Modeling and simulation of a solar-driven membrane distillation process utilizing an energy recovery system

This study presents a comprehensive approach to optimizing solar-powered membrane distillation (MD) by integrating experimental work, advanced multiplatform modeling, and intelligent system design. Novel polyvinylidene fluoride hollow fiber membranes were fabricated by incorporating superhydrophobic Silicalite-1 nanoparticles, enhancing permeability and selectivity. The mass and heat transfer phenomena in the vacuum MD unit were modeled using a Python-based framework, which was validated against experimental data. A key innovation lies in the dynamic coupling of this Python model with TRNSYS and HYSYS simulations, achieved via a custom 2-way interface, enabling real-time integration between solar thermal input and membrane performance. To mitigate solar intermittency and thermal losses, an energy recovery system was introduced, capturing waste heat to improve solar utilization efficiency. This hybrid system demonstrated a 57% solar energy utilization rate, delivering 36.3 GWh of thermal energy annually and yielding 1.15 million m³ of desalinated water. The work highlights how advanced modeling and cross-platform integration can significantly enhance the sustainability and efficiency of solar-driven MD technologies.