Multi-scale modelling and optimization design of zeolite/NH3 working pairs, processes and networks for an integrated waste heat recovery and adsorption refrigeration system

Abundant and stable industrial low-grade waste heat (LGWH) creates opportunities for adsorption refrigeration (AR) using natural refrigerants to realize near-zero-carbon cooling applications. In this study, to achieve the simultaneous optimization design of working pairs, processes and networks, a superstructure of the integrated waste heat recovery network and adsorption refrigeration (WHRN-AR) system is extracted, and a multi-scale mixed integer non-linear programming (MINLP) optimization framework is formulated. At the microscopic scale, a general adsorption capacity prediction model based on the exponential decayed adsorption phase density distribution, shape selection adsorption concentration and zeolite's accessible volume is developed. At the mesoscale level, a comprehensive LGWH-driven AR thermodynamic process is constructed to effectively couple LGWH recovery and cold energy production. At the macroscale level, the energy network, including waste heat recovery, medium streams, pipes and pumps, is modelled to optimize the entire system. The WHRN-AR system and optimization framework are successfully applied to three practical industrial designs with different cooling specifications, in which the total annual cost (TAC) is minimized, 11 zeolite/NH3 working pairs, processes and networks are simultaneously optimized, and energy efficiencies are observed. In case 3, 4 working pairs can achieve a maximum cooling capacity (Qev) of 1800 kW at a desorption temperature of 343 K, and the integrated system reduces CO2 emissions by 76.6 %, lowing them to 42.2 kg/h compared to the electric refrigeration. Last, to represent the practical energy requirement for LGWH recovery, a power-based coefficient of performance for cooling (COPCP) is further introduced to analyze and compare the solution results.