Leveraging Artificial Intelligence for Affordable and Clean Energy: Advancing UN Sustainable Development Goal 7

Artificial Intelligence (AI) presents significant opportunities to accelerate progress towards the United Nations Sustainable Development Goal 7 (SDG 7) ensuring access to affordable, reliable, sustainable, and modern energy for all. This paper reviews major AI techniques, including machine learning, deep learning, hybrid models, optimization and control, and explainable AI, and their applications across energy system domains such as renewable energy forecasting, grid stability, energy efficiency, demand-side management, energy access, and transport electrification. We discuss enabling factors like data, infrastructure, markets, policies, and human factors and highlight the importance of multidisciplinary research. AI's potential for advancing clean energy access, synergistic SDG impacts, and energy justice is investigated. The paper emphasizes overarching principles of sustainability, resilience, and responsible AI development. With strategic collaboration between the AI and energy research communities, policymakers, and broader stakeholders, AI can help realize a clean energy future for all.

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Publication Details

Published
2024-08-16
DOI
https://doi.org/10.1109/besc64747.2024.10780659
Citations
3
Primary Topic
Global Energy and Sustainability Research
Type
article
Field-Weighted Citation Impact
0.31
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article

Leveraging Artificial Intelligence for Affordable and Clean Energy: Advancing UN Sustainable Development Goal 7

M. J. Hossain, Guandong Xu, Bavly Hanna, Xianzhi Wang
3 citations
Global Energy and Sustainability Research
0.31
article

Leveraging Artificial Intelligence for Affordable and Clean Energy: Advancing UN Sustainable Development Goal 7

M. J. Hossain, Guandong Xu, Bavly Hanna, Xianzhi Wang
article en
3 citations

Abstract

Artificial Intelligence (AI) presents significant opportunities to accelerate progress towards the United Nations Sustainable Development Goal 7 (SDG 7) ensuring access to affordable, reliable, sustainable, and modern energy for all. This paper reviews major AI techniques, including machine learning, deep learning, hybrid models, optimization and control, and explainable AI, and their applications across energy system domains such as renewable energy forecasting, grid stability, energy efficiency, demand-side management, energy access, and transport electrification. We discuss enabling factors like data, infrastructure, markets, policies, and human factors and highlight the importance of multidisciplinary research. AI's potential for advancing clean energy access, synergistic SDG impacts, and energy justice is investigated. The paper emphasizes overarching principles of sustainability, resilience, and responsible AI development. With strategic collaboration between the AI and energy research communities, policymakers, and broader stakeholders, AI can help realize a clean energy future for all.

University of Technology Sydney (AU)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Global Energy and Sustainability Research
0.31
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