Integrating artificial intelligence in energy transition: A comprehensive review
The global energy transition, driven by the imperative to mitigate climate change, demands innovative solutions to address the technical, economic, and social challenges of decarbonization. Artificial intelligence (AI) has emerged as a transformative technology in this domain, offering tools to enha...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Energy Strategy Reviews |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211467X24003092 |
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| author | Qiang Wang Yuanfan Li Rongrong Li |
| author_facet | Qiang Wang Yuanfan Li Rongrong Li |
| author_sort | Qiang Wang |
| collection | DOAJ |
| description | The global energy transition, driven by the imperative to mitigate climate change, demands innovative solutions to address the technical, economic, and social challenges of decarbonization. Artificial intelligence (AI) has emerged as a transformative technology in this domain, offering tools to enhance each link in the energy system. This comprehensive review examines the current state of AI applications across key energy transition domains, including renewable energy deployment, energy efficiency, grid stability, and smart grid integration. The study identifies the pivotal role of AI in accelerating the adoption of intermittent renewable energy sources like solar and wind, managing demand-side dynamics with advanced forecasting and optimization, and enabling energy storage and distribution innovations such as vehicle-to-grid systems and hybrid energy solutions. It also highlights the potential of AI to advance energy system stability, address cybersecurity risks, and promote equitable and sustainable energy systems. Despite these advancements, challenges remain, including data quality and accessibility, system interoperability, scalability, and concerns regarding privacy and ethics. By synthesizing recent research and practical case studies, this paper provides insights into the opportunities and limitations of AI-driven energy transformation and offers strategic recommendations to guide future research, development, and policy-making. This review highlights that AI is not just a tool but a transformative catalyst, reshaping global energy systems into equitable, resilient, and sustainable frameworks, essential for achieving a net-zero future. |
| format | Article |
| id | doaj-art-6a3c567adcfc4ee692c0b59072921413 |
| institution | Kabale University |
| issn | 2211-467X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Strategy Reviews |
| spelling | doaj-art-6a3c567adcfc4ee692c0b590729214132025-01-05T04:27:56ZengElsevierEnergy Strategy Reviews2211-467X2025-01-0157101600Integrating artificial intelligence in energy transition: A comprehensive reviewQiang Wang0Yuanfan Li1Rongrong Li2Corresponding author. School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.; School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of ChinaSchool of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of ChinaCorresponding author. School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of China.; School of Economics and Management, China University of Petroleum (East China), Qingdao, 266580, People's Republic of ChinaThe global energy transition, driven by the imperative to mitigate climate change, demands innovative solutions to address the technical, economic, and social challenges of decarbonization. Artificial intelligence (AI) has emerged as a transformative technology in this domain, offering tools to enhance each link in the energy system. This comprehensive review examines the current state of AI applications across key energy transition domains, including renewable energy deployment, energy efficiency, grid stability, and smart grid integration. The study identifies the pivotal role of AI in accelerating the adoption of intermittent renewable energy sources like solar and wind, managing demand-side dynamics with advanced forecasting and optimization, and enabling energy storage and distribution innovations such as vehicle-to-grid systems and hybrid energy solutions. It also highlights the potential of AI to advance energy system stability, address cybersecurity risks, and promote equitable and sustainable energy systems. Despite these advancements, challenges remain, including data quality and accessibility, system interoperability, scalability, and concerns regarding privacy and ethics. By synthesizing recent research and practical case studies, this paper provides insights into the opportunities and limitations of AI-driven energy transformation and offers strategic recommendations to guide future research, development, and policy-making. This review highlights that AI is not just a tool but a transformative catalyst, reshaping global energy systems into equitable, resilient, and sustainable frameworks, essential for achieving a net-zero future.http://www.sciencedirect.com/science/article/pii/S2211467X24003092Artificial intelligenceEnergy transitionClean energy supplyDemand-side managementTechnological innovationSmart grids |
| spellingShingle | Qiang Wang Yuanfan Li Rongrong Li Integrating artificial intelligence in energy transition: A comprehensive review Energy Strategy Reviews Artificial intelligence Energy transition Clean energy supply Demand-side management Technological innovation Smart grids |
| title | Integrating artificial intelligence in energy transition: A comprehensive review |
| title_full | Integrating artificial intelligence in energy transition: A comprehensive review |
| title_fullStr | Integrating artificial intelligence in energy transition: A comprehensive review |
| title_full_unstemmed | Integrating artificial intelligence in energy transition: A comprehensive review |
| title_short | Integrating artificial intelligence in energy transition: A comprehensive review |
| title_sort | integrating artificial intelligence in energy transition a comprehensive review |
| topic | Artificial intelligence Energy transition Clean energy supply Demand-side management Technological innovation Smart grids |
| url | http://www.sciencedirect.com/science/article/pii/S2211467X24003092 |
| work_keys_str_mv | AT qiangwang integratingartificialintelligenceinenergytransitionacomprehensivereview AT yuanfanli integratingartificialintelligenceinenergytransitionacomprehensivereview AT rongrongli integratingartificialintelligenceinenergytransitionacomprehensivereview |