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Free Cooling for Saving Energy: Technical Market Analysis of Dry, Wet, and Hybrid Cooling Based on Manufacturer Data

Author

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  • Paula M. Wenzel

    (Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 70565 Stuttgart, Germany)

  • Marc Mühlen

    (Faculty 4—Energy, Process- and Bio-Engineering, University of Stuttgart, 70569 Stuttgart, Germany)

  • Peter Radgen

    (Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 70565 Stuttgart, Germany)

Abstract

In light of energy and climate targets, free cooling unlocks a major resource-saving potential compared to refrigeration. To fill the knowledge gap in quantifying this saving potential, we aim to specify the physical and technical limits of cooling tower applications and provide comprehensive data on electricity and water consumption. For this purpose, we distinguish six types of package-type cooling towers: dry, closed wet, open wet, and three types of hybrid systems; defining one generalized system for all types enables comparability. Subsequently, we collect data from 6730 system models of 27 manufacturers, using technical information from data sheets and additional material. The analysis reveals, for example, specific ranges of electricity demand from 0.01 to 0.06 kW el /kW th and highlights influencing factors, including type and operating point. Refrigeration systems would consume approximately ten times more electricity per cooling capacity. Furthermore, the evaluation demonstrates the functional limits, for example, the minimum cooling temperatures. Minimum outlet temperatures using evaporative cooling are up to 16 K lower than for dry cooling. The collected data have crucial implications for designing and optimizing cooling systems, including potential analysis of free cooling and efficiency assessment of cooling towers in operation.

Suggested Citation

  • Paula M. Wenzel & Marc Mühlen & Peter Radgen, 2023. "Free Cooling for Saving Energy: Technical Market Analysis of Dry, Wet, and Hybrid Cooling Based on Manufacturer Data," Energies, MDPI, vol. 16(9), pages 1-27, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3661-:d:1131660
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    References listed on IDEAS

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    2. Qi, Xiaoni & Liu, Yongqi & Guo, Qianjian & Yu, Jie & Yu, Shanshan, 2016. "Performance prediction of seawater shower cooling towers," Energy, Elsevier, vol. 97(C), pages 435-443.
    3. Adrien Deroubaix & Inga Labuhn & Marie Camredon & Benjamin Gaubert & Paul-Arthur Monerie & Max Popp & Johanna Ramarohetra & Yohan Ruprich-Robert & Levi G. Silvers & Guillaume Siour, 2021. "Large uncertainties in trends of energy demand for heating and cooling under climate change," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
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    Cited by:

    1. Paula M. Wenzel & Eva Fensterle & Peter Radgen, 2023. "Catalyzing Cooling Tower Efficiency: A Novel Energy Performance Indicator and Functional Unit including Climate and Cooling Demand Normalization," Sustainability, MDPI, vol. 15(21), pages 1-24, October.

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