Artificial Vision in Renewable Photovoltaic Systems: A Review and Vision of Specific Applications and Technologies
Source abstract
Abstract
Renewable energy resources have become extremely important in the current context of air pollution and the production of significant amounts of greenhouse gas emissions that contribute to global warming. One of the most important renewable energy sources that has shown the highest growth in recent years is photovoltaic (PV) systems. Due to their significance, this research presents a review of the applications in which artificial computer vision can be used in photovoltaic systems. From the results presented in this review, it will be evident that artificial vision can be applied for several different purposes. The advantages of using this technique will also be highlighted. Additionally, a systematic literature review is presented on the research associated with this topic. Through this review, it will be evident that many advanced algorithms related to image acquisition equipment have been proposed to ensure high reliability and fast results. This review does not merely focus on a specific topic or algorithms associated with image processing applied to photovoltaic systems. Rather, this work presents a broad and comprehensive review detailing all viable applications and associated computer vision technologies that can be deployed within these systems. Besides that, the review will clearly specify which work one is based on public datasets. To allow future reproducibility or research, the links to all public datasets utilized in the works based on them are included.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Photovoltaic System Optimization Techniques · Photovoltaic Systems and Sustainability · Solar Radiation and Photovoltaics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering (DEE), Escola Superior de Tecnologia de Setúbal (ESTSetúbal), Polytechnic University of Setúbal, Campus do IPS, Estefanilha, 2914-508 Setúbal, Portugal
Low Carbon Energy Conversion (LCEC), Department of Electrical, Energy and Automation Engineering (DEEEA), Instituto Superior de Engenharia de Lisboa (ISEL), Polytechnic University of Lisbon, Estrada de Benfica, 529, 1500-085 Lisboa, Portugal
Investigation and Development Center, Institute for Systems and Computer Engineering: Research and Development in Lisbon (INESC-ID), Rua Alves Redol, 9, 1000-029 Lisboa, Portugal
References (100+)
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