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Electronics
Special Issues
Resilience-Oriented Smart Grid Systems
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Resilience-Oriented Smart Grid Systems

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

Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 16556

Special Issue Editors

Dr. Muhammad Fahad Zia

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Guest Editor
Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, Brest, France
Interests: smart grids; microgrids; energy management; renewable energy; transactive energy
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mohamed Benbouzid

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Guest Editor
Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, 29238 Brest, France
Interests: fault detection and diagnosis; failure prognosis; cyberattack detection; fault-resilient control; machine learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Elhoussin Elbouchikhi

E-Mail Website
Guest Editor
ISEN Yncréa Ouest, Nantes Campus, LABISEN, 33, Avenue du Champ de Manoeuvre, 44470 Carquefou, France
Interests: electrical machine fault detection and diagnosis; fault-tolerant control; signal processing and statistics for power system monitoring; energy management systems in microgrids based on renewables; power electronics; microgrids; renewable energy; energy management systems; EV charging stations
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. S. M. Muyeen

E-Mail Website
Guest Editor
Department of Electrical Engineering, Qatar University, Doha 2713, Qatar
Interests: renewable energy and smart grids
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Natural disasters such as hurricanes, floods, earthquakes, and tornadoes, as well as cyber-attacks, cause severe damage to electric power system infrastructure, due to which unpredicted electricity blackouts happen for longer durations that may span several weeks. Such extreme events can be managed by designing resilient smart grid systems. Resilience is an integral part of electric power systems to provide continuous and reliable electric power supply to end users for achieving sustainable economic operation of the smart grid system. With the evolution and deployment of smart sensors along with advanced information and communication infrastructure, resilience can be effectively achieved in smart grid systems. These recent innovative developments have led to extensive research efforts to meet the demands for the development of resilience-efficient smart grid systems.

In this context, this Special Issue aims to be an open platform to share knowledge about progress and challenges in resilience-oriented smart grid systems against natural and cyber disasters. It particularly seeks original contributions regarding ideas, recent developments, or mature studies addressing both theoretical and experimental aspects.

Dr. Muhammad Fahad Zia
Prof. Mohamed Benbouzid
Dr. Elhoussin Elbouchikhi
Prof. S. M. Muyeen
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

  • Natural disasters
  • Cyber-attacks classification and detection
  • Natural disasters and component failure prediction
  • Resilience quantification metrics
  • Rapid service restoration
  • Smart grid self-healing
  • Smart metering and smart sensors
  • Smart electric transportation in smart grid resilience
  • Networked microgrids and smart grid resilience
  • Demand response
  • Signal processing techniques for smart grid monitoring
  • 5G communication and Internet of Things applications in monitoring and management of smart grids under extreme events

Published Papers (3 papers)

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Research

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18 pages, 1672 KiB  
Article
Optimal Sizing and Cost Minimization of Solar Photovoltaic Power System Considering Economical Perspectives and Net Metering Schemes
by Abdul Rauf, Ali T. Al-Awami, Mahmoud Kassas and Muhammad Khalid
Electronics 2021, 10(21), 2713; https://doi.org/10.3390/electronics10212713 - 07 Nov 2021
Cited by 10 | Viewed by 2826
Abstract
In this paper, economic feasibility of installing small-scale solar photovoltaic (PV) system is studied at the residential and commercial buildings from an end-user perspective. Based on given scenarios, the best sizing methodology of solar PV system installation has been proposed focusing primarily on [...] Read more.
In this paper, economic feasibility of installing small-scale solar photovoltaic (PV) system is studied at the residential and commercial buildings from an end-user perspective. Based on given scenarios, the best sizing methodology of solar PV system installation has been proposed focusing primarily on the minimum payback period under given (rooftop) area for solar PV installation by the customer. The strategy is demonstrated with the help of a case study using real-time monthly load profile data of residential as well as commercial load/customers and current market price for solar PVs and inverters. In addition, sensitivity analysis has also been carried out to examine the effectiveness of net metering scheme for fairly high participation from end users. Since Saudi Arabia’s Electricity and Co-generation Regulatory Authority (ECRA) has recently approved and published the net metering scheme for small-scale solar PV systems allowing end users to generate and export energy surplus to the utility grid, the proposed scheme has become vital and its practical significance is justified with figures and graphs obtained through computer simulations. Full article
(This article belongs to the Special Issue Resilience-Oriented Smart Grid Systems)
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Review

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20 pages, 966 KiB  
Review
Learning-Based Methods for Cyber Attacks Detection in IoT Systems: A Survey on Methods, Analysis, and Future Prospects
by Usman Inayat, Muhammad Fahad Zia, Sajid Mahmood, Haris M. Khalid and Mohamed Benbouzid
Electronics 2022, 11(9), 1502; https://doi.org/10.3390/electronics11091502 - 07 May 2022
Cited by 54 | Viewed by 7711
Abstract
Internet of Things (IoT) is a developing technology that provides the simplicity and benefits of exchanging data with other devices using the cloud or wireless networks. However, the changes and developments in the IoT environment are making IoT systems susceptible to cyber attacks [...] Read more.
Internet of Things (IoT) is a developing technology that provides the simplicity and benefits of exchanging data with other devices using the cloud or wireless networks. However, the changes and developments in the IoT environment are making IoT systems susceptible to cyber attacks which could possibly lead to malicious intrusions. The impacts of these intrusions could lead to physical and economical damages. This article primarily focuses on the IoT system/framework, the IoT, learning-based methods, and the difficulties faced by the IoT devices or systems after the occurrence of an attack. Learning-based methods are reviewed using different types of cyber attacks, such as denial-of-service (DoS), distributed denial-of-service (DDoS), probing, user-to-root (U2R), remote-to-local (R2L), botnet attack, spoofing, and man-in-the-middle (MITM) attacks. For learning-based methods, both machine and deep learning methods are presented and analyzed in relation to the detection of cyber attacks in IoT systems. A comprehensive list of publications to date in the literature is integrated to present a complete picture of various developments in this area. Finally, future research directions are also provided in the paper. Full article
(This article belongs to the Special Issue Resilience-Oriented Smart Grid Systems)
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40 pages, 1556 KiB  
Review
Overview of Signal Processing and Machine Learning for Smart Grid Condition Monitoring
by Elhoussin Elbouchikhi, Muhammad Fahad Zia, Mohamed Benbouzid and Soumia El Hani
Electronics 2021, 10(21), 2725; https://doi.org/10.3390/electronics10212725 - 08 Nov 2021
Cited by 22 | Viewed by 4328
Abstract
Nowadays, the main grid is facing several challenges related to the integration of renewable energy resources, deployment of grid-level energy storage devices, deployment of new usages such as the electric vehicle, massive usage of power electronic devices at different electric grid stages and [...] Read more.
Nowadays, the main grid is facing several challenges related to the integration of renewable energy resources, deployment of grid-level energy storage devices, deployment of new usages such as the electric vehicle, massive usage of power electronic devices at different electric grid stages and the inter-connection with microgrids and prosumers. To deal with these challenges, the concept of a smart, fault-tolerant, and self-healing power grid has emerged in the last few decades to move towards a more resilient and efficient global electrical network. The smart grid concept implies a bi-directional flow of power and information between all key energy players and requires smart information technologies, smart sensors, and low-latency communication devices. Moreover, with the increasing constraints, the power grid is subjected to several disturbances, which can evolve to a fault and, in some rare circumstances, to catastrophic failure. These disturbances include wiring issues, grounding, switching transients, load variations, and harmonics generation. These aspects justify the need for real-time condition monitoring of the power grid and its subsystems and the implementation of predictive maintenance tools. Hence, researchers in industry and academia are developing and implementing power systems monitoring approaches allowing pervasive and effective communication, fault diagnosis, disturbance classification and root cause identification. Specifically, a focus is placed on power quality monitoring using advanced signal processing and machine learning approaches for disturbances characterization. Even though this review paper is not exhaustive, it can be considered as a valuable guide for researchers and engineers who are interested in signal processing approaches and machine learning techniques for power system monitoring and grid-disturbance classification purposes. Full article
(This article belongs to the Special Issue Resilience-Oriented Smart Grid Systems)
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