Editorial: AI-driven green revolution

Tianlong Liu , Ying Zheng

Green Energy and Resources ›› 2025, Vol. 3 ›› Issue (3) : 100144

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Green Energy and Resources ›› 2025, Vol. 3 ›› Issue (3) : 100144 DOI: 10.1016/j.gerr.2025.100144
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Editorial: AI-driven green revolution

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Tianlong Liu, Ying Zheng. Editorial: AI-driven green revolution. Green Energy and Resources, 2025, 3(3): 100144 DOI:10.1016/j.gerr.2025.100144

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References

[1]

Abdalla, A.N., Nazir, M.S., Tao, H., Cao, S., Ji, R., Jiang, M., Yao, L., 2021. Integration of energy storage system and renewable energy sources based on artificial intelligence: an overview. J. Energy Storage 40, 102811.

[2]

Boza, P., Evgeniou, T., 2021. Artificial intelligence to support the integration of variable renewable energy sources to the power system. Appl. Energy 290, 116754.

[3]

Duan, Y., Edwards, J.S., Dwivedi, Y.K., 2019. Artificial intelligence for decision making in the era of Big Data - evolution, challenges and research agenda. Int. J. Inf. Manag. 48, 63-71.

[4]

Dwivedi, Y.K., Hughes, L., Ismagilova, E., et al., 2021. Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manag. 57, 101994.

[5]

Ghahramani, M., Qiao, Y., Zhou, M.C., O'Hagan, A., Sweeney, J., 2020. AI-based modeling and data-driven evaluation for smart manufacturing processes. IEEE/CAA J. Automatica Sinica 7 (4), 1026-1037.

[6]

Huang, J., Koroteev, D.D., 2021. Artificial intelligence for planning of energy and waste management. Sustain. Energy Technol. Assessments 47, 101426.

[7]

Jarrahi, H.M., Memariani, A., Guha, S., 2023. The principles of data-centric AI. Commun. ACM 66 (8), 84-92.

[8]

Murshed, M.G.S., Murphy, C., Hou, D., Khan, N., Ananthanarayanan, G., Hussain, F., 2021. Machine learning at the network edge: a survey. ACM Comput. Surv. 54 (8), 1-37.

[9]

Priya, A.K., Devarajan, B., Alagumalai, A., Song, H., 2023. Artificial intelligence enabled carbon capture: a review. Sci. Total Environ. 886, 163913.

[10]

SaberiKamarposhti, M., Ng, K-W., Yadollahi, M., Kamyab, H., Cheng, J., Khorami, M., 2024. Cultivating a sustainable future in the artificial intelligence era: a comprehensive assessment of greenhouse gas emissions and removals in agriculture. Environ. Res. 250, 118528.

[11]

Salehi, S., Schmeink, A., 2023. Data-centric green artificial intelligence: a survey. IEEE Transact. Artific. Intellig. 5 (5), 1973-1989.

[12]

Soni, N., Singh, P.K., Mallick, S., Pandey, Y., Tiwari, S., Mishra, A., Tiwari, A., 2024. Advancing sustainable energy: exploring new frontiers and opportunities in the green transition. Advan. Sustain. Syst. 8 (10), 2400160.

[13]

van Wynsberghe, A., 2021. Sustainable AI: AI for sustainability and the sustainability of AI. AI Ethics 1, 213-218. https://doi.org/10.1007/s43681-021-00043-6.

[14]

Wahl, B., Cossy-Gantner, A., Germann, S., Schwalbe, N.R., 2018. Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Glob. Health 3 (4), e000798.

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