Artificial Intelligence for Next-Generation Solar Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".
Deadline for manuscript submissions: 25 February 2026 | Viewed by 10
Special Issue Editors
Interests: renewable energy; solar energy; artificial intelligence; machine learning; electroluminescent imaging
Special Issues, Collections and Topics in MDPI journals
Interests: solar energy; electroluminescent imaging; machine learning; photoluminescent imaging; solar energy materials
Special Issue Information
Dear Colleagues,
This Special Issue on “Artificial Intelligence for Next-Generation Solar Energy Systems” in Energies seeks to showcase the transformative potential of artificial intelligence (AI), machine learning (ML), and advanced computational intelligence in accelerating innovation across the solar energy sector. As global demand for clean and reliable power grows, solar energy is increasingly positioned at the forefront of the renewable transition. Yet, challenges remain in ensuring optimal performance, reducing costs, managing large-scale integration, and addressing operational uncertainties. AI offers powerful tools to address these challenges, providing new ways to design, monitor, and optimise solar energy systems with unprecedented accuracy and efficiency.
AI and ML techniques are reshaping solar energy research and practice at every stage of the value chain. Predictive modelling and forecasting approaches enable more accurate estimation of solar resource availability and system performance under varying environmental conditions. Intelligent control and optimisation frameworks are driving greater efficiency in power conversion, grid integration, and energy storage. Automated diagnostic tools, leveraging electroluminescence (EL), thermal, and multispectral imaging, are revolutionising fault detection and predictive maintenance in photovoltaic (PV) systems, significantly improving system reliability and lifetime yields.
This Special Issue invites original research articles and comprehensive reviews that push the frontier of AI-driven solar solutions. Key areas of interest include, but are not limited to, the following:
· AI and ML applications for PV fault detection, diagnosis, and performance optimisation.
· The integration of computer vision, deep learning, and multimodal frameworks for intelligent analysis of PV systems.
· Large language models (LLMs) and hybrid approaches combining physics-based modelling with data-driven learning for enhanced decision-making.
· Development of digital twins and real-time virtual representations of solar assets to improve design, monitoring, and predictive control.
· Explainable AI (XAI) approaches that promote transparency, trust, and interpretability in solar system decision-making.
· Edge and cloud-based AI systems enabling scalable, real-time analytics and management of distributed PV networks.
By bringing together cutting-edge contributions from researchers and practitioners, this Special Issue aims to highlight how AI can accelerate the deployment, efficiency, and sustainability of solar technologies worldwide. The editors particularly welcome interdisciplinary work that covers solar engineering, computer science, and data analytics, as well as case studies demonstrating the practical application of AI in real-world solar energy projects.
Dr. Mahmoud Dhimish
Dr. Gisele Alves Dos Reis Benatto
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
- artificial intelligence in solar energy
- photovoltaic diagnostics and monitoring
- electroluminescence and thermal image processing
- large language models (LLMs) for PV systems
- explainable AI (XAI) in solar energy
- digital twins and predictive modelling
- real-time AI-based PV fault detection
- intelligent energy forecasting and optimization
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