Energy efficiency and environmental assessment of cooling towers

Abstract

Cooling towers are becoming increasingly important as the demand for cooling facilities rises globally due to data centers, industrial cooling, and rising ambient temperatures. De-spite the prioritization for energy transition of heat recovery over cooling, cooling towers can offer an energy-efficient alternative to refrigeration through free cooling. At the same time, their electricity consumption, water usage, and environmental impacts require careful evalu-ation. However, prevailing environmental assessment methods lack comparability when it comes to quantifying the useful outputs of cooling towers to calculate their efficiency. This work introduces a methodological framework for identifying energy- and resource-efficient options during the selection, design, and operation of cooling towers. To systemati-cally identify the most feasible assessment methods, this thesis formulates comparison crite-ria and compares methods by means of a case study. Moreover, this work aims to delineate the physical and technical limitations of dry, wet, and hybrid cooling against waste-heat uti-lization and refrigeration. Furthermore, introducing a novel efficiency indicator satisfies the need for comparability across configurations and operational states. Based on a multi-criteria method comparison, a wet cooling tower in a data center was as-sessed using five methods: material flow analysis, life cycle inventory, life cycle assessment, exergy analysis, and life cycle exergy analysis. Moreover, data from 6730 cooling tower models of various types were collected and analyzed. Six types of package-type cooling tow-ers have been distinguished: dry, closed wet, open wet, and three types of hybrid systems, while defining one generalized system for all types enables comparability. The proposed efficiency indicator is the ratio between electricity demand and the thermodynamic mini-mum airflow. Subsequently, the indicator has been applied to a dataset of 6575 system mod-els and a year-long case study. Examining the dataset demonstrates the functional limits of cooling towers. For example, minimum outlet temperatures using evaporative cooling are up to 16 Kelvin lower than for dry cooling. Accordingly, the areas of application are highlighted depending on the follow-ing influencing factors: cooling tower approach, cooling temperatures, and outside condi-tions. Furthermore, the life cycle assessment of the case study stresses that electricity and water usage cause more than 97% of the environmental impacts in all the impact categories considered. Investigating the manufacturer data reveals ranges of electricity demand per heat load from 0.01 to 0.06 kWel/kWth, which allows for benchmarking and monitoring of existing plants. However, the specific electricity demand omits external and technical parameters. The method comparisons using the criteria metric and the case study also underscore the need for methodological refinement. This work therefore introduces a novel efficiency indi-cator and associated benchmarks that include normalization of ambient conditions and cool-ing demand. The indicator median demonstrates that dry cooling requires 8 times more min-imum airflow than evaporative cooling, which directly correlates to the fan power. At the same time, the physical and technical constraints are included, further underlining that the operating points of wet cooling towers would partly be unachievable with dry cooling. In conclusion, the challenge of normalizing dynamic technical and environmental conditions persists in prevailing methods. The method comparison leads to the conclusion that a materi-al flow analysis, including energy flows, mostly suffices as long as no impact assessment is required. The efficiency indicator and functional unit definition introduced here offer a reso-lution for identifying resource-saving potentials in cooling tower applications. The ineffi-ciency of the cooling tower can thereby be distinguished from adverse ambient conditions. Furthermore, the collected data provide benchmarks for various configurations. Overall, this thesis shall contribute to increasing the efficiency of cooling towers by means of comparing and refining existing environmental assessment methods. The thesis now ena-bles these methods to effectively identify and monitor efficiency potential with the aid of the novel efficiency indicator and dataset. On this basis, manufacturers and operators can im-plement target-aimed efficiency measures, as enhancing cooling tower efficiency is a minor yet important contribution to mitigating climate change and increasing sustainability.