Catalyzing Cooling Tower Efficiency: A Novel Energy Performance Indicator and Functional Unit including Climate and Cooling Demand Normalization

Paula M. Wenzel (), Eva Fensterle and Peter Radgen
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Paula M. Wenzel: Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, 70565 Stuttgart, Germany
Eva Fensterle: 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

Sustainability, 2023, vol. 15, issue 21, 1-24

Abstract: Energy and climate targets necessitate efficiency indicators to reflect resource-saving potentials. Prevailing indicators for cooling towers, however, often omit the effect of outside conditions. Hence, this study introduces an innovative indicator grounded in the energy efficiency ratio. Our proposed metric is the cost–benefit ratio between electricity demand and the thermodynamic minimum airflow . Thus, we call the novel indicator the airflow performance indicator . To validate its feasibility, we apply the indicator first to an extensive dataset encompassing 6575 cooling tower models and second to a year-long case study involving a data center’s wet cooling system. As a result, the energy performance indicator demonstrates that dry cooling requires eight times more minimum airflow at the median than evaporative cooling would, directly correlating to the fan power. Furthermore, efficiency benchmarks derived from the dataset of 6575 cooling tower models provide a comparative assessment of the case study. Defining the quantified benefit as minimum airflow additionally underscores the limitations of free cooling as the wet cooling system only partly covers the cooling demand, requiring chillers additionally. In conclusion, the indicator empowers the identification of energy-saving potentials in the selection, design, and operation of cooling towers. Moreover, the functional unit definition provides a foundation for future life cycle assessments of cooling towers, enhancing cooling tower efficiency and sustainability.

Keywords: key performance indicator; energy performance indicator; energy efficiency; environmental management; environmental impact; life cycle assessment; functional unit; physical optimum; free cooling; data center (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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