Multi-Stage Flash Desalination Plants - Literature review Example

MULTI-STAGE FLASH DESALINATION PLANTS - LITERATURE REVIEW By Name Course Instructor Institution City/State Date Multi-Stage Flash Desalination Plants - Literature Review Abstract The population across the globe is growing rapidly, but the natural water resources are still constant. For some decades now, multistage flash desalination (MSF) and reverse osmosis (RO) have turned out to be a feasible, sustainable as well as economical source of fresh water across the globe. This literature review is motivated by the existence of detailed analysis and modelling of the MSF process dynamics. The majority of the existing studies about MSF plant have majored on the development of models, but only a few focuses on the performance data. Multi Stage Flash Distillation is widely utilised for sea water desalination, but because of large scale and complexity nature of such plants, there is a need to improve their operation reliability under heavy and continuous loads as well as their efficiency. Ways of improving their operation reliability have not been studied extensively, but this paper will review a few of the studies that have presented ways of optimising the MSF desalination plants. As mentioned in a number of studies, the operation sequence of the desalination plant has to be monitored and controlled. The aim of this literature review is to analyse the existing studies on multi-stage flash desalination plants. The objective of this literature review is to provide a recapitulation and comprehensive overview on multi-stage flash desalination plant from the past to present; thus, creating a sense of focus with regard to the direction that this research is headed. The literature review reviews, summarises as well as compares and contrasts different scholarly articles as and other secondary sources, which are directly associated with the present research. The need to improve the reliability of the MSF desalination in terms of costs and performance has resulted in the development of various models by different authors as reviewed in this literature review. Introduction Desalination can be described as a process where dissolved minerals are removed from salty water so as to generate fresh water. The literature review focuses on multistage flash (MSF), which is a thermal energy driven desalination process. The other desalination processes that use thermal energy include multi-effect distillation (MED) while those that use electrical energy include electrodialysis (ED) as well as reverse osmosis (RO). Basically, the process of Multistage flash (MSF) involves the multistage seawater distillation at low pressure and is a main process used in the industries for desalination. The MSF desalination focuses on evaporating the brine (the saline seawater) as well as condensing the produced vapour. In this case, flashing (pressure reduction) or boiling (heat addition) can be used to obtain the vapour. The process of evaporation, as well as condensation, is performed in stages at the closed chambers. Brine recycle system (MSF-BC) is the most common MSF desalination process (Al-Fulaij, 2011, p.20). This paper will be divided into; literature review where different methods and solutions will be discussed; analysis where the review main points will be made more explicit; and the discussions that will lead up to specific conclusions. Literature review According to Ismail (1998, p.145), there have been some rigorous automation and control applications of Multi-Stage Flash (MSF) plants that have recently shown some encouraging outcomes in finding modern control approaches to the reliability issue of MSF desalination. In view of this, Ismail (1998, p.145) conducted a survey to examine the efforts that have been made in using control and automation techniques to MSF Desalination plants as well as processes. In desalination plants, as mentioned by Ismail (1998, p.146), control systems are utilised to keep the plant parameters within acceptable design limits. The main variables of the process that have to be set so that the MSF desalination plant operation can be acceptable are: Brine recirculation flow, the top brine heater temperature (TBT), make-up flow, Sea water feed flow and temperature, the condensate level of the brine heater, and the last stage brine and distillate level. Citing a number of studies, Ismail (1998, p.146) asserts that MSF plants can be controlled through regulation of the main parameters using automatic control loops that are anchored on conventional proportional–integral–derivative controllers as well as with less manual operation. Therefore, he proposes an alternative microprocessor-based solution that is completely computerised. The proposed controllers according to Ismail (1998, p.154) exhibited superior performance and this provides evidence that new intelligent and advanced control systems may be used to solve a number of important issues such as parametric uncertainty, process complexity, disturbance accommodation as well as unmeasurable variables in the MSF desalination plants. Because the MSF desalination process has scores of output and input variables, Bodalal et al. (2010, p.395) agrees with Ismail (1998) that is hard to model the plant dynamic behaviour. Therefore, to design the control system that can efficiently control the process variables it is important to understand the dynamics. In his study, Bataineh (2016, p.48) noted that a thermal energy driven desalination plant can bring about best performance when the collectors are sloped along the north and south axis at a fixed angle equal towards the latitude. Another study similar to this is that by Said et al. (2013) that seeks to describe the optimisation of the parameters of the MSF desalination process design as well as operation. For this reason, Said et al. (2013, p.279) developed correlations of simple polynomial based dynamic seawater temperature as well as varying demand for freshwater anchored on the authentic data that was integrated into the MSF mathematical model by gPROMS ModelBuilder software. They optimised some of the MSF process operation parameters like recycle flow rate of brine and seawater at discrete time interval while the everyday total costs of operation were reduced. The results of optimisation exhibited an increase in the cost of operation but a reduction of the number of stages. Besides that, Said et al. (2013, p.294) noted that the utilisation of intermediate storage tank supplements MSF plants flexible scheduling so as to meet the freshwater demand variation with fluctuating temperatures of the seawater devoid of interrupting the plant. Still, cooling the feed brine mixture at the intake of the MSF plant has become more promising and viable (Alhazmy, 2014, p.1035). According to Alhazmy (2011, p.5232), a MSF with brine mixing as well as cooling (MSF-MC) is an improved MSF plant that provides improved yield and performance ratio. The MSF-MC plant sustains the basic advantages of low feed pumping power as well as chemical treatment of the MSF-BR. As mentioned by Alhazmy (2011, p.5232), low feed mass fraction facilitates in the reduction of the cooler size, cooling load, pumping power and the feed chemical treatment. He further noted that a yield improvement of 1.184 per cent was realised for every 10C reduction in the bottom temperature of the MSF plant. As cited by Gambier et al. (2002, p.128) a number of efforts have been made with the goal of improving the control performance through various advanced techniques. Although hybrid design techniques have been developed recently with improved results especially on the supervisory control area, Gambier et al. (2002, p.128) maintains that the applications in desalination are yet to be documented. Therefore, the authors used PID adaptive control for parameter scheduling together with hybrid automaton to facilitate the detection of the changes on the operating point as well as perform smoothed transfer from one point of operation to another. This is in the view of the fact that desalination plant requires its operation sequence to be controlled and monitored. On the other hand, Morsi et al. (2009, p.67) proposed the utilisation of the Human-Machine Interface (HMI) as well as Supervisory Control and Data Acquisition system (SCADA) for the MSF Brine Recirculation (MSF-BR) desalination plant. They noted that the SCADA system helped reduce the operation time. The control level that Blum and Marquardt (2000, p.2) used in their study is related to the implementation of set points that are computed at the higher control level either through a real-time optimization or off-line scheme. However, Ali et al. (1997, p.301) argues that the computational time is exceedingly long. Therefore, they suggest that there is a need for model reduction techniques so as to ensure that the advanced control strategies are efficiently implemented to the MSF plants. Analysis As evidenced in the literature review, MSF desalination plants can be categorised into two models, MSF-MC as well as (MSF-BC). Most of the reviewed studies have focussed on the optimisation and modelling of MSF desalination plants. Basically, the MSF models are solved using different software such as gPROMS. The software allows the model to be constructed in a hierarchical structure whereby the flashing stages are included in the lower hierarchy and are combined together at the higher hierarchy. As maintained by Said et al. (2013), the MSF desalination cost may be reduced through advances in operation and technology. A number of optimality objectives for MSF desalination processes as highlighted by Al-shayji et al. (2005, p.592) include the realisation of stable operation, energy consumption minimization, the equipment fouling avoidance as well as reducing the chemicals consumption. Basically, there are benefits and challenges associated with improving the design as well as the operation of MSF desalination plants through emphasising on the control aspects of dynamic and steady state simulations. Utilisation of computer modelling in addition to process simulation is economically beneficial. A number of reviewed studies have exhibited that dynamic simulation is powerful for the design of the MSF plant, control synthesis and analysis, plant optimization as well as safety studies. For simulation and automatic control purpose, for instance, Goto et al. (2008, p.15910) suggests that there is a need for dynamic modelling of MSF desalination plants. But still, the MSF processes are complex and large plants that need numerous simplifying assumptions so as to offer the first principle models for predicting as well as simulating their operation (Al-shayji et al., 2005, p.591). MSF plants have a number of challenges; for instance, Naser (2013, p.180) observed that areas around MSF plants were experiencing reduced biodiversity and the macrobenthic assemblages were severely impacted by the brine effluents because of salinities, high temperatures as well as heavy metal contaminants. Bleninger and Jirka (2008, p.595) also observed that discharge from the MSF desalination plants was negatively affecting the marine environment. Discussion MSF desalination as evidenced by the reviewed studies has proved to be an economical and feasible process that can help solve the problem of shortage in different areas across the globe. Basically, the increasing demands for freshwater have resulted in efforts to improve the performance of MSF desalination plants. According to some of the reviewed studies such as Ismail (1998) and Said et al. (2013) improved the performance of MSF plants can be evidenced by high rates of production, efficient economic performance and improved thermal operation. Still, as evidenced by Al-Fulaij (2011) different configurations of MSF plants, especially the MSF-MC and MSF-BR configuration have similar benefits in terms of reduced mass flow rate of the feed as well as minimised chemical treatment. Generally, the plant mass balance offers large amounts of seawater and the plants process large amount of energy; therefore, there is a need for optimisation. Moreover, the MSF plants normally dispose of significant quantities of brine after the desalination treatment. This has created the need for optimising the MSF plants operation as cited in the reviewed studies such as Al-shayji et al. (2005). In view of the reviewed studies, it is evidently that MSF desalination plants can benefit from greater reliability and stability, which can be achieved through remote maintenance functionality and optimisation to allow for greatest uptime. To fill the gap in the knowledge, there is need to integrate the process automation solution with the MSF desalination plants so as to leverage the comprehensive remote support which may bring about maximum throughput through operations optimisations. Computerising the MSF desalination process can help fill knowledge gaps in terms of reducing the costs of maintenance and simplify the whole maintenance process. Ways of improving MSF desalination plants efficiency and effectiveness have not been studied extensively; thus, creating knowledge gap. This can be filled by integrating MSF desalination plants with thermal compressor driven by steam, through dynamic modeling as well as simulation or software such as SCADA/HMI. Conclusions In conclusion, the literature review has provided a recapitulation and comprehensive overview on a multi-stage flash desalination plant. Most of the reviewed studies have proposed some models for the MFS desalination plants so as to improve reliability and performance. The issue of water has globally become a serious problem due to the factors such as rapid population growth, climate change, global warming, and so forth. Scores of industries have started focussing on the desalination technology capable of producing freshwater from seawater that is nearly inexhaustible. The existing studies that have documented the environmental challenges brought about by MSF desalination plants are very few. Optimum operation of the MFS plant offers reduced cost for desalination, which consequently offers maximised performance ratio. Optimisation mentioned by a number of the reviewed studies as results in low cost and ability to satisfy the demands for fresh water. References Al-Fulaij, H.F., 2011. Dynamic Modeling of Multi Stage Flash (MSF) Desalination Plant. Thesis. London: University College London. Alhazmy, M.M., 2011. Multi stage flash desalination plant with brineefeed mixing and cooling. Energy, vol. 36, p.5225-5232. Alhazmy, M.M., 2014. Economic and thermal feasibility of multi stage flash desalination plant with brineefeed mixing and cooling. Energy, vol. 76, pp.1029-35. Ali, E., Ajbar, A. & Alhumaizi, K., 1997. Robust control of industrial multi-stage flash desalination plants. Desalination, vol. 114, pp.289-302. Al-shayji, K.A., Al-wadyei, S. & Elkamel, A., 2005. Modelling and optimization of a multistage flash desalination process. Engineering Optimization, vol. 37, no. 6, pp.591-607. Bataineh, K.M., 2016. Multi-effect desalination plant combined with thermal compressor driven by steam generated by solar energy. Desalination, vol. 385, pp.39–52. Bleninger, T. & Jirka, G.H., 2008. Modelling and environmentally sound management of brine discharges from desalination plants. Desalination, vol. 221, pp.585–97. Blum, J. & Marquardt, W., 2000. The need for multivariable control in MSF desalination plants. In Darwish, M. & AlGobaisi, D. Encyclopedia of Desalination and Water Resources. Oxford, UK: EOLSS publishers. pp.1-25. Bodalal, A.S., Abdul_Mounem, S.A. & Salama, H.S., 2010. Dynamic Modeling and Simulation of MSF Desalination Plants. Jordan Journal of Mechanical and Industrial Engineering, vol. 4, no. 3, pp.394 - 403. Gambier, A., Fertig, M. & Badreddin, E., 2002. Hybrid Supervisory Control Of The Brine Heater For Multi Stage Flash Desalination Plants. In 15th Triennial World Congress. Barcelona, Spain, 2002. Goto, S. et al., 2008. A Simulation Model of Spray Flash Desalination System. In 17th IFAC World Congress. Seoul, Korea, 2008. Ismail, A., 1998. Control of multi-stage flash desalination plants: A survey. Desalination, vol. 116, pp.145-56. Morsi, I., Deeb, M.E. & Zawawi, A.E., 2009. SCADA/HMI Development for a Multi Stage Desalination Plant. In 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns. Alexandria, Egypt, 2009. IEEE. Naser, H.A., 2013. Effects of Multi-Stage Flash and Reverse Osmosis Desalinations on Benthic Assemblages in Bahrain, Arabian Gulf. Journal of Environmental Protection, vol. 4, pp.180-87. Said, S.A., Emtir, M. & Mujtaba, I.M., 2013. Flexible Design and Operation of Multi-Stage Flash (MSF) Desalination Process Subject to Variable Fouling and Variable Freshwater Demand. Processes, vol. 1, pp.279-95. Read More

Literature review According to Ismail (1998, p.145), there have been some rigorous automation and control applications of Multi-Stage Flash (MSF) plants that have recently shown some encouraging outcomes in finding modern control approaches to the reliability issue of MSF desalination. In view of this, Ismail (1998, p.145) conducted a survey to examine the efforts that have been made in using control and automation techniques to MSF Desalination plants as well as processes. In desalination plants, as mentioned by Ismail (1998, p.146), control systems are utilised to keep the plant parameters within acceptable design limits.

The main variables of the process that have to be set so that the MSF desalination plant operation can be acceptable are: Brine recirculation flow, the top brine heater temperature (TBT), make-up flow, Sea water feed flow and temperature, the condensate level of the brine heater, and the last stage brine and distillate level. Citing a number of studies, Ismail (1998, p.146) asserts that MSF plants can be controlled through regulation of the main parameters using automatic control loops that are anchored on conventional proportional–integral–derivative controllers as well as with less manual operation.

Therefore, he proposes an alternative microprocessor-based solution that is completely computerised. The proposed controllers according to Ismail (1998, p.154) exhibited superior performance and this provides evidence that new intelligent and advanced control systems may be used to solve a number of important issues such as parametric uncertainty, process complexity, disturbance accommodation as well as unmeasurable variables in the MSF desalination plants. Because the MSF desalination process has scores of output and input variables, Bodalal et al. (2010, p.395) agrees with Ismail (1998) that is hard to model the plant dynamic behaviour.

Therefore, to design the control system that can efficiently control the process variables it is important to understand the dynamics. In his study, Bataineh (2016, p.48) noted that a thermal energy driven desalination plant can bring about best performance when the collectors are sloped along the north and south axis at a fixed angle equal towards the latitude. Another study similar to this is that by Said et al. (2013) that seeks to describe the optimisation of the parameters of the MSF desalination process design as well as operation.

For this reason, Said et al. (2013, p.279) developed correlations of simple polynomial based dynamic seawater temperature as well as varying demand for freshwater anchored on the authentic data that was integrated into the MSF mathematical model by gPROMS ModelBuilder software. They optimised some of the MSF process operation parameters like recycle flow rate of brine and seawater at discrete time interval while the everyday total costs of operation were reduced. The results of optimisation exhibited an increase in the cost of operation but a reduction of the number of stages.

Besides that, Said et al. (2013, p.294) noted that the utilisation of intermediate storage tank supplements MSF plants flexible scheduling so as to meet the freshwater demand variation with fluctuating temperatures of the seawater devoid of interrupting the plant. Still, cooling the feed brine mixture at the intake of the MSF plant has become more promising and viable (Alhazmy, 2014, p.1035). According to Alhazmy (2011, p.5232), a MSF with brine mixing as well as cooling (MSF-MC) is an improved MSF plant that provides improved yield and performance ratio.

The MSF-MC plant sustains the basic advantages of low feed pumping power as well as chemical treatment of the MSF-BR. As mentioned by Alhazmy (2011, p.5232), low feed mass fraction facilitates in the reduction of the cooler size, cooling load, pumping power and the feed chemical treatment. He further noted that a yield improvement of 1.184 per cent was realised for every 10C reduction in the bottom temperature of the MSF plant.

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