Multi-objective optimization for capacity matching and energy performance of heat-pump-driven liquid-desiccant air-conditioning system

Abstract

In heat-pump-driven liquid-desiccant (HPLD) air-conditioning systems, releasing condensing heat from heat pump to regenerator solution and exhaust air (i.e., capacity matching) is important for maintaining dehumidification performance, operational feasibility, and system stability. Therefore, this study optimizes capacity matching, especially focusing on releasing extra condensing heat, which has simply been assumed to be well-treated in previous studies, in conjunction with energy performance. With four design variables under various outdoor air conditions, a multi-objective optimization is conducted to simultaneously maximize system coefficient of performance (COP) and minimize a newly defined capacity-matching index of extra condenser. Pareto front, a set of optimum points, is obtained using a multi-objective genetic algorithm. Final optimum solutions are then determined and discussed based on a decision-making scenario. In optimization results, the regenerator air and solution flow rates should be respectively greater and lower than those of the absorber. The optimum temperature of absorber inlet solution is generally distributed at approximately 18 °C, while that of regenerator inlet solution is significantly influenced by the decision-making scenario. Finally, the system COP was maximally increased by 24 %, and the capacity-matching index of extra condenser was maximally decreased by 55 %, compared with each initial value.