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Energies
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Integration of Renewable Energy Technologies
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Integration of Renewable Energy Technologies

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (1 December 2021) | Viewed by 2453

Special Issue Editors

Prof. Dr. Kang Li

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Guest Editor
School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK
Interests: smart energy systems; microgrid; railway decarbonization; electric vehicles; battery management systems; energy management of industrial processes; control engineering; AI and machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Petros Aristidou

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Guest Editor
Cyprus University of Technology, Cyprus
Interests: Sustainable, secure, and resilient electric power systems
Dr. Jun Cao

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Guest Editor
School of Computer Science and Maths, Keele University, Staffordshire ST5 5BG, UK
Interests: Power system stability analysis and operation control, including wind power generation and energy storage systems; dynamic control and optimisation of multi-energy systems which include heat, gas and power networks

Special Issue Information

Dear Colleagues,

The world energy landscape is under major transformation due to significant penetration of clean and renewable generations. This Special Issue will present some latest progresses in technological development to support the global ambition to achieve 100% clean and renewable transitions by the mid of this century. It will cover enabling technologies for integration of renewable generations, from advanced control engineering, artificial intelligence, and big data analytics, to novel power electronics and energy storage systems. The special issue will also cover novel applications of these technologies in integration of renewables with transportation systems and intelligent manufacturing systems. 

Prof. Dr. Kang Li
Dr. Petros Aristidou
Dr. Jun Cao
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

  • Renewable integration
  • Advanced control
  • Artificial intelligence
  • Big data analytics
  • Power electronics
  • Energy storage systems
  • Transportation systems
  • Manufacturing systems

Published Papers (1 paper)

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Research

19 pages, 1040 KiB  
Article
A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids
by Meng Xia, Dajun Du, Minrui Fei, Xue Li and Taicheng Yang
Energies 2020, 13(11), 2940; https://doi.org/10.3390/en13112940 - 8 Jun 2020
Cited by 4 | Viewed by 1893
Abstract
To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible [...] Read more.
To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible region and validity of the attack vector. For the above drawbacks, this paper has three main contributions: (1) To construct the appropriate attack evading bad data detection (BDD), the feasible region of the attack vector is proved by projection transformation theory. The acquisition of the feasible region can help the defender to formulate the defense strategy; (2) an effective attack is proposed and the constraint of effectiveness is obtained using norm theory; (3) the domain of the state variations caused by the attack vector in the feasible region is calculated, while the singular value decomposition method is adopted. Finally, an attack vector is constructed based on l 0 -norm using OMP algorithms in the feasible domain. Simulation results confirm the feasibility and effectiveness of the proposed technique. Full article
(This article belongs to the Special Issue Integration of Renewable Energy Technologies)
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