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Electronics
Special Issues
Anomaly Detection and Prevention in the Smart Grid
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Anomaly Detection and Prevention in the Smart Grid

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

Deadline for manuscript submissions: 15 April 2025 | Viewed by 2442

Special Issue Editors

Dr. Giovanni Gaggero

E-Mail Website
Guest Editor
Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture (DITEN), University of Genoa, 16145 Genoa, Italy
Interests: cybersecurity; industrial control system; smart grid; anomaly detection
Dr. Fabio Patrone

E-Mail Website
Guest Editor
Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture (DITEN), University of Genoa, 16145 Genoa, Italy
Interests: satellite; DTN networks; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Dr. Imed Ben Dhaou

E-Mail Website
Guest Editor
Department of Computing, University of Turku, 20500 Turku, Finland
Interests: VLSI; computer security; embedded systems for IoT; low-power design; approximate computing; DC microgrid; blockchain technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of smart grid technologies has revolutionized the way we generate, distribute, and consume electrical energy. As the smart grid continues to evolve, ensuring its security and stability has become of paramount importance. To address this critical aspect, we invite researchers and experts to contribute to this Special Issue, entitled “Anomaly Detection and Prevention in the Smart Grid” for MDPI Electronics. This Special Issue aims to bring together the latest research and developments in the field of anomaly detection and prevention in the context of smart grids. We welcome original contributions that explore novel methodologies, techniques, and solutions to safeguard the integrity and resilience of smart grid systems. Topics of interest include, but are not limited to, the following:

  • Advanced anomaly detection techniques: developments in machine learning, artificial intelligence, data mining, and statistical methods for the early identification of anomalies in smart grid data, such as power consumption patterns, communication traffic, and equipment behavior.
  • Cybersecurity and intrusion detection: novel approaches to detect and mitigate cyber threats, unauthorized access, and malicious activities targeting the smart grid infrastructure, including communication networks, data centers, and control systems.
  • Predictive maintenance: utilizing data analytics and predictive modeling to anticipate potential failures or anomalies in smart grid components, enabling efficient maintenance strategies and minimizing downtime.
  • Resilience and fault tolerance: strategies to enhance the robustness and fault tolerance of smart grid systems through adaptive control, reconfiguration, and self-healing mechanisms in response to anomalies or disturbances.
  • Integration of renewable energy sources: addressing challenges related to the integration of intermittent renewable energy sources into the smart grid, including anomaly detection and mitigation in distributed generation and storage systems.
  • Real-time monitoring and visualization: techniques for real-time monitoring, visualization, and situational awareness to enable rapid anomaly detection, response, and decision-making.

This Special Issue provides a platform to exchange ideas, share insights, and foster collaborations among researchers, practitioners, and policymakers in the field of smart grids and cybersecurity. We look forward to receiving your contributions to help fortify the smart grid infrastructure against emerging anomalies and threats.

For inquiries and submissions, please contact Dr. Giovanni Gaggero at [email protected].

Dr. Giovanni Battista Gaggero
Dr. Fabio Patrone
Dr. Imed Ben Dhaou
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 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. Electronics 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 2400 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

  • smart grid
  • anomaly detection
  • resilience
  • distributed energy resources
  • industrial control systems.

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

23 pages, 3006 KiB  
Article
Security Challenges in Energy Flexibility Markets: A Threat Modelling-Based Cyber-Security Analysis
by Zeeshan Afzal, Mathias Ekstedt, Nils Müller and Preetam Mukherjee
Electronics 2024, 13(22), 4522; https://doi.org/10.3390/electronics13224522 - 18 Nov 2024
Viewed by 363
Abstract
Flexibility markets are crucial for balancing the decentralised and renewable-driven energy landscape. This paper presents a security evaluation of a flexibility market system using a threat modelling approach. A reference architecture for a typical flexibility market system is proposed, and attack graph-driven simulations [...] Read more.
Flexibility markets are crucial for balancing the decentralised and renewable-driven energy landscape. This paper presents a security evaluation of a flexibility market system using a threat modelling approach. A reference architecture for a typical flexibility market system is proposed, and attack graph-driven simulations are performed to analyse potential attack pathways where malicious actors might infiltrate the system and the vulnerabilities they might exploit. Key findings include the identification of high-risk areas, such as the Internet links between market actors. To mitigate these risks, the paper proposes and evaluates multiple protection scenarios in reducing the identified attack vectors. The findings underline the importance of multi-layered security strategies to safeguard flexibility markets from increasingly sophisticated cyber threats. Full article
(This article belongs to the Special Issue Anomaly Detection and Prevention in the Smart Grid)
►▼ Show Figures

Figure 1

Figure 1
<p>Reference architecture model for a flexibility market.</p> Full article ">Figure 2
<p>Component description of the technical architecture.</p> Full article ">Figure 3
<p>Overview of coreLang [<a href="#B37-electronics-13-04522" class="html-bibr">37</a>].</p> Full article ">Figure 4
<p>Model view for FAO.</p> Full article ">Figure 5
<p>Attack path for full access on an SM application.</p> Full article ">Figure 6
<p>Attack path for accessing Core Zone LAN in Aggregator.</p> Full article ">Figure 7
<p>Attack path for DoS on SCADA Core Zone LAN.</p> Full article ">Figure 8
<p>Alternate attack path for DoS attack on SCADA Core Zone LAN.</p> Full article ">Figure 9
<p>Attack path for denying an RTU in a substation.</p> Full article ">Figure 10
<p>Attack path for gaining full access on an SM application.</p> Full article ">Figure 11
<p>Attack path for DoS on SCADA Core LAN using social engineering.</p> Full article ">Figure 12
<p>Attack path for hardware supply chain attack on SM.</p> Full article ">Figure 13
<p>Attack Path for Man in the Middle on an SM.</p> Full article ">Figure 14
<p>Supply chain attack on SCADA Core Zone.</p> Full article ">Figure 15
<p>Attack path for denying RTU in substations.</p> Full article ">
16 pages, 4120 KiB  
Article
Impact Analysis of Cyber Attacks against Energy Communities in Distribution Grids
by Afroz Mokarim, Giovanni Battista Gaggero and Mario Marchese
Electronics 2024, 13(9), 1709; https://doi.org/10.3390/electronics13091709 - 29 Apr 2024
Viewed by 1389
Abstract
With the advancement of regulations regarding the reduction in carbon emissions, renewable energy communities have come into the picture. However, many implications come with the installation of these communities from a cybersecurity point of view. The software platforms responsible for managing and controlling [...] Read more.
With the advancement of regulations regarding the reduction in carbon emissions, renewable energy communities have come into the picture. However, many implications come with the installation of these communities from a cybersecurity point of view. The software platforms responsible for managing and controlling them handle a lot of crucial information, and therefore, tampering with these data can lead to several impacts on the operation of these communities and, in turn, the power grid as well. This paper examines the plausible impacts that can be caused by altering certain parameters of the system that make it a potential cyber attack target. The analysis is done by observing how the grid responds to these manipulations for both low-voltage as well as medium-voltage systems. These systems are designed along with integrated energy communities and are implemented in MATLAB/Simulink R2022b software. The observations are made by plotting the grid voltage and power profiles in normal as well as attacked conditions. Full article
(This article belongs to the Special Issue Anomaly Detection and Prevention in the Smart Grid)
►▼ Show Figures

Figure 1

Figure 1
<p>Overall scheme of an energy community.</p> Full article ">Figure 2
<p>Attack model scheme.</p> Full article ">Figure 3
<p>IEEE European low-voltage test feeder (ELVTF).</p> Full article ">Figure 4
<p>Energy community scheme implemented in use case scenarios.</p> Full article ">Figure 5
<p>General load demand trend in Italy.</p> Full article ">Figure 6
<p>Single-line diagram of IEEE 69-bus system integrated with REC.</p> Full article ">Figure 7
<p>Voltage profile for an injection of 200 kW active power.</p> Full article ">Figure 8
<p>Voltage profile for an absorption of 200 kW active power.</p> Full article ">Figure 9
<p>Voltage profile for an injection of 400 kW active power.</p> Full article ">Figure 10
<p>Grid parameters for 2 MW active power injection: (<b>a</b>) p.u. voltage profiles of grid buses, (<b>b</b>) voltage and current waveforms at time of attack, and (<b>c</b>) total active and reactive power measured at bus 13.</p> Full article ">Figure 11
<p>Grid parameters for 2 MW active power absorption: (<b>a</b>) p.u. voltage profiles of grid buses, (<b>b</b>) voltage and current waveforms at time of attack, and (<b>c</b>) total active and reactive power measured at bus 13.</p> Full article ">Figure 12
<p>Grid parameters for 1 MVAr inductive reactive power injection: (<b>a</b>) p.u. voltage profiles of grid buses, (<b>b</b>) voltage and current waveforms at time of attack, and (<b>c</b>) total active and reactive power measured at bus 13.</p> Full article ">Figure 13
<p>Grid parameters for 1 MVAr capacitive reactive power injection: (<b>a</b>) p.u. voltage profiles of grid buses, (<b>b</b>) voltage and current waveforms at time of attack, and (<b>c</b>) total active and reactive power measured at bus 13.</p> Full article ">
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