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OPTIMIZATION OF REVERSE OSMOSIS DESALINATION SYSTEM USING GENETIC ALGORITHMS TECHNIQUE

In this paper, a methodology is developed for optimization of the reverse osmosis (RO) desalination system performance. The solution-diffusion model is used for the modeling. The optimization of RO systems is achieved by the genetic algorithms (GA) technique. The objective function is taken as the maximization of permeate volumetric flow rate. The optimization problem is to find the best pressure difference across the membrane which maximizes permeate volumetric flow rate and fulfill the permeate concentration constraint. The used constraint is that permeate concentration to be less than a desired value. A computer program was written in FORTRAN, GARO program (Genetic Algorithm Reverse Osmosis) to include the methodology. A binary-coded micro-genetic algorithm was linked with the equations describing the RO system performance. The methodology was tested on a real RO desalination plant in Nuweiba City, Egypt. Results from application of the GARO program on this plant have shown that the relationship between the operating pressure difference across membrane and permeate volumetric flow rate is approximately linear. The permeate concentration decreases with the increase in volumetric flow rate and the membrane pressure difference. The theoretical results obtained are seen to be in a good agreement with that experimentally obtained from the optimization program especially at higher flow rates.