The rising role of artificial intelligence in renewable energy development in China

Xiaojing Zhang, Khalid Khan, Xuefeng Shao, Camelia Oprean-Stan and Qian Zhang

Energy Economics, 2024, vol. 132, issue C

Abstract: Exploring the role of artificial intelligence (AI) in renewable energy (RE) development is pivotal for seizing technological opportunities and achieving climate objectives. This study uses wavelet analysis to examine the correlation between AI and RE in China. Our findings indicate a co-movement between AI and RE from 2014 to 2016 and a positive influence from AI to RE emerging from late 2018 to 2022. This suggests that AI acts as a facilitator for China's energy transition. Nevertheless, this effect is not constant; it becomes more pronounced with advancements in AI technology. These outcomes align with the techno-economic paradigms framework, implying that China can benefit from AI breakthroughs to accelerate its energy transition. Future policy efforts may focus on fostering collaboration among the government, businesses, and universities to promote AI and RE development.

Keywords: Artificial intelligence; Renewable energy; Energy transition; Wavelet analysis (search for similar items in EconPapers)
JEL-codes: O33 Q54 Q55 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:132:y:2024:i:c:s014098832400197x

DOI: 10.1016/j.eneco.2024.107489

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