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Enhancing the resilience of urban energy systems: The role of artificial intelligence

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  • Jiang, Mingdong
  • Yu, Xinxin

Abstract

Global climate change threaten the balance between energy supply and demand considerably, resulting in increased focus on urban energy resilience. Meanwhile, the rapid development of artificial intelligence (AI) has had an inevitable impact on energy production and consumption. This study takes China's New Generation AI Innovative Development Pilot Zones as a quasi-natural experiment to explore the impact of AI on the resilience of urban energy systems (RUES). The results demonstrate that AI has a positive effect on RUES, which can be enhanced under lower economic growth targets, higher talent levels and tighter carbon emission constraints. AI significantly promotes the technological innovation in new energy and intelligent grid industries on the production side, which further enhance RUES. From the consumption side, AI affects RUES by influencing technological innovation in energy-efficient and high-end equipment manufacturing industries, and the effect on the latter is stronger. Heterogeneity tests reveal that the effects of AI are more pronounced for cities in China's central and western regions. The study enriches the research on AI and offers solutions for enhancing RUES.

Suggested Citation

  • Jiang, Mingdong & Yu, Xinxin, 2025. "Enhancing the resilience of urban energy systems: The role of artificial intelligence," Energy Economics, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:eneeco:v:144:y:2025:i:c:s0140988325001367
    DOI: 10.1016/j.eneco.2025.108313
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    4. Chen, Wei & Dai, Qin & Zheng, Yang & Wang, Chang-song, 2025. "Laissez-faire or policy intervention: How climate policy shape urban energy systems resilience," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 1929-1944.
    5. Gao, Xiangming & Ji, Xinliang & Wang, Rong & Yu, Jian, 2025. "The effect of artificial intelligence on energy transition: Evidence from China," Energy Economics, Elsevier, vol. 147(C).
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    7. Lin, Boqiang & Zhou, Dengli, 2025. "A new green transition driver: How does artificial intelligence affect the green economic efficiency," Energy, Elsevier, vol. 334(C).
    8. Kang, Shikang & Shang, Yu, 2025. "How artificial intelligence drives industrial digitalization and greening synergies? Evidence from China's AI innovation and development pilot zones," Technology in Society, Elsevier, vol. 83(C).

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