Techno-economic performance of reservoir thermal energy storage for data center cooling system

Abstract

Electronic equipment in data centers generates heat during operation, which should be dissipated through a cooling system to prevent overheating and maintain optimal performance. Electricity consumption for the data center cooling system becomes significant as the demand for data-intensive services increases. Although various technologies have been developed and integrated into the data center cooling system, there are limited high-efficiency alternatives for data center cooling. In this study, we designed a reservoir thermal energy storage (RTES) system that stores cooling energy during winters and produces it during summers for data center cooling. We then demonstrated the techno-economic performance of the RTES incorporated with dry coolers and heat recovery for a year-round 5 MW cooling load. The RTES cooling production was reliable during the 20-year lifetime. We estimated the levelized cost of cooling as $5/MWh, significantly lower than $15/MWh for the base scenario where chillers and dry coolers supply the same cooling load without the RTES. We also estimated that the RTES-based cooling system annually avoids CO2 emissions up to 1488 tCO2e compared to the base case. These results highlight techno-economic feasibility and environmental benefits of the RTES and its potential to be deployed for various applications at large scales as well as for data center cooling.

Wencheng Jin

Assistant Professor of Petroleum Engineering

My research interests include novel rock breakage and fracture for subsurface resource recovery, data-driven and physics-based multiphysics modeling in porous and fractured media, and granular material flow characterization and modeling. My research provides solutions for energy/minerals recovery & storage, material handling, and GeoHazards prediction.