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

Abstract 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.

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