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NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient datamore » centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.« less

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 RTESmore » 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.« less

As quantum computers increase in size, the total energy used by a quantum data center, including the cooling, will become a greater concern. The cooling requirements of quantum computers, which operate at temperatures near absolute zero, are determined by computing system parameters, including the number and type of physical qubits, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. When combined with thermal system parameters such as cooling efficiency and cryostat heat transfer, the total energy use can be determined using a first-principles energy model. These models showmore » that cooling of quantum computers differs in two fundamental ways from conventional data centers: (1) the energy required for cooling is much greater than the energy required for computation, and (2) the cooling loads are sensitive to the computational architecture. The temperature requirements for different qubit types can change energy requirements by orders of magnitude. Power use and computational power, as quantified by quantum volume, are analytically correlated. Approaches are identified for minimizing energy use in integrated quantum systems relative to computational power. Furthermore, designing a sustainable quantum computer will require both efficient cooling and system design that minimizes cooling requirements.« less