Multi-Stage Flash (MSF) desalination process is energy intensive and it is, therefore, essential to search for operating the plant at its optimum parameters which lead to reduction of energy consumption and consequently lower water production cost.
In this study, we used a solver optimization tool of Matlab software, for optimization of operating parameters of recirculation multi-stage flash (MSF-BR) desalting plant, taking in consideration the change of brine heater fouling factor and seasonal variation of seawater temperature. The solver uses genetic algorithms for solving multi-objective optimization problems. The operating variables over which optimization was carried out are the make-up flow rate, the cooling seawater flow rate, the brine recycle flow rate and the steam temperature. The optimization method and results analysis are based on actual plant data that includes 10 desalting units, each of 16 flashing stages and a nominal capacity of 26 700 m(3)/d.
Three objectives were considered in this optimization approach. The first is to maximize the fresh water capacity of the installation. The second is to minimize the heating steam flow rate in order to reduce the thermal energy consumption, and the third is to minimize the sum of flow rates of main pumps of the unit production in order to reduce the electric energy consumption. The expressions of the first two objective functions are obtained using response surface methodology (RSM). Solving the optimization problem has led to obtaining a set of Pareto optimal solutions, which defining various combinations of the optimal operating parameters of each MSF-BR desalination plant unit, and thus leading to optimal plant operation policy for the whole year.