Parametric analysis and design optimization of a fully open absorption heat pump for heat and water recovery of flue gas

The fully open absorption heat pump (FOAHP) is a novel approach for recovering and reusing waste heat and water from flue gas. By employing open-type towers in the absorption, regeneration, and condensation processes, the recovery efficiency is substantially enhanced while concurrently lowering system costs. However, as a complex system with multiparameter, nonlinear, and strongly coupled characteristics, research on system design is lacking, which hinders the widespread application of FOAHPs. To address this issue, this study proposes a model-based optimization framework to determine the design parameters of FOAHPs. A physical model of the system was established and utilized to obtain a matrix of system performance parameters for 6700 sets under a wide range of design parameter inputs. The dataset was then adopted to train and verify the data-driven model of the system, which reduced the computational time to 0.085126 s and provided a foundation for global optimization with multiple design parameters. Subsequently, a sensitivity analysis of the design parameters was conducted to elucidate their influence on the system characteristics. Based on data-driven model, the system's design parameters were globally optimized by combining genetic algorithm with the optimization objectives of the coefficient of performance (COP), flue gas recovery efficiency (η), and life cycle benefit (LCB). Results show that the optimized design parameters improved the COP and η of the system from 0.835 and 0.543 to 1.089 and 0.722, respectively, and the LCB from 71,309 USD to 149,843 USD, at which time the system heating capacity increases from 470,102 kWh to 840,182 kWh in one heating season. This study provides a foundational framework and data support for the global multi-objective optimization of the design parameters of FOAHPs.