Modelling, simulation, optimization and control of multistage flashing (MSF) desalination plants Part II: Optimization and control

Abstract

Applying optimization techniques to a multistage flash (MSF) plant can involve a number of areas such as the design of a new plant (process synthesis) or modification of an existing plant (through simulation). Optimizing the operation of MSF plants is still in its infancy. Limited efforts have been made earlier where semi-empirical equations were used to calculate the set-points. In contrast, several authors have developed optimization programs for general design purposes. These involved mostly less accurate models with a limited number of decision variables and less efficient strategies. The optimization of an MSF plant discussed in this paper deals with the steady-state optimization of the operation of an existing plant. In this case, the purpose of optimization is the adjustment of set-points in an optimal manner. The steam input for the MSF plant is considered as available in sufficient amount and with constant quality. Minimizing energy cost is suggested as an objective function. Other costs are assumed to be invariable. Under some conditions, it is possible to use a technical objective such as minimizing energy consumption or energy losses while satisfying energy and material balances of the process. An accurate process model is necessary for the set-point optimization. The equality and inequality constraints which bind decision variables are discussed. The problem considered is one of nonlinear optimization. The integration of optimization method and process model is discussed. Two algorithms are suggested, the Generalized Reduced Gradient method and the successive Quadratic Programming. The set-point optimization can be performed in two modes; off-line and on-line mode, the off-line mode is recommended for the test phase.