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Electronics
Special Issues
Reliability and Artificial Intelligence in Power Electronics
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Reliability and Artificial Intelligence in Power Electronics

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 15 August 2025 | Viewed by 878

Special Issue Editors

Dr. Xu Xu

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
Interests: power system optimization; renewable energy generation and integration; energy sharing and trading; application of artificial intelligence in smart grids
Dr. Chun Sing Lai

E-Mail Website
Guest Editor
Department of Electronic and Electrical Engineering, Brunel University, London UB8 3PH, UK
Interests: smart cities; electric vehicles; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Zhekang Dong

E-Mail Website
Guest Editor
School of Electronics & Information, Hangzhou Dianzi University, Hangzhou 310000, China
Interests: neuromorphic computing; artificial intelligence in power electronics; energy management
Special Issues, Collections and Topics in MDPI journals
Dr. Huayi Wu

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering and the Research Institute of Smart Energy, The Hong Kong Polytechnic University, Hong Kong 999077, China
Interests: artificial intelligence application in power system; renewable energy; power system operation

Special Issue Information

Dear Colleagues,

The increasing complexity and variability of power electronics systems present significant challenges to their reliability. Concurrently, the rising interest in Artificial Intelligence (AI) techniques offers promising new tools for design optimization, monitoring, control, and enhancing system life-cycle performance. This topic encapsulates the evolving performance requirements and methodologies in power electronics. This topic will delve into the reliability of power electronics components and systems, as well as the application of AI in power electronics, showcasing cutting-edge academic research and industry innovations. It will also address the challenges and opportunities inherent in this exciting field of research. The Special Issue on Reliability and Artificial Intelligence in Power Electronics invites articles on data gathering, analysis, and improvements in the reliable operation of power electronics, with applications to the smart grid.

Dr. Xu Xu
Dr. Chun Sing Lai
Dr. Zhekang Dong
Dr. Huayi Wu
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. Electronics 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 2400 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 electronics
  • artificial intelligence
  • reliability of power electronics components and systems

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Published Papers (1 paper)

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Research

15 pages, 2149 KiB  
Article
A Distributed Photovoltaic Aggregation Method Considering Photovoltaic Output Characteristics and Active Voltage Sensitivity
by Shaobo Yang, Xuekai Hu, Zengze Tu, Rui Yin, Yufei Zhang, Jiapeng Li, Lei Wang and Liang Meng
Electronics 2025, 14(5), 917; https://doi.org/10.3390/electronics14050917 - 25 Feb 2025
Viewed by 329
Abstract
With the large-scale integration of distributed photovoltaics, the morphology and characteristics of distribution networks are becoming increasingly complex. Accurate and efficient modeling of distributed photovoltaic aggregation is of significant importance for the planning and operation of new distribution networks. In this study, we [...] Read more.
With the large-scale integration of distributed photovoltaics, the morphology and characteristics of distribution networks are becoming increasingly complex. Accurate and efficient modeling of distributed photovoltaic aggregation is of significant importance for the planning and operation of new distribution networks. In this study, we first evaluated the similarity of different photovoltaic generation units by integrating the output characteristics of photovoltaic systems and the sensitivity indicators of grid connection points, proposing a distributed photovoltaic clustering method based on the K-means algorithm. Secondly, the output of the photovoltaic aggregation cluster was calculated using the capacity-weighting method. An equivalent network connecting various photovoltaic clusters was constructed based on the node elimination of the admittance matrix, and a modeling method for distributed photovoltaic aggregation was developed. Finally, the effectiveness of the method proposed in this paper was verified through the IEEE-33 test system. The results show that the distributed photovoltaics aggregation modeling method proposed in this paper can effectively simplify network topologies and improve the accuracy of the calculation results while also improving the efficiency of power flow analysis. Full article
(This article belongs to the Special Issue Reliability and Artificial Intelligence in Power Electronics)
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