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Energies
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Reliability, Security and Resiliency of Smart Grids
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Reliability, Security and Resiliency of Smart Grids

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

Deadline for manuscript submissions: closed (15 September 2022) | Viewed by 4924

Special Issue Editors

Prof. Dr. Mia Naeini

E-Mail Website
Guest Editor
Department of Electrical Engineering, University of South Florida, Tampa, FL 33620, USA
Interests: network science; graph signal processing; stochastic processes; data analytics; machine learning and system modeling with applications in cyber-physical-human systems with an emphasis on critical infrastructures and particularly smart grids and their reliability and security analyses
Prof. Dr. Yi-Ping Fang

E-Mail Website
Guest Editor
Risk and Resilience of Complex Systems, Laboratoire Génie Industriel, CentraleSupélec, Université Paris-Saclay, 3 Rue Joliot Curie, 91190 Gif-sur-Yvette, France
Interests: reliability theory; stochastic models; uncertainty quantification; stochastic and robust optimization; and complex network theory with application in risk; reliability and resilience assessment and optimization of cyber-physical systems (particularly smart grids and intelligent transportation systems)

Special Issue Information

Dear colleagues,

The Guest Editors would like to invite submissions to a Special Issue of Energies on the subject area of “Reliability, Security, and Resiliency of Smart Grids”. This Special Issue is a platform for researchers in the area of smart grid reliability, security, and resiliency to appraise recent theoretical, practical, and engineering developments in this field. Contributions related to identifying and studying new reliability and security challenges in smart grids as well as their joint considerations and new solutions and mechanisms to address such challenges and smart grids’ resiliency are welcome.

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

  • Power system reliability challenges;
  • Reliability and renewable energies;
  • Cascading failures and blackouts;
  • Data analytics and machine learning for reliability analysis;
  • Voltage stability and optimal line flow analysis for improved reliability;
  • Smart grid resilience;
  • Resilience through cross-domain (power/cyber) designs;
  • Cyber and physical attack resilience;
  • Cybersecurity for smart grids;
  • Cybersecurity of energy management systems;
  • Joint cyber and physical failures analyses;
  • Data analytics and machine learning for cybersecurity;
  • PMU-based sensing and control for reliability and security;
  • Graph-theoretic reliability and security analysis;
  • Wide area monitoring, situational awareness, and state estimation for smart grids reliability and security;
  • Event detection and locating in smart grids;
  • Securing Internet of Things (IoT) for energy systems;
  • SCADA and legacy system security;
  • Cyber-physical security for distributed energy resources.

Prof. Dr. Mia Naeini
Prof. Dr. Yi-Ping Fang
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. 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

  • smart Grids
  • security
  • reliability
  • resiliency
  • cyber and physical systems
  • data analytics
  • machine learning
  • situational awareness
  • stability
  • cascading failures

Published Papers (2 papers)

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Research

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17 pages, 579 KiB  
Article
Multi-Area Distributed State Estimation in Smart Grids Using Data-Driven Kalman Filters
by Md Jakir Hossain and Mia Naeini
Energies 2022, 15(19), 7105; https://doi.org/10.3390/en15197105 - 27 Sep 2022
Cited by 10 | Viewed by 1438
Abstract
Low-latency data processing is essential for wide-area monitoring of smart grids. Distributed and local data processing is a promising approach for enabling low-latency requirements and avoiding the large overhead of transferring large volumes of time-sensitive data to central processing units. State estimation in [...] Read more.
Low-latency data processing is essential for wide-area monitoring of smart grids. Distributed and local data processing is a promising approach for enabling low-latency requirements and avoiding the large overhead of transferring large volumes of time-sensitive data to central processing units. State estimation in power systems is one of the key functions in wide-area monitoring, which can greatly benefit from distributed data processing and improve real-time system monitoring. In this paper, data-driven Kalman filters have been used for multi-area distributed state estimation. The presented state estimation approaches are data-driven and model-independent. The design phase is offline and involves modeling multivariate time-series measurements from PMUs using linear and non-linear system identification techniques. The measurements of the phase angle, voltage, reactive and real power are used for next-step prediction of the state of the buses. The performance of the presented data-driven, distributed state estimation techniques are evaluated for various numbers of regions and modes of information sharing on the IEEE 118 test case system. Full article
(This article belongs to the Special Issue Reliability, Security and Resiliency of Smart Grids)
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Review

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29 pages, 1412 KiB  
Review
Resilience Quantification of Smart Distribution Networks—A Bird’s Eye View Perspective
by Youba Nait Belaid, Patrick Coudray, José Sanchez-Torres, Yi-Ping Fang, Zhiguo Zeng and Anne Barros
Energies 2021, 14(10), 2888; https://doi.org/10.3390/en14102888 - 17 May 2021
Cited by 6 | Viewed by 2627
Abstract
The introduction of pervasive telecommunication devices, in the scope of smart grids (SGs), has accentuated interest in the distribution network, which integrates a huge portion of new grid applications. High impact low probability (HILP) events, such as natural hazards, manmade errors, and cyber-attacks, [...] Read more.
The introduction of pervasive telecommunication devices, in the scope of smart grids (SGs), has accentuated interest in the distribution network, which integrates a huge portion of new grid applications. High impact low probability (HILP) events, such as natural hazards, manmade errors, and cyber-attacks, as well as the inherent fragility of the distribution grid have propelled the development of effective resilience tools and methods for the power distribution network (PDN) to avoid catastrophic infrastructural and economical losses. Multiple resilience evaluation frameworks are proposed in the literature in order to assist distribution system operators (DSOs) in managing their networks when faced with exogenous threats. We conduct detailed analysis of existing quantitative resilience studies in both electric and telecommunication domains of a PDN, focusing on event type, metrics, temporal phases, uncertainty, and critical load. Our work adopts the standpoint of a DSO, whose target is to identify feasible resilience assessment frameworks, which apply to pre-defined requirements in terms of resilience evaluation objectives (planning, reactive response, or simple assessment), time of evaluation, and available enhancement strategies. Finally, results and observations on selected works are presented, followed by discussion of identified challenges and opportunities. Full article
(This article belongs to the Special Issue Reliability, Security and Resiliency of Smart Grids)
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