This research introduces and optimises a grid-connected hybrid solar-wind system to power a reverse osmosis (RO) desalination unit in Bahrain. A model based on mixed-integer nonlinear programming (MINLP) optimisation framework is developed to design the system and evaluate its performance under Bahrain’s weather conditions. The design and operation of the RO process are optimised while considering fluctuations in water demands, changes in seawater temperature, and renewable energy variations throughout the day. The model determines the optimal operation strategy of flexible RO systems, the ideal number of wind turbines and photovoltaic (PV) modules, and the energy purchased from the grid to operate the RO plant and supply freshwater at a minimum cost. Hourly fluctuations in weather conditions are considered to achieve an efficient design. Two case studies of winter and summer conditions are presented in this research to accommodate different feed water and weather conditions. The levelized cost of water LCOW is found to be 0. 751/m³ in summer and 0. 648/m³ in winter, demonstrating the cost-effectiveness of the hybrid system, particularly during winter when wind energy is more abundant. The integration of solar and wind power reduces CO2 emissions by an estimated 4. 0 tons per day in January (winter) and 3. 0 tons per day in June (summer), further enhancing the environmental benefits of the proposed system. The optimisation model successfully determines that maintaining continuous operation of one membrane group while operating a second group intermittently is sufficient to meet freshwater demands, allowing the third group to remain available for maintenance. This operational strategy provides both production efficiency and maintenance flexibility while minimising total system costs.
Sassi et al. (2025) studied this question.