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Energies
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Condition Monitoring of Power System Components 2024
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Condition Monitoring of Power System Components 2024

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 4276

Special Issue Editors

Dr. Muhammad Shafiq

E-Mail Website
Guest Editor
Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Interests: power systems and high voltage engineering; condition monitoring; insulation diagnosis; partial discharge; insulation breakdown; high-frequency sensor; measurement and instrumentation; data analysis; signal processing
Special Issues, Collections and Topics in MDPI journals
Dr. Ghulam Amjad Hussain

E-Mail Website
Guest Editor
College of Engineering and IT, University of Dubai, 800UOD（863）Dubai, United Arab Emirates
Interests: power systems; electrical machines; high voltage engineering; power system fault and transient analysis; protection and controls in modern microgrid and smart grid technologies; renewal energy systems and engineering education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Condition monitoring is considered a proactive approach to observe the changes or degradation of the important parameters of power system components that may lead to the malfunctioning, breakdown, or failure of the affected components if not attended to in a timely manner. Networks are growing, the number of components is increasing, and the operation of grids is changing. Various factors, such as the rapid proliferation of renewable sources, inclusion of hybrid network operations (AC and DC), and increased use of high-voltage power electronics, are pushing network components (power transformers, switchgears, insulators, and power lines) to operate under complex power supply conditions. Above all, improved reliability is becoming an elevated concern among power grid owners, especially considering the already installed aging components which are more vulnerable to additional operational changes. The changes to the grid demand efficient monitoring solutions, not only emphasizing the development of improved diagnostic techniques for the assessment of designed and operational parameters of the power components, but also underlining the need for enhanced measurement and data processing capabilities.  

This Special Issue invites papers presenting condition monitoring solutions for all grid voltage levels (low, medium, and high voltage) and addressing issues linked to the generation, transmission, distribution, and consumer-side components. Topics such as diagnosis techniques for component parameters, measurement systems, sensors and transducers, data acquisition and processing, onsite and remote sensing, offline and online monitoring, individual and integrated measurement capabilities, and other relevant aspects are welcome. We look forward to receiving your valuable work. 

Dr. Muhammad Shafiq
Dr. Ghulam Amjad Hussain
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

  • power system
  • grid operation
  • high voltage
  • medium voltage
  • low voltage
  • network component
  • monitoring
  • proactive diagnosis
  • measurement system
  • sensors and transducers
  • data processing
  • signal analysis
  • power lines (underground cables and overhead lines)
  • power transformer
  • switchgear
  • substations
  • insulators

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Published Papers (3 papers)

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Research

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27 pages, 4705 KiB  
Article
High-Precision Analysis Using μPMU Data for Smart Substations
by Kyung-Min Lee and Chul-Won Park
Energies 2024, 17(19), 4907; https://doi.org/10.3390/en17194907 - 30 Sep 2024
Viewed by 420
Abstract
This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea’s Yeonggwang substation, which is [...] Read more.
This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea’s Yeonggwang substation, which is connected to renewable energy sources (RESs), is introduced. Time-synchronized μPMU data are collected through the phasor data concentrator (PDC). A pre-processing program is implemented and utilized to integrate the raw data of each μPMU into a single comma-separated values (CSV) snapshot file based on the Timetag. After presenting the technique for identification and correction of event, duplicate, and spike bad data of μPMU, causal relationships are confirmed through the voltage and current fluctuations for a total of five states, such as T/L fault, tap-up, tap-down, generation, and generation shutdown. Additionally, the difference in active power between the T/L and the secondary side of the M.Tr is compared, and the fault ride through (FRT) regulations, when the fault in wind power generation (WP), etc., occurred, is analyzed. Finally, a statistical analysis, such as boxplot and kernel density, based on the instantaneous voltage fluctuation rate (IVFR) is conducted. As a result of the simulation evaluation, the proposed correction technique and precise analysis can accurately identify various phenomena in substations and reliably estimate causal relationships. Full article
(This article belongs to the Special Issue Condition Monitoring of Power System Components 2024)
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11 pages, 3354 KiB  
Article
Evaluation of the Optional Wideband Accuracy of Inductive Current Transformers in Accordance with the Standard IEC 61869-1 Ed.2
by Ernest Stano, Piotr Kaczmarek and Michal Kaczmarek
Energies 2023, 16(20), 7206; https://doi.org/10.3390/en16207206 - 23 Oct 2023
Viewed by 1144
Abstract
This paper presents the evaluation of tested inductive CTs’ accuracy for distorted current harmonics in accordance with the optional accuracy class WB1 introduced by the new edition of the standard IEC 61869-1 published in the year 2023. The tests were performed in compliance [...] Read more.
This paper presents the evaluation of tested inductive CTs’ accuracy for distorted current harmonics in accordance with the optional accuracy class WB1 introduced by the new edition of the standard IEC 61869-1 published in the year 2023. The tests were performed in compliance with the interpretation sheet IEC 61869-2:2012/ISH1:2022. Therefore, the resistive and the resistive–inductive loads of the secondary winding of tested inductive CTs were used, as this was required for the given test conditions. The results indicate that the units designed for the transformation of a sinusoidal current of a frequency of 50 Hz ensure the high wideband transformation accuracy of the distorted current harmonics, as demanded by the power quality monitoring and distorted electrical power and energy requirements. The key to this is proper design using modern magnetic material(s) for the magnetic core and its oversizing in relation to the requirements for a given accuracy class defined for the transformation of sinusoidal currents with a rated frequency. Both tested inductive CTs with a rated primary current RMS value equal to 300 A, class 0.2 and 0.5, ensured compliance with the requirements of the WB1 wideband accuracy class. Full article
(This article belongs to the Special Issue Condition Monitoring of Power System Components 2024)
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Review

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31 pages, 2308 KiB  
Review
A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques
by Haresh Kumar, Muhammad Shafiq, Kimmo Kauhaniemi and Mohammed Elmusrati
Energies 2024, 17(5), 1142; https://doi.org/10.3390/en17051142 - 28 Feb 2024
Cited by 7 | Viewed by 2100
Abstract
Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse [...] Read more.
Medium-voltage (MV) cables often experience a shortened lifespan attributed to insulation breakdown resulting from accelerated aging and anomalous operational and environmental stresses. While partial discharge (PD) measurements serve as valuable tools for assessing the insulation state, complexity arises from the presence of diverse discharge sources, making the evaluation of PD data challenging. The reliability of diagnostics for MV cables hinges on the precise interpretation of PD activity. To streamline the repair and maintenance of cables, it becomes crucial to discern and categorize PD types accurately. This paper presents a comprehensive review encompassing the realms of detection, feature extraction, artificial intelligence, and optimization techniques employed in the classification of PD signals/sources. Its exploration encompasses a variety of sensors utilized for PD detection, data processing methodologies for efficient feature extraction, optimization techniques dedicated to selecting optimal features, and artificial intelligence-based approaches for the classification of PD sources. This synthesized review not only serves as a valuable reference for researchers engaged in the application of methods for PD signal classification but also sheds light on potential avenues for future developments of techniques within the context of MV cables. Full article
(This article belongs to the Special Issue Condition Monitoring of Power System Components 2024)
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