Meeting Variable Freshwater Demand by Flexible Design and Operation of the Multistage Flash Desalination Process

Abstract

In this work, the design and operation of multistage flash (MSF) desalination processes are optimized and controlled in order to meet variable demands of freshwater with changing seawater temperature throughout the day and throughout the year. On the basis of actual data, the neural network (NN) technique has been used to develop a correlation which can be used for calculating dynamic freshwater demand/consumption profiles at different times of the day and season. A storage tank is linked to the freshwater line of the MSF process which helps avoiding dynamic changes in operating conditions of the process. A steady state process model for the MSF process coupled with a dynamic model for the storage tank is developed which is incorporated into the optimization framework within gPROMS modeling software. For a given design (process configuration), the operation parameters are optimized at discrete time intervals (based on the storage tank level which is monitored dynamically and maintained within a feasible limit) while the total daily cost is minimized.

Flexible Design and Operation of Multi-Stage Flash (MSF) Desalination Process Subject to Variable Fouling and Variable Freshwater Demand

“…These models are taken from Hawaidi and Mujtaba [9] and are presented here for the sake of completeness of the process model.…”

“…Most recently, [9] provided a study on the design and operation of the MSF process with constant fouling resistance in the brine heater only and variable seawater temperature and freshwater demand during a day and throughout the year. However, the dynamic variation in freshwater demand during the week days is not the same as weekends [10].…”

“…Also, the changing seawater temperature during the day will affect the stage temperature which will affect the fouling profile of the stages. Unlike Hawaidi and Mujtaba [9], we have proposed a fouling model [11,12] as a function of stage temperature which is incorporated into the MSF process model. In addition to fouling, the effect of non-condensable gases [13] on the condenser overall heat transfer co-efficient is built up in the process model.…”

“…In addition to fouling, the effect of non-condensable gases [13] on the condenser overall heat transfer co-efficient is built up in the process model. Like Hawaidi and Mujtaba [9], an intermediate storage tank between the plant and the client is considered to provide additional flexibility in operation and maintenance of the MSF process throughout the day. However, instead of a neural network based freshwater demand model, simple polynomial based dynamic freshwater demand correlation is developed using actual data from literature.…”

Generic Model Control (GMC) in Multistage Flash (MSF) Desalination

“…For fixed operating conditions, the MSF plants produce more fresh water in winter (low sea water temperature) than in summer. However, this production pattern goes counter to the demand of fresh water (Hawaidi and Mujtaba, 2011). Tanvir and Mujtaba (2008) minimised the operating cost by optimizing the number of stages based on seasonal variation of the sea water temperature.…”