Data-driven cooling tower optimization: A comprehensive analysis of energy savings using microsand filtration

Effective management of cooling tower systems requires thorough water quality control. While traditional chemical water treatment methods are currently the most prominent strategy, they are costly and may yield limited results when relied upon as the sole approach. Cross-flow microsand filtration systems offer an interesting alternative with the added benefit of potentially increasing evaporative cooling efficiency, thus saving energy. The focus of the study was to evaluate the effect of these filtration systems on cooling tower operation. A comprehensive data-driven analysis over two cooling seasons evaluated the energetic performance of a system equipped with and without an operating filter using continuous monitoring and statistical modeling. For similar environmental conditions, the coefficient of performance was on average 18% higher and was higher 63% of the time when the filter was operating, indicating superior heat transfer efficiency and significant energy savings. It was also 41% higher during periods of high cooling demand. Consequently, the filter and the system work more efficiently at high wet-bulb temperature and thermal load. Machine learning modeling suggested that operating the filter year-round could save between 5% and 13% of the energy bill, primarily during the cooling season. Continuous filter operation is essential as it mitigates biofouling, underscoring its long-term significance, even during periods of lower thermal loads. The results of this study are significant for sustainability, public health and hold broader implications for cooling tower management. Integrating filtration systems into cooling tower management therefore fosters sustainable practices by decreasing energy consumption and biofouling. This study presents a novel approach by demonstrating, for the first time, the significant impact of continuous cross-flow microsand filtration on cooling tower efficiency, both in terms of energy savings and biofouling mitigation. • Data-driven analysis of cooling towers with microsand filters was conducted. • The coefficient of performance was 18% higher on average with the filter. • The filter was 41% more efficient during periods of high cooling demand. • Machine learning suggested year-round filter use could save up to 13% on energy.