Yes / Multi-Stage Flash (MSF) desalination process has been used for decades for making fresh water from seawater and is the largest sector in desalination industries. In this work, dynamic optimisation of MSF desalination is carried out using powerful and robust dynamic simulation and optimisation software called gPROMS model builder. For a fixed freshwater demand, a number of optimal combinations of the factors such as heat transfer area, brine flow rate, cooling water flow rate, steam flow in brine heater, Top Brine Temperature, the number of stages, etc. are determined with the objective of maximising the performance ratio of the process (defined as the amount of fresh water produced per unit of energy input) considering the seasonal variations. An attempt has been made to develop an operational schedule for a particular day using dynamic optimisation.

Yes / Multistage Flash Desalination (MSF) is currently facing an enormous challenge in cutting of the cost: within the last few years, the MSF experienced a gradual decline in investment compared to other techniques of desalting water and thus, a significant improvement is required to remain attractive for capital investors. Improved process control is a cost effective approach to energy conservation and increased process profitability. In this work, a dynamic model is presented using gPROMS model builder to optimize and control MSF process. The Proportional Integral Derivative Controller (PID) and Generic Model Control (GMC) are used successfully to control the Top Brine Temperature (TBT) and the Brine Level (BL) in the last stage at different times of the year. The objectives of this study are: firstly, to obtain optimum TBT and BL profiles for four different seasons throughout the year by minimizing the Total Seasonal Operating Cost (TSOC); secondly, to track the optimum TBT and BL profiles using PID and GMC controllers with and without the presence of constraints; thirdly, to examine how both types of controllers handle the disturbances which occur in the plant. The results are promising and show that GMC controller provides better performance over conventional PID controller to handle a nonlinear system.

Yes / In this paper, a dynamic model of fouling is presented to predict the crystallization of calcium carbonate and magnesium hydroxide inside the condenser tubes of Once-Through Multistage Flash (MSF-OT) desalination process. The model considers the combination of kinetic and mass diffusion rates taking into account the effect of temperature, velocity and salinity of the seawater. The equations for seawater carbonate system are used to calculate the concentration of the seawater species. The effects of salinity and temperature on the solubility of calcium carbonate and magnesium hydroxide are also considered. The results reveal an increase in the fouling inside the tubes caused by crystallization of CaCO3 and Mg(OH)2 with increase in the stage temperature. The intake seawater temperature and the Top Brine Temperature (TBT) are varied to investigate their impact on the fouling process. The results show that the (TBT) has greater impact than the seawater temperature on increasing the fouling.

No

Desalination technology provides fresh water to the arid regions around the world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. Top Brine Temperature (TBT) (boiling point temperature of the feed seawater in the first stage of the process) is one of the many important parameters that affect optimal design and operation of MSF processes. For a given pressure, TBT is a function of Boiling Point Temperature (BPT) at zero salinity and Temperature Elevation (TE) due to salinity. Modelling plays an important role in simulation, optimisation and control of MSF processes and within the model, calculation of TE is therefore important for each stages (including the first stage, which determines the TBT). Firstly, in this work, several Neural Network (NN) based correlations for predicting TE are developed. It is found that the NN based correlations can predict the experimental TE very closely. Also predictions of TE by the NN based correlations were found to be good when compared to those obtained using the existing correlations from the literature. Secondly, a hybrid steady state MSF process model is developed using gPROMS modelling tool embedding the NN based correlation. gPROMS provides an easy and flexible platform to build a process flowsheet graphically. Here a Master Model connecting (automatically) the individual unit model (brine heater, stages, etc.) equations is developed which is used repeatedly during simulation and optimisation. The model is validated against published results. Seawater is the main source raw material for MSF processes and is subject to seasonal temperature variation. With fixed design the model is then used to study the effect of a number of parameters (e.g. seawater and steam temperature) on the freshwater production rate. It is observed that, the variation in the parameters affect the rate of production of fresh water. How the design and operation are to be adjusted to maintain a fixed demand of fresh water through out the year (with changing seawater temperature) is also investigated via repetitive simulation. Thirdly, with clear understanding of the interaction of design and operating parameters, simultaneous optimisation of design and operating parameters of MSF process is considered via the application MINLP technique within gPROMS. Two types of optimisation problems are considered: (a) For a fixed fresh water demand throughout the year, the external heat input (a measure of operating cost) to the process is minimised; (b) For different fresh water demand throughout the year and with seasonal variation of seawater temperature, the total annualised cost of desalination is minimised. It is found that seasonal variation in seawater temperature results in significant variation in design and some of the operating parameters but with minimum variation in process temperatures. The results also reveal the possibility of designing stand-alone flash stages which would offer flexible scheduling in terms of the connection of various units (to build up the process) and efficient maintenance of the units throughout the year as the weather condition changes. In addition, operation at low temperatures throughout the year will reduce design and operating costs in terms of low temperature materials of construction and reduced amount of anti-scaling and anti-corrosion agents. Finally, an attempt was made to develop a hybrid dynamic MSF process model incorporating NN based correlation for TE. The model was validated at steady state condition using the data from the literature. Dynamic simulation with step changes in seawater and steam temperature was carried out to match the predictions by the steady state model. Dynamic optimisation problem is then formulated for the MSF process, subjected to seawater temperature change (up and down) over a period of six hours, to maximise a performance ratio by optimising the brine heater steam temperature while maintaining a fixed water demand.

Among many seawater desalination processes, the multistage flash (MSF) desalination process is a major source of fresh water around the world. The most costly design and operation problem in seawater desalination is due to scale formation and corrosion problems. Fouling factor is one of the many important parameters that affect the operation of MSF processes. This thesis therefore focuses on determining the optimal design and operation strategy of MSF desalinations processes under fouling which will meet variable demand of freshwater. First, a steady state model of MSF is developed based on the basic laws of mass balance, energy balance, and heat transfer equations with supporting correlations for physical properties. gPROMS software is used to develop the model which is validated against the results reported in the literature. The model is then used in further investigations. Based on actual plant data, a simple dynamic fouling factor profile is developed which allows calculation of fouling factor at different time (season of the year). The role of changing brine heater fouling factor with varying seawater temperatures (during the year) on the plant performance and the monthly operating costs for fixed water demand and fixed top brine temperature are then studied. The total monthly operation cost of the process are minimised while the operating parameters such as make up, brine recycle flow rate and steam temperature are optimised. It was found that the seasonal variation in seawater temperature and brine heater fouling factor results in significant variations in the operating parameters and operating costs. The design and operation of the MSF process are optimized 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 for calculating dynamic freshwater demand/consumption profiles at different times of the day and season. Also, a simple polynomial based dynamic seawater temperature correlation is developed based on actual data. An intermediate storage tank between the plant and the client is considered. The MSF process model developed earlier is coupled with the dynamic model for the storage tank and is incorporated into the optimization framework within gPROMS. Four main seasons are considered in a year and for each season, with variable freshwater demand and seawater temperature, the operating parameters are optimized at discrete time intervals, while minimizing the total daily costs. The intermediate storage tank adds flexible scheduling and maintenance opportunity of individual flash stages and makes it possible to meet variable freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any-time during the day and for any season. Finally, the purity of freshwater coming from MSF desalination plants is very important when the water is used for industrial services such as feed of boiler to produce steam. In this work, for fixed water demand and top brine temperature, the effect of separation efficiency of demister with seasonal variation of seawater temperatures on the final purity of freshwater for both cleaned and fouled demister conditions is studied. It was found that the purity of freshwater is affected by the total number of stages. Also to maintain the purity of freshwater product, comparatively large number of flash stage is required for fouled demister.

yes / This work describes how the design and operation parameters of the Multi-Stage Flash (MSF) desalination process are optimised when the process is subject to variation in seawater temperature, fouling and freshwater demand throughout the day. A simple polynomial based dynamic seawater temperature and variable freshwater demand correlations are developed based on actual data which are incorporated in the MSF mathematical model using gPROMS models builder 3.0.3. In addition, a fouling model based on stage temperature is considered. The fouling and the effect of noncondensable gases are incorporated into the calculation of overall heat transfer co-efficient for condensers. Finally, an optimisation problem is developed where the total daily operating cost of the MSF process is minimised by optimising the design (no of stages) and the operating (seawater rejected flowrate and brine recycle flowrate) parameters.

Desalination technology provides fresh water to the arid regions around the world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. Top Brine Temperature (TBT) (boiling point temperature of the feed seawater in the first stage of the process) is one of the many important parameters that affect optimal design and operation of MSF processes. For a given pressure, TBT is a function of Boiling Point Temperature (BPT) at zero salinity and Temperature Elevation (TE) due to salinity. Modelling plays an important role in simulation, optimisation and control of MSF processes and within the model, calculation of TE is therefore important for each stages (including the first stage, which determines the TBT). Firstly, in this work, several Neural Network (NN) based correlations for predicting TE are developed. It is found that the NN based correlations can predict the experimental TE very closely. Also predictions of TE by the NN based correlations were found to be good when compared to those obtained using the existing correlations from the literature. Secondly, a hybrid steady state MSF process model is developed using gPROMS modelling tool embedding the NN based correlation. gPROMS provides an easy and flexible platform to build a process flowsheet graphically. Here a Master Model connecting (automatically) the individual unit model (brine heater, stages, etc.) equations is developed which is used repeatedly during simulation and optimisation. The model is validated against published results. Seawater is the main source raw material for MSF processes and is subject to seasonal temperature variation. With fixed design the model is then used to study the effect of a number of parameters (e.g. seawater and steam temperature) on the freshwater production rate. It is observed that, the variation in the parameters affect the rate of production of fresh water. How the design and operation are to be adjusted to maintain a fixed demand of fresh water through out the year (with changing seawater temperature) is also investigated via repetitive simulation. Thirdly, with clear understanding of the interaction of design and operating parameters, simultaneous optimisation of design and operating parameters of MSF process is considered via the application MINLP technique within gPROMS. Two types of optimisation problems are considered: (a) For a fixed fresh water demand throughout the year, the external heat input (a measure of operating cost) to the process is minimised; (b) For different fresh water demand throughout the year and with seasonal variation of seawater temperature, the total annualised cost of desalination is minimised. It is found that seasonal variation in seawater temperature results in significant variation in design and some of the operating parameters but with minimum variation in process temperatures. The results also reveal the possibility of designing stand-alone flash stages which would offer flexible scheduling in terms of the connection of various units (to build up the process) and efficient maintenance of the units throughout the year as the weather condition changes. In addition, operation at low temperatures throughout the year will reduce design and operating costs in terms of low temperature materials of construction and reduced amount of anti-scaling and anti-corrosion agents. Finally, an attempt was made to develop a hybrid dynamic MSF process model incorporating NN based correlation for TE. The model was validated at steady state condition using the data from the literature. Dynamic simulation with step changes in seawater and steam temperature was carried out to match the predictions by the steady state model. Dynamic optimisation problem is then formulated for the MSF process, subjected to seawater temperature change (up and down) over a period of six hours, to maximise a performance ratio by optimising the brine heater steam temperature while maintaining a fixed water demand.

Among many seawater desalination processes, the multistage flash (MSF) desalination process is a major source of fresh water around the world. The most costly design and operation problem in seawater desalination is due to scale formation and corrosion problems. Fouling factor is one of the many important parameters that affect the operation of MSF processes. This thesis therefore focuses on determining the optimal design and operation strategy of MSF desalinations processes under fouling which will meet variable demand of freshwater. First, a steady state model of MSF is developed based on the basic laws of mass balance, energy balance, and heat transfer equations with supporting correlations for physical properties. gPROMS software is used to develop the model which is validated against the results reported in the literature. The model is then used in further investigations. Based on actual plant data, a simple dynamic fouling factor profile is developed which allows calculation of fouling factor at different time (season of the year). The role of changing brine heater fouling factor with varying seawater temperatures (during the year) on the plant performance and the monthly operating costs for fixed water demand and fixed top brine temperature are then studied. The total monthly operation cost of the process are minimised while the operating parameters such as make up, brine recycle flow rate and steam temperature are optimised. It was found that the seasonal variation in seawater temperature and brine heater fouling factor results in significant variations in the operating parameters and operating costs. The design and operation of the MSF process are optimized 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 for calculating dynamic freshwater demand/consumption profiles at different times of the day and season. Also, a simple polynomial based dynamic seawater temperature correlation is developed based on actual data. An intermediate storage tank between the plant and the client is considered. The MSF process model developed earlier is coupled with the dynamic model for the storage tank and is incorporated into the optimization framework within gPROMS. Four main seasons are considered in a year and for each season, with variable freshwater demand and seawater temperature, the operating parameters are optimized at discrete time intervals, while minimizing the total daily costs. The intermediate storage tank adds flexible scheduling and maintenance opportunity of individual flash stages and makes it possible to meet variable freshwater demand with varying seawater temperatures without interrupting or fully shutting down the plant at any-time during the day and for any season. Finally, the purity of freshwater coming from MSF desalination plants is very important when the water is used for industrial services such as feed of boiler to produce steam. In this work, for fixed water demand and top brine temperature, the effect of separation efficiency of demister with seasonal variation of seawater temperatures on the final purity of freshwater for both cleaned and fouled demister conditions is studied. It was found that the purity of freshwater is affected by the total number of stages. Also to maintain the purity of freshwater product, comparatively large number of flash stage is required for fouled demister.