Guest Editors
Dr. Fatemeh Rezaei
Email: fatemeh.rezaei@unicampania.it
Affiliation: Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, Naples, 8103, Italy
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Research Interests: renewable energy planning, energy sustainability, energy waste management, environmental policy
Dr. Nima Rezazadeh
Email: nima.rezazadeh@unicampania.it
Affiliation: Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, Naples, 8103, Italy
Homepage:
Research Interests: machine learning application in energy engineering, anomaly detection, fault detection
Summary
The global push for energy security and sustainability has made renewable energy a cornerstone of modern policy and research. As the world confronts the challenges of climate change and dwindling fossil fuel reserves, the transition to clean energy sources is not just an option but a necessity. This shift requires comprehensive planning that integrates economic viability, environmental protection, and social equity. In this regard, this Special Issue aims to bring together cutting-edge research and interdisciplinary perspectives on the challenges and opportunities in the renewable energy sector. The scope includes but is not limited to, the development of intelligent energy systems, the creation of sustainable energy planning, proactive and predictive maintenance of renewable assets through Edge-AI and IoT integration, and neutralizing environmental and operational variabilities in monitoring systems of off-shore and on-shore renewable energy assets. We seek contributions that showcase novel methods, including renewable energy planning, machine learning and artificial intelligence, for addressing the complexities of renewable energy development.
Suggested themes include:
Policy and Socio-Economic Aspects: This includes studies on the effectiveness of different environmental policies, sustainable site planning of offshore and onshore renewable energies, the economic impacts of transitioning to renewable energy, and social equity issues related to energy access and sustainability.
Sustainable AI-Driven Condition Monitoring of Renewable Energy Assets: Exploring eco-efficient artificial intelligence models and algorithms that reduce computational cost while enabling real-time, accurate fault detection in renewable energy systems.
Neutralizing Environmental and Operational Variabilities in Intelligent Monitoring Systems: Investigating AI-powered feature extraction, domain adaptation, and signal compensation techniques to enhance monitoring performance and reliability under fluctuating environmental and operational conditions in renewable energy assets.
Keywords
renewable energy planning, site selection, environmental impact, GIS-based approach, proactive monitoring, preventive monitoring; artificial intelligence.
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