Optimal operating conditions of a hybrid humidification-dehumidification and heat pump desalination system with multi-objective particle swarm algorithm

Hybrid humidification-dehumidification (HDH) and heat pump desalination system is a newly developed type of desalination plant. The hybrid system is entirely driven by electricity, and therefore, it is essential to investigate its optimal operation for certain optimization targets. In the present work, the multi-objective particle swarm optimization (MOPSO) algorithm is introduced to discover the optimal operation of a hybrid HDH and heat pump desalination system. Based on a mathematical model of the hybrid system, multi-objective optimization is performed to obtain the optimal air flow rate and seawater flow rate in terms of the maximum system production rate, minimum unit cost of fresh water and maximum gained output ratio (GOR). It can be concluded that the inlet air temperature has insignificant impact on the optimization objectives. As the inlet air humidity ratio increases within the concerned range, the increment of optimized system production rate as well as GOR are 3.79% and 4.15% respectively, and the decrement of fresh water cost is 8.50%. The variation tendencies of optimization objectives with increasing inlet seawater temperature are similar to those with increasing inlet air humidity ratio. It is also revealed that a near-linear relationship exists between the optimized cost and electricity price.