Digital Twin Based Real Time Performance Prediction and Water Saving Strategy for Industrial Cooling Towers

Industrial cooling towers represent vital components in thermal power plants processing industries and HVAC networks balancing thermal rejection with water usage [۱]. However, traditional cooling tower operations lack dynamic adaptation to transient environmental conditions and variable thermal loads, resulting in suboptimal thermal efficiency and significant water loss via excessive evaporation and drift. This paper presents a novel Digital Twin (DT) framework engineered for the real time performance prediction and smart water saving control of industrial mechanical and induced draft cooling towers. By pairing real time physical sensor streams with a high fidelity computational modeling engine, the digital twin continuously determines the tower's thermal metrics including cooling range, approach efficiency, and effectiveness alongside transient mass balances for evaporative and windage water losses. Physical validation was performed using a fully instrumented induced draft cooling tower operating under varying hydraulic loadings (۱۲, ۱۸, and ۳۰ lpm) and bed configurations, including jute carpets with wire mesh and polystyrene ball matrices. The predictive engine, trained using real world operational plant data across diverse seasonal environments achieved an exceptional fit for inlet and outlet thermal profiles [۲]. Integrating this predictive capability with an automated water saving control logic allowed for real-time optimization of the L/G via variable speed fan and pump adjustments. The experimental and simulation results reveal that maximizing the contact area through structural packed beds yields a ۶۷% increase in thermal efficiency at higher volumetric flow rates. Concurrently, the digital twin driven control loop successfully balances exergy destruction against mass loss, achieving a significant reduction in make-up water consumption while strictly maintaining the required thermal cooling capacity.

کلیدواژه ها:

Digital Twin cooling tower ، Exergy efficiency ، evaporative cooling ، water saving strategy ، Liquid to gas ratio optimization ، Heating ، Ventilation ، and Air Conditioning