Towards a digital twin approach – Experimental analysis and energy optimization of a multi-bed adsorption system

Abstract

An adsorption chiller system is one of the most promising technologies that utilize waste thermal energy to simultaneously produce cooling and potable water. However, the energy utilization optimization and detection of desiccant’s sorption capacity degradation are two unresolved issues that have severely impeded the development and commercial applications of adsorption chiller technologies. This study is pioneered to develop a digital twin platform specifically designed for an experimental four-bed two-evaporator adsorption chiller system prototype. Leveraging this platform, system monitoring, performance prediction, and optimization functions are achieved. Relying on the monitoring function, the digital twin can detect the capacity degradation of desiccant-coated heat exchangers. By employing the prediction and optimization functions, the application performance of the adsorption chiller system under varying ambient and load conditions can be simulated and optimized under real-time operating conditions. Additionally, this work projects a first-time experimental parametric study analysis for a four-bed two-evaporator adsorption chiller system prototype under a heat recovery scheme that considers fourteen operating parameters. Key results revealed that COPth reaches 0.68 when the cycle time is 2240 s. Case studies also showed that the adsorption chiller system can yield significant energy-saving performance for climatic conditions in Malaysia and Saudi Arabia. The proposed digital twin optimization method demonstrates that COPth is enhanced by 8.5 %, 9.5 %, and 8.5 %, respectively. In contrast to the conventional method, optimizing the adsorption chiller’s performance through the digital twin platform enables a reduction of the annual electricity consumption by up to 10.3 %.