Energy optimization of reverse osmosis desalination systems in arid regions: A case study in Morocco

Reverse osmosis (RO) desalination has become an essential technology for providing freshwater in arid regions; however, its high energy demand remains a major operational and environmental concern. This study investigates the energy optimization of a full-scale RO desalination unit located in southern Morocco. Real operational data were collected and analyzed using a Python-based linear regression model to identify relationships between feed pressure, flow rate, conductivity, and specific energy consumption (SEC). Results show a strong correlation between energy use and operational scheduling, with an optimal operating window reducing SEC from 1.42 to 1.20 kWh m⁻³ and decreasing specific cost by approximately 0.015 USD m⁻³. Implementation of optimized control strategies led to an estimated 15 % reduction in energy consumption and 12 % decrease in CO₂ emissions. The proposed three-level methodology data acquisition, operational supervision, and AI-assisted optimization provides a replicable framework for improving the sustainability of desalination plants in energy-constrained arid environments.