MILP optimization of the multi-heat pump waste heat recovery system integrated with full-free cooling data center through lake water

Shuyi Chen, Quan Zhang, John Zhai, Haowen Liu, Gang Chen, Jianjun Lei and Shuguang Liao

Energy, 2025, vol. 318, issue C

Abstract: Free cooling and waste heat recovery are vital and promising energy-saving technologies for the cooling system of data centers and the heating system of nearby buildings. The multi-heat pump system with different heat capacities is one of the most effective ways to extract heat from data centers, which need to match the cooling and heating demand in varied times and spaces. It will improve the performance of the integrated system, however, it raises their complexity and decreases the reliability. This study developed a comprehensive model from the computer room to heat consumers, mainly including information technology (IT) equipment heat dissipation, computer room air handler (CRAH), heat exchanger, water pump, heat pump, and thermal energy storage tank (TES). Based on mixed integer linear programming (MILP), an optimization control strategy was used to save energy without sacrificing the data center's reliability by regulating key operating parameters, such as the partial load ratio (PLR) of the heat pump, the ON-OFF mode, water pump's flow rate, and the heat storage and release mode of TES. Compared to the rule-based strategy, the MILP-based strategy improved the heat pump's daily average coefficient of performance (COP) and the heating system's energysaving rate by 1.19 and 15.11 % in winter, 1.21 and 14.68 % in the transition season, 1.13 and 12.91 % in summer, respectively. The related energy consumption of the cooling system in the above three seasons decreased by 3.78 %, 3.50 %, and 3.38 %, and the annual power usage effectiveness (PUE) reduced by 0.01. The annual energy-saving rate of the whole system was 8.12 %, and its global coefficient of performance (GCOP) increased from 9.96 to 10.85.

Keywords: Data center; Heat pump; Waste heat recovery; Mixed integer linear programming; Operation optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s0360544225004657

DOI: 10.1016/j.energy.2025.134823

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