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Analyse des scénarios d'émissions de carbone des centres de données chinois sous l'objectif de neutralité carbone.

Carbon emission scenario analysis of data centers in China under the carbon neutrality target.

Auteurs : ZHOU F., WANG R., MA G.

Type d'article : Article de la RIF

Résumé

The low-carbon transformation of data centers is of great significance to achieve the goals of carbon peaking and carbon neutrality. This study compared and analyzed the overall situation of data centers in China. Based on China's CO2 emission and intensity targets in key years, the four variables of energy efficiency improvement rate, nonfossil energy consumption proportion, negative emission technology intensity, and waste energy utilization rate were introduced, and a net zero emission path model of data centers was established. Using scenario analysis to predict the total CO2 emissions and emission intensity from 2021 to 2060, three emission reduction path scenarios were obtained. Results showed that the energy consumption of data centers increased gradually, the carbon emissions first increased and then decreased, and the power usage effectiveness (PUE) of the data centers decreased gradually. The carbon peak time of the three scenarios is 2030, and the time for carbon neutrality is 2055, 2053, and 2051 in three scenarios. The data center industry should further improve the energy efficiency utilization rate, increase the proportion of nonfossil energy consumption, strengthen the technological innovation of carbon capture and storage, enhance the level of carbon sink, and optimize the utilization rate of waste energy.

Documents disponibles

Format PDF

Pages : 648-661

Disponible

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    20 €

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    Gratuit

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Détails

  • Titre original : Carbon emission scenario analysis of data centers in China under the carbon neutrality target.
  • Identifiant de la fiche : 30032887
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 168
  • Date d'édition : 12/2024
  • DOI : http://dx.doi.org/10.1016/j.ijrefrig.2024.09.017

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