On using particle swarm optimization to model a thermodynamically-balanced humidification dehumidification system with multiple extractions

Abstract

A humidification dehumidification system is a cost-effective thermal desalination system. It is well-suited for small-scale and off-grid applications to extract freshwater from seawater with minimum maintenance. The primary drawback of humidification dehumidification systems is the low thermal performance, and thermodynamic balancing using the extraction technique can substantially improve the system's performance. Unfortunately, the extraction model is not easy to converge due to its high nonlinearity, especially at a higher number of extractions. It is found that the system performance increases as the number of extractions increases up to Carnot performance at infinity extractions. In the literature, the highest number of extractions achieved is six. This study proposes an innovative model based on the particle-swarm minimization technique, which utilizes the balancing concept. The maximum number of extractions achieved using the proposed model is 22 at an enthalpy pinch of 0.1 kJ kgd-1, which shows that the proposed approach is promising, effective, and robust. The closest operating conditions to Carnot performance (99 %) are at an enthalpy pinch of 3 kJ kgd-1, minimum and maximum temperature of 40 °C and 80 °C, respectively, with seven extractions.