Various approaches in optimization of multi effects distillation desalination systems using a hybrid meta-heuristic optimization tool

Thermodynamic and thermoeconomic optimization of multi effects distillation (MED) desalination systems with thermo-vapor compressor (TVC) is performed. A complete thermodynamic modeling including the energy and exergy analysis is presented. An economic model of the system is developed according to the Total Revenue Requirement (TRR) method. The objective functions based on the thermodynamic and thermoeconomic analysis are developed. The proposed multi effects distillation system including six decision variables is considered for optimization. A hybrid stochastic/deterministic optimization approach developed based on a combination of genetic algorithm and simulated annealing (GA + SA) is utilized as an optimization method. This approach has been applied to minimize either the cost of the system product (fresh water) and/or maximizing the exergetic efficiency of the system. It is shown that the hybrid SA–GA method is able to obtain a better solution faster than a conventional genetic algorithm. Three optimization scenarios including thermodynamic single-objective, thermoeconomic single-objective and multi-objective optimizations are performed. In multi-objective optimization both thermodynamic and thermoeconomic objectives are considered, simultaneously. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from the available optimal points is presented here. The results obtained using the various optimization approaches are compared and discussed.