Special Issue "Selected Papers from The International Conference on Condition Monitoring and Diagnosis 2018 (CMD2018)"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (15 January 2019).

Special Issue Editor

Dr. Ahmed Abu-Siada
Website
Guest Editor
Discipline of Electrical and Computer Engineering, Curtin University, Perth WA6102, Australia
Interests: fault diagnosis; asset management; power system analysis; control and quality; power electronics
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The main challenges facing the adoption of 100% renewable energy generation include widespread mix of utilities, individual investors and residential generation, employing cost effective energy storage technologies, adopting intelligent online monitoring and self-healing techniques, as well as secured communication protocols and smart control technologies. As such, worldwide, utilities are currently establishing smart grids with intelligent online monitoring and self-healing techniques. The scope of this Special Issue will include, but is not limited to, condition monitoring techniques for electrical assets within transmission and distribution networks, asset management and remaining life estimation, fault diagnosis, protection and self-healing techniques, etc.

Prof. Ahmed Abu Siada
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 papers will be 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 1800 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

  • condition monitoring for electrical apparatus
  • asset management
  • life cycle management
  • fault diagnosis
  • smart control technology
  • advanced communication protocols.

Published Papers (1 paper)

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Research

Open AccessArticle
Surface Discharge Analysis of High Voltage Glass Insulators Using Ultraviolet Pulse Voltage
Energies 2019, 12(2), 204; https://doi.org/10.3390/en12020204 - 09 Jan 2019
Cited by 1
Abstract
Surface discharges are precursors to flashover. To pre-empt the occurrence of flashover incidents, utility companies need to regularly monitor the condition of line insulators. Recent studies have shown that monitoring of UV signals emitted by surface discharges of insulators is a promising technique. [...] Read more.
Surface discharges are precursors to flashover. To pre-empt the occurrence of flashover incidents, utility companies need to regularly monitor the condition of line insulators. Recent studies have shown that monitoring of UV signals emitted by surface discharges of insulators is a promising technique. In this work, the UV signals’ time and frequency components of a set of contaminated and field-aged insulator under varying contamination levels and degrees of ageing were studied. Experimental result shows that a strong correlation exists between the discharge intensity levels under varying contamination levels and degree of ageing. As the contamination level increases, the discharge level of the insulator samples also intensifies, resulting in the increase of total harmonic distortion and fundamental frequencies. Total harmonic distortion and fundamental frequencies of the UV signals were employed to develop a technique based on artificial neural networks (ANNs) to classify the flashover prediction based on the discharge intensity levels of the insulator samples. The results of the ANN simulation showed 87% accuracy in the performance index. This study illustrates that the UV pulse detection method is a potential tool to monitor insulator surface conditions during service. Full article
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