Differential evolution optimization of water gap membrane distillation process for water desalination

A theoretical model to predict the performance of the water gap membrane distillation process is developed to study the impacts of the operating parameters on the permeate flux, specific energy consumption, and water production cost. The MD model is integrated with a heuristic differential evolution (DE) optimization technique to optimize the operating variables of the process to maximize the permeate flux and minimize the energy consumption and production cost. The optimized parameters include the feed temperature, coolant temperature, feed flow rate, coolant flow rate, and water gap thickness. The optimization is carried out for both single and multi-objective functions. Results indicated that about 60% increase in the value of the highest permeate flux is obtained from the optimization model compared with the theoretical model of the MD process. Moreover, the lowest values of both energy consumption and production cost are reduced by about 31% and 38%, respectively, when the optimization is applied. For the multi-objective model, optimization results showed significant improvement and achieved an optimized permeate flux 51% higher than the maximum flux obtained from the MD model without optimization, with an optimized value of specific energy consumption as low as 876 kWh/m3.

Automated summary

By developing a theoretical model and integrating a heuristic differential evolution optimization technique, this study optimized the operating parameters of the water gap membrane distillation process to maximize the permeate flux and minimize energy consumption and production cost. The results showed a significant increase in efficiency and energy cost savings compared to the theoretical model.