotic detection latency with an increase in intensity from 35 to 12 s. Moreover, with a storage budget of 10 MB, 28 priority bins were selected (their total size was 7.39 MB), ensuring the approximate preservation of 85% of the most informative packets for subsequent examination. This research contribution involves the creation of a ready-to-deploy, resource-efficient detector with low latency, explainable statistical layers, and a built-in mechanism for generating a standardized evidence package to facilitate rapid law enforcement response. Full article
(This article belongs to the Special Issue Cyber Security in Microgrids and Smart Grids—2nd Edition)
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17 pages, 1546 KB  
Article
Secure State Estimation with Asynchronous Measurements for Coordinated Cyber Attack Detection in Active Distribution Systems
by Md Musabbir Hossain and Wei Sun
Energies 2025, 18(21), 5604; https://doi.org/10.3390/en18215604 - 24 Oct 2025
Viewed by 888
Abstract
Coordinated cyber attacks tamper with measurement data to disrupt the situational awareness of active distribution systems. Various sensors report measurements asynchronously at different rates, which introduces challenges during state estimation. In addition, this forces cyber intruders to exert greater effort to compromise multiple [...] Read more.
Coordinated cyber attacks tamper with measurement data to disrupt the situational awareness of active distribution systems. Various sensors report measurements asynchronously at different rates, which introduces challenges during state estimation. In addition, this forces cyber intruders to exert greater effort to compromise multiple communication channels and launch coordinated attacks. Therefore, multi-channel and asynchronous measurements could be harnessed to develop more secure cyber defense strategies. In this paper, a prediction-correction-based multi-rate observer is designed to exploit the value of asynchronous measurements for the detection of coordinated false data injection (FDI) attacks. First, a time-function-dependent prediction-correction strategy is proposed to adjust the sampling interval for each sensor’s measurement. Then, an observer is designed based on the trade-off between estimation error and the optimal period of the most recent sampling instant, with the convergence of estimation error with the maximum permitted sampling interval. Moreover, the conditions for exponential stability are developed using the Lyapunov–Krasovskii functional technique. Next, a coordinated FDI attack detection strategy is developed based on the dual nonlinear minimization problem. The proposed attack detection and secure state estimation strategies are tested on the IEEE 13-node system. Simulation results show that these schemes are effective in enhancing attack detection based on asynchronous measurements or compromised data. Full article
(This article belongs to the Special Issue Cyber Security in Microgrids and Smart Grids—2nd Edition)
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