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Applied Computer Vision and Intelligent Computing for Electric Power Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 January 2026 | Viewed by 2

Special Issue Editors


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Guest Editor
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Interests: computer vision; operation situational awareness; abnormality monitoring of distributed generation equipment

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Guest Editor
Hainan Institute of Zhejiang University, Zhejiang University, Sanya 572025, China
Interests: electric power artificial intelligence; renewable energy utilization; nonlinear degradation behavior prediction
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Guest Editor
Hainan Institute of Zhejiang University, Zhejiang University, Sanya 572025, China
Interests: self optimal control of active distribution network; cyber-physical security with application in power system; survivability of power system under extreme conditions

Special Issue Information

Dear Colleagues,

With the acceleration of the global energy transition, power systems are undergoing profound transformations, marked by large-scale renewable energy integration, new energy access, and the tight coupling of energy–carbon markets. These changes introduce unprecedented complexity, characterized by dynamic uncertainties, abrupt fluctuations, and intricate inter-dependencies, necessitating breakthroughs in operational intelligence and resilient scheduling. Computer vision and artificial intelligence, with their powerful data processing capabilities and highly adaptive learning characteristics, have brought revolutionary improvements to the perception accuracy and decision-making efficiency of power systems. Furthermore, AI's data-driven insights and adaptive learning capabilities enhance the accuracy of power system situational awareness and operational decision-making, while computer vision enables real-time equipment inspection and anomaly detection through image-based analysis. However, in this process, challenges such as cross-domain collaboration of multi-source power data and the application of explainable AI algorithms need to be addressed. It is necessary to study multi-modal power data fusion mechanisms, human–machine collaboration and autonomous decision-making mechanisms in power systems, as well as automated monitoring and fault diagnosis technologies for electrical equipment. Through these technologies, we aim to provide technical references for the operation of power systems towards safer, greener, and more autonomous directions.

Dr. Yunfeng Yan
Dr. Xian-Bo Wang
Dr. Yulin Chen
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. Applied Sciences 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

  • electric power artificial intelligence
  • computer vision
  • multimodal data processing
  • smart grid optimization
  • large language models

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Published Papers

This special issue is now open for submission.
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