Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-2663-2024
https://doi.org/10.5194/gmd-17-2663-2024
Model description paper
 | 
11 Apr 2024
Model description paper |  | 11 Apr 2024

Carbon Monitor Power-Simulators (CMP-SIM v1.0) across countries: a data-driven approach to simulate daily power generation

Léna Gurriaran, Yannig Goude, Katsumasa Tanaka, Biqing Zhu, Zhu Deng, Xuanren Song, and Philippe Ciais

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Cited articles

ACAPS: COVID-19 – Government Measures Dataset, ACAPS [data set], https://data.humdata.org/dataset/acaps-covid19-government-measures-dataset (last access: 5 January 2023), 2021. 
Ahmad, A.: Increase in frequency of nuclear power outages due to changing climates, Nature Energy, 6, 755, https://doi.org/10.1038/s41560-021-00849-y, 2021. 
Antoniadis, A., Gaucher, S., and Goude, Y.: Hierarchical transfer learning with applications for electricity load forecasting, arXiv [preprint], arXiv:2111.08512, 22 November 2022. 
Antonopoulos, I., Petropoulos, F., and Hatziargyriou, N.: Artificial intelligence and machine learning approaches to energy demand-side response: a systematic review, Renew. Sustain. Energ. Rev., 130, 109899, https://doi.org/10.1016/j.rser.2020.109899, 2020. 
Apley, D. W. and Zhu, J.: Visualizing the effects of predictor variables in black box supervised learning models, J. Roy. Stat. Soc. B, 82, 1059–1086, https://doi.org/10.1111/rssb.12377, 2020. 
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Short summary
We developed a data-driven model simulating daily regional power demand based on climate and socioeconomic variables. Our model was applied to eight countries or regions (Australia, Brazil, China, EU, India, Russia, South Africa, US), identifying influential factors and their relationship with power demand. Our findings highlight the significance of economic indicators in addition to temperature, showcasing country-specific variations. This research aids energy planning and emission reduction.
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