Performance Optimization of Multi-Effect Distillation-Thermal Vapor Compression Desalination Using Genetic Algorithm

In the present study, a MATLAB computer code has been prepared for the simulation of a multi-effect desalination unit with thermal vapor compression. The first step is to obtain the parameters’ effect on the performance, including motive steam flow rate, temperatures, and dimensions of the system. Comparison of the present simulation results with the data reported for an actual desalination system shows a good consistency. System performance in two different cases of extracted secondary vapor from the last effect and all effects is investigated. It is observed that a higher performance ratio and specific heat transfer area are obtained by receiving secondary vapor from the last effect. Finally, the genetic algorithm is used to maximize the performance ratio of the system which is considered as the fitness function. Optimization results show that one can achieve a performance ratio higher than 17 and specific heat consumption less than 107 kJ/kg for a system with 10 effects.