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A data center expansion scheme considering net-zero carbon operation: Optimization of geographical location, on-site renewable utilization and green certificate purchase.
- Source :
-
Socio-Economic Planning Sciences . Apr2024, Vol. 92, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Recently, more and more global attention has been paid to data centers' energy consumption and climate impact. Serving as the backbone of the digital world, the energy and carbon-intensive data centers have to find a green expansion way to fulfill their obligations in building a carbon-neutral society. Therefore, this paper proposes a net-zero carbon operation oriented data center expansion scheme for the central government to formulate incentive policies. The economic expansion model minimizes newly established data centers' investment and electricity consumption costs. Geographical location, on-site renewable utilization, and green certificate purchase are integrated and considered to achieve net-zero carbon operation by reducing total electricity consumption, increasing green power consumption, and offsetting inevitable carbon emissions. A case study in China is conducted, and results under different geographical location scenarios, power supply mix scenarios, and green certificates market scenarios are analyzed and compared. It is found that the zero-carbon operation of new data centers mainly relies on clean main-grid power, but a more decentralized layout and a provincial green certificate market can increase the contribution of on-site renewable energy. Lastly, four detailed policy implications for stimulating China's data center expansion are discussed. • A data center expansion scheme considering net-zero carbon operation is proposed. • Expansion model minimizes newly established data centers' expansion costs is built. • Three measures are integrated to achieve data centers' net-zero carbon operation. • Case study in China is conducted and core findings and key implications proposed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00380121
- Volume :
- 92
- Database :
- Academic Search Index
- Journal :
- Socio-Economic Planning Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 176036295
- Full Text :
- https://doi.org/10.1016/j.seps.2023.101789