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Energies
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Fault Location and Management in Electrical Power Distribution Networks
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Fault Location and Management in Electrical Power Distribution Networks

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F2: Distributed Energy System".

Deadline for manuscript submissions: closed (23 August 2023) | Viewed by 9692

Special Issue Editor

Dr. Alireza Bahmanyar

E-Mail Website
Guest Editor
Department of Electrical Engineering and Computer Science Montefiore Institute, University of Liège, 4000 Liège, Belgium
Interests: distribution networks; smart grids; fault management ; security risk analysis; transient stability

Special Issue Information

Dear Colleagues,

These days, there is a considerable and continuous increase in the reliance of the functions of modern societies on electricity, calling for a much higher service quality than before. Considering that approximately 80% of customer power interruptions occur due to distribution faults, distribution system managers need to enable fast and efficient fault management to ensure service quality. The process usually includes fault location, isolation, and service restoration, each a challenging subject requiring the scientific investigation of the research community. The Guest Editor is inviting submissions to a Special Issue of Energies on the subject area of “Fault Location and Management in Electrical Power Distribution Networks”.

This Special Issue will deal with challenges and novel techniques for fault management in electrical power distribution networks, with a special focus on fault location methods. Topics of interest for publication include, but are not limited to:

  • Literature review, classification of techniques and their comparison;
  • Challenges in distribution fault management and in the practical application of fault location techniques;
  • Challenges and techniques for fault management for non-effectively grounded networks;
  • High impedance fault location in distribution networks;
  • Fault management and location techniques for active distribution networks;
  • Fault management in AC/DC Microgrids;
  • Innovative fault management and location techniques for smart grids;
  • Innovative application of artificial intelligence for fault management and location.

Dr. Alireza Bahmanyar
Guest Editor

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

  • Distribution network
  • Smart grid
  • Fault management
  • Fault location
  • Artificial intelligence

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Published Papers (3 papers)

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Research

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18 pages, 567 KiB  
Article
Fault Detection in Distribution Network with the Cauchy-M Estimate—RVFLN Method
by Cem Haydaroğlu and Bilal Gümüş
Energies 2023, 16(1), 252; https://doi.org/10.3390/en16010252 - 26 Dec 2022
Cited by 7 | Viewed by 2396
Abstract
Fault detection is an important issue in today’s distribution networks, the structure of which is becoming more complex. In this article, a data-based Cauchy distribution weighting M-estimate RVFLNs method is proposed for short-circuit fault detection in distribution networks. The proposed method detects short [...] Read more.
Fault detection is an important issue in today’s distribution networks, the structure of which is becoming more complex. In this article, a data-based Cauchy distribution weighting M-estimate RVFLNs method is proposed for short-circuit fault detection in distribution networks. The proposed method detects short circuits based on current and voltage measurements. In addition, noises were added to the data to ensure the robustness of the method. The performance of the method was examined in the RTDS RTS simulator using the IEEE 33-bus-bar system model with the help of real-time simulations. The success rate of the proposed method is between 98% and 100% for low-impedance (0 ohm) short-circuit faults, depending on the fault type. The success rate of high-impedance (100 ohm) short-circuit faults, which are more difficult to detect, is between 80% and 92%, depending on the fault type. Full article
(This article belongs to the Special Issue Fault Location and Management in Electrical Power Distribution Networks)
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19 pages, 579 KiB  
Article
Improving the Efficiency of Earth Fault Detection by Fault Current Passage Indicators in Medium-Voltage Compensated Overhead Networks
by Bartosz Olejnik and Beata Zięba
Energies 2022, 15(23), 9007; https://doi.org/10.3390/en15239007 - 28 Nov 2022
Cited by 2 | Viewed by 1923
Abstract
The article presents a method for detecting earth faults in a compensated medium-voltage network, which can be used especially in fault current passage indicators, but also in standard protection devices. The method is based on the adaptation process of the zero-sequence current protection [...] Read more.
The article presents a method for detecting earth faults in a compensated medium-voltage network, which can be used especially in fault current passage indicators, but also in standard protection devices. The method is based on the adaptation process of the zero-sequence current protection setting, with the adaptation factor depending on the current value of the zero-sequence voltage. In this article, a comparative analysis of the classical and adaptive zero-sequence current criterion is conducted, taking into account the errors of the measuring system. The results of simulations performed in the PSCad environment are also presented. For a representative set of example short circuits, it was shown that the effectiveness of the presented criterion can be more than 50% higher than that of the standard criteria, taking into account the range of detected transition resistances. A comparison of the proposed method with admittance criteria was also drawn, and it was shown that it is suitable for the detection of high-resistance earth faults. Full article
(This article belongs to the Special Issue Fault Location and Management in Electrical Power Distribution Networks)
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Review

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18 pages, 3610 KiB  
Review
Review on Artificial Intelligence-Based Fault Location Methods in Power Distribution Networks
by Hamed Rezapour, Sadegh Jamali and Alireza Bahmanyar
Energies 2023, 16(12), 4636; https://doi.org/10.3390/en16124636 - 11 Jun 2023
Cited by 14 | Viewed by 4274
Abstract
This paper provides a comprehensive and systematic review of fault localization methods based on artificial intelligence (AI) in power distribution networks described in the literature. The review is organized into several sections that cover different aspects of the methods proposed. It first discusses [...] Read more.
This paper provides a comprehensive and systematic review of fault localization methods based on artificial intelligence (AI) in power distribution networks described in the literature. The review is organized into several sections that cover different aspects of the methods proposed. It first discusses the advantages and disadvantages of various techniques used, including neural networks, fuzzy logic, and reinforcement learning. The paper then compares the types of input and output data generated by these algorithms. The review also analyzes the data-gathering systems, including the sensors and measurement equipment used to collect data for fault diagnosis. In addition, it discusses fault type and DG considerations, which, together with the data-gathering systems, determine the applicability range of the methods. Finally, the paper concludes with a discussion of future trends and research gaps in the field of AI-based fault location methods. Highlighting the advantages, limitations, and requirements of current AI-based methods, this review can serve the researchers working in the field of fault location in power systems to select the most appropriate method based on their distribution system and requirements, and to identify the key areas for future research. Full article
(This article belongs to the Special Issue Fault Location and Management in Electrical Power Distribution Networks)
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