LAPSE:2023.34751
Published Article
LAPSE:2023.34751
AI and Expert Insights for Sustainable Energy Future
April 28, 2023
This study presents an innovative framework for leveraging the potential of AI in energy systems through a multidimensional approach. Despite the increasing importance of sustainable energy systems in addressing global climate change, comprehensive frameworks for effectively integrating artificial intelligence (AI) and machine learning (ML) techniques into these systems are lacking. The challenge is to develop an innovative, multidimensional approach that evaluates the feasibility of integrating AI and ML into the energy landscape, to identify the most promising AI and ML techniques for energy systems, and to provide actionable insights for performance enhancements while remaining accessible to a varied audience across disciplines. This study also covers the domains where AI can augment contemporary and future energy systems. It also offers a novel framework without echoing established literature by employing a flexible and multicriteria methodology to rank energy systems based on their AI integration prospects. The research also delineates AI integration processes and technique categorizations for energy systems. The findings provide insight into attainable performance enhancements through AI integration and underscore the most promising AI and ML techniques for energy systems via a pioneering framework. This interdisciplinary research connects AI applications in energy and addresses a varied audience through an accessible methodology.
Record ID
Keywords
AI-compatible energy models, data-driven-based models, energy future landscape, energy system modeling, modern energy policies, parameter-based models, transforming energy models
Subject
Suggested Citation
Danish MSS. AI and Expert Insights for Sustainable Energy Future. (2023). LAPSE:2023.34751
Author Affiliations
Danish MSS: Energy Systems (Chubu Electric Power) Funded Research Division, IMaSS (Institute of Materials and Systems for Sustainability), Nagoya University, Furocho, Chikusa Ward, Nagoya 464-8601, Aichi, Japan [ORCID]
Journal Name
Energies
Volume
16
Issue
8
First Page
3309
Year
2023
Publication Date
2023-04-07
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16083309, Publication Type: Journal Article
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LAPSE:2023.34751
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doi:10.3390/en16083309
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[v1] (Original Submission)
Apr 28, 2023
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Apr 28, 2023
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