- 3.2Impact Factor
- 7.3CiteScore
- 17 daysTime to First Decision
State-of-the-Art Artificial Intelligence Models for PV Fault Detection
This special issue belongs to the section “K: State-of-the-Art Energy Related Technologies“.
Special Issue Information
Dear Colleagues,
Even with the consistent growth in global photovoltaic (PV) capacity, the necessity for fault detection in PV systems has not been widely addressed regardless of its importance. Therefore, this Special Issue aims to solicit original and high-quality research articles related to the aforementioned topics. In particular, topics of interest include but are not limited to:
- PV fault detection and classification using mathematical and statistical-based algorithms;
- PV fault detection and classification using artificial intelligence (AI) models;
- Degradation estimation of PV systems;
- On-site characterization and inspection of PV systems (photoluminescence, thermography, electroluminescence).
Other relevant topics will also be considered.
Dr. Mahmoud Dhimish
Prof. Dr. Yihua Hu
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 250 words) can be sent to the Editorial Office for assessment.
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
- PV fault detection and classification using mathematical and statistical-based algorithms
- PV fault detection and classification using artificial intelligence (AI) models
- degradation estimation of PV systems
- on-site characterization and inspection of PV systems
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