China’s power industry faces critical challenges in balancing rapid economic growth with environmental sustainability amidst surging electricity demand from artificial intelligence (AI), cloud computing, and data centers. This study introduces the Data Center Energy Consumption Ratio (DCECR) as a quantitative metric and comprehensively evaluates China’s “East-to-West Computing” (ETWC) strategy through empirical analysis and predictive modeling. Using official data from 2018 to 2024 and advanced scenario analysis, we quantify that data center electricity consumption increased from 161 TWh (2.35% of total) in 2018, with projections indicating 277–500 TWh by 2030 depending on AI adoption rates and efficiency improvements. Our analysis reveals that China’s renewable energy capacity reached 1.889 billion kW (56% of total) by end-2024, providing foundation for sustainable data center expansion. Through comprehensive carbon emission modeling and economic analysis, we demonstrate that the ETWC strategy can achieve 25%–40% emission reduction per kWh by relocating computational loads to renewable-rich western regions, with potential annual carbon savings of 30–50 million tonnes CO 2 by 2030. Sensitivity analysis indicates that the reported 20.8–45 Mt CO 2 emission reduction range is subject to uncertainty from time-varying grid emission factors and key parameter assumptions, with load-shifting scenarios potentially yielding 14–52 Mt CO 2 savings depending on temporal alignment with renewable generation. This research provides evidence-based insights for policymakers and industry stakeholders to achieve balanced electricity development in China’s digital economy era.
(1303185) et al. (2026) studied this question.