Multistage Flash Plants Research Articles

A fixed point iterative algorithm for solving equations modeling the multi-stage flash desalination process

The paper presents an algorithm for solving the equations simulating the steady state behavior of the Multi Stage Flash (MSF) desalination process. The model can be used either for design of new plants or analysis and optimization of existing units. The set of equations relating the large number of design and operating variables for any stage ( ith stage) in MSF plant are decomposed into three subsets. The first subset contains equations describing processes in the tubes of the preheater inside the flashing chamber. The second subset deals with the processes inside the flashing chamber. These two subsets of equations are subsequently solved iteratively involving only a single variable for each subset. These variables are: (i) Saturation temperature T vi of the flashed-off vapor and (ii) Temperature of the unevaporated brine flowing from the chamber. The third subset of equations considered the existing interactions between the first two subsets. This subset defines the mass of vapor formed by flashing D i in the ith stage. All equations in the above-mentioned three subsets are solved by a reliable and efficient one-dimensional fixed-point iteration. The main advantages of this method are less sensitivity to initial guesses, requires a small number of iterations to obtain the required solution, and there is no need for calculating derivatives. The algorithm is implemented using the Computer-Aided Design (CAD) interactive package L-A-S (Linear Algebra and Systems). Detailed results are presented to show the dependence of the important factors controlling the fresh water cost, which are plant performance ratio, specific heat transfer area, specific brine flow rate, and specific cooling water flow rate, on the most significant two design variables, namely the total number of stages and the top brine temperature. The predicted data from the model are compared with published data of a typical MSF plant in operation at Kuwait. The agreement is found to be very good.

Environmental aspects of corrosion in MSF and RO desalination plants

Desalination plants are mostly manufactured from metallic materials and corrosion plays an important part in determining their life and reliability. The primary interest of plant designers and operators is to minimise corrosion in order to improve life and reliability, and less emphasis has been placed on the effects of corrosion products on the environment. This paper reviews known information on the corrosion behaviour of alloy materials in two important desalination processes, namely reverse osmosis (RO) and multi-stage flash (MSF) and considers the environmental effects of corrosion products. The main materials considered are the copper base alloys such as copper-nickels, and stainless steels. Details of alloy composition are given in Table 1. Both these groups of materials are used in large amounts in desalination processes.

Modeling multistage flash desalination plants

Multistage flash (MSF) desalination plants are among the major sources of potable water in the world, in particular in the Arab Gulf area [1]. These are very large, complex and expensive plants, in which large amounts of seawater and energy are consumed. Accordingly, big quantities of concentrated brine are disposed of after the desalination treatment. These characteristics of MSF plants make issues such as optimization of the operation and minimization of the corresponding environmental impact of the greatest importance. To the aim of addressing all these aspects, mathematical models provide a very useful tool. This work describes a steady-state mathematical model developed to analyze the MSF desalination process. It is based on a detailed physicochemical representation of the process, including all the fundamental elementary phenomena. In particular, the model accounts for the geometry of the stages, the variation of the physical properties of water with temperature and salinity, the different non-idealities involved in the process, the mechanism of heat transfer and the role of fouling. The developed model allows to analyze the role of operating and design variables in determining the process performances in terms of steady-state behavior. These information are used not only for design purposes, but also to support the development of a dynamical model through which the time-dependent behavior of the plant can be studied.

Solving equations simulating the steady-state behavior of the multi-stage flash desalination process

The paper presents an algorithm for solving the equations simulating the steady-state behavior of the multi-stage flash (MSF) desalination process. The model can be used either for designing new plants or anlysis and optimization of existing units. The set of equations relating the large number of design and operating variables for any stage ( i-th stage) in MSF plants is broken down into three subsets. The first subset contains equations describing processes in the tubes of the preheater inside the flashing chamber. The second subset deals with the processes inside the flashing chamber. These two subsets of equations are subsequently solved iteratively involving only a single variable for each subset. These variables are: (1) saturation temperature T vi of the flashed-off vapor and (2) temperature of the unevaporated brine flowing from the chamber. The third subset of equations considers the existing interactions between the first two subsets. This subset defines the mass of vapor formed by flashing D i in the i-th stage. All equations in the above-mentioned subsets are solved by a reliable and efficient one-dimensional fixed-point iteration. The main advantages of this method are less sensitivity to initial guesses, fewer iterations to obtain the required solution, and no need for calculating derivatives. The algorithm is implemented using the computer-aided design (CAD) interative package L-A-S (Linear Algebra and Systems). Detailed results are presented to show the dependence of the important factors controlling the fresh water cost, which are plant performance ratio, specific heat transfer area, specific brine flow rate, and specific cooling water flow rate, on the most significant two design variables, namely the total number of stages and the top brine temperature. The predicted data from the model are compared with published data of a typical MSF plant in operation at Kuwait. The agreement was found to be very good.

A comparative study of RO and MSF desalination plants

The total capacity of operating and projected desalination plants in Saudi Arabia is 725.4 mgd (2.74 Mm 3/d). Reverse osmosis (RO) only accounts for about 10% of the total desalted capacity. However, there is a recent trend toward the use of more RO in seawater desalination either for new plants or in connection with the present multi-stage flash (MSF) plants. MSF is preferred for large-scale dual-purpose seawater desalination plants. For single-purpose plants RO becomes a competitive choice, especially for moderate capacity. Power generation, desalting capacity and fuel cost strongly influence the selection of the desalination process. Process schemes also play an important role in this regard. MSF plants coupled with gas or steam turbines, RO with or without energy recovery and RO/MSF hybrid are examples of possible process schemes. In Saudi Arabia the first MSF plant was started in Al-wajh and Duba in 1928 with a capacity of 60,000 gpd (227.1 m 3/d). The first seawater RO plant in Saudi Arabia was installed in 1979. Recently numbers of RO and MSF plants were in production in different locations in Saudi Arabia. A discussion of the advantages and disadvantages of RO and MSF processes will be given as well as a detailed comparison between them. Plant production and capacity and energy consumption will be considered with reference to Saudi Arabia.

A comparative study of RO and MSF desalination plants

The total capacity of operating and projected desalination plants in Saudi Arabia is 725.4 mgd (2.74 Mm 3 /d). Reverse osmosis (RO) only accounts for about 10% of the total desalted capacity. However, there is a recent trend toward the use of more RO in seawater desalination either for new plants or in connection with the present multi-stage flash (MSF) plants. MSF is preferred for large-scale dual-purpose seawater desalination plants. For single-purpose plants RO becomes a competitive choice, especially for moderate capacity. Power generation, desalting capacity and fuel cost strongly influence the selection of the desalination process. Process schemes also play an important role in this regard. MSF plants coupled with gas or steam turbines, RO with or without energy recovery and RO/MSF hybrid are examples of possible process schemes. In Saudi Arabia the first MSF plant was started in Al-wajh and Duba in 1928 with a capacity of 60,000 gpd (227.1 m 3 /d). The first seawater RO plant in Saudi Arabia was installed in 1979. Recently numbers of RO and MSF plants were in production in different locations in Saudi Arabia. A discussion of the advantages and disadvantages of RO and MSF processes will be given as well as a detailed comparison between them. Plant production and capacity and energy consumption will be considered with reference to Saudi Arabia.

Advanced controls for multi-stage flash (MSF) desalination plant optimization

An in-depth study of an MSF desalination plant control system has been conducted. The degrees of freedom analysis based on a dynamic mathematical model was used to determine the number of controlled (PVs) and manipulated variables (MVs). The analysis of the control problem points to a fully interacting multivariable system. Furthermore, prudent plant practices dictate strict bounds on several of these PVs and MVs and the desire to achieve unit optimization is felt. Thus, the MSF plant is an ideal candidate for constrained model predictive control (CMPC). A locally developed CMPC was designed to achieve a variety of operational objectives such as maximizing distillate production or performance ratio, minimizing energy consumption, etc. CMPC provides set points to the existing PID controllers and, thus, integrity with the existing instrumentation is maintained. The performance of CMPC was tested utilizing the SPEEDUP dynamic simulation software and the results are excellent. For example, it is shown that for an illustrative plant, steam savings of $1.6 million per year are possible. The potential impact of CMPC for MSF plants is rather large considering that there are several hundred plants throughout the world all of which are currently on PID-type control.

Exergy analysis of major recirculating multi-stage flash desalting plants in Saudi Arabia

A simple and auspicious scheme to estimate exergy losses in multi-stage flash (MSF) plants is discribed. This method is used to evaluate major MSF plants in Saudi Arabia, namely, Al-Khobar II, Al-Jubail II, and Shuaibah. This study presents a quantitative assessment of the exergy losses, exergetic efficiency, and exergy-destruction term for each plant. The effect of these terms on the performance of the three MSF plants when operating at various top brine temperature (load conditions) is also investigated. The results obtained for the three plants show that the three MSF desalting plants are highly irreversible with exergetic efficiencies ranging from 1.12–10.38%. The associated total exergy destruction is found to range from 6.75–26.16% MW, with the exergy-destruction term ε ranging from 40.52–77.96 kJ/kg. The exergetic efficiency of brine heaters, when calculated separately, ranges from 72.20–87.98%, with exergy losses of 1.20–5.42 MW. The study concludes that the top brine temperature ( TBT) is directly proportional to the exergy losses in the MSF plants.

Steady-state analysis of multi-stage flash desalination process

The multi-stage flash (MSF) water desalination process plays a vital role in the provision of fresh water in many areas of the world, particularly in the Arab Gulf countries. This paper describes a steady-state mathematical model developed to analyze the MSF water desalination process. Relationships between parameters controlling the product water cost (e.g., thermal performance ratio, specific heat transfer surface area, and specific flow rate of cooling water and recirculated brine) to other operating and design variables are established. These relationships can be used to design new plants or to analyze already existing units. The model assumes the practical case of constant heat transfer surface area per stage in each section. It considered the variation of the physical properties of water with temperature and salt concentration, the effect of fouling factors and presence of non-condensable gases on the overall heat transfer coefficients, and variations in stage flash down and thermodynamic loss from stage to stage. The model also takes into consideration the heat transfer losses from the stages to the surroundings and through rejection of the noncondensable gases. The results obtained from the model developed are compared with data from six different MSF plants. Good agreement is obtained between data of these plants and model predictions.

Simulation Aided Design and Development of an Adaptive Scheme with Optimally Tuned PID Controller for a Large Multistage Flash Seawater Desalination Plant - Part I: Process Description, Linearised Dynamic Model and its Features

This paper is Part-I of a series of papers concerning the control of multistage flash (MSF) seawater desalination plants. MSF desalination happens to be a major means of producing potable water from the sea in several arid regions of the world. This process is one of thermal evaporation and condensation in a cascade of chambers through which heated seawater flows and flashes. The present day MSF plants are very large and complex. Their operation is energy intensive and the control of these plants is very crucial to the maintenance of life support in the related regions. The present set of three papers is based on a major scientific investigation believed to be the first of its kind in the field of desalination. This paper outlines the principle of MSF desalination and highlights the importance of the various control systems for a large MSF plant.An 18-stage MSF plant is considered for study. The following aspects are presented in this paper:1.An outline of the flowsheet simulation of the complete MSF plant model.2.Derivation of a linearized state-space model corresponding to several operating points, spanning the normal operating range.3.System theoretic analysis of the linearized model at all the operating points under consideration.4.Parameter variations of the linearized model over the operating region and their implications on control system design.5.Discussion and setting for the next phase of study.

A quarter-century of seawater desalination by large multistage flash plants in Abu Dhabi (Plant performance analysis, assessment, present efforts toward enhancement and future hopes)

This paper reviews some important aspects of performance of several large-scale multistage flash (MSF) seawater desalination plants, based on the operational experience over the past quarter-century in the Emirate of Abu Dhabi, United Arab Emirates. It discusses certain factors which influence plant performance, availability and economy in the light of the methods of current practice based on the observations made, the analysis carried out and the insight gained over the long period of operational experience. Arising out of this discussion are some sggestions for future research, design and development of MSF plants with the long-term objective of rendering them robust, reliable, economical, and intelligently automated for plant wide measurement, monitoring, assessment, optimization, control, diagnosis and care.

Evaluation of Belgard EV 2000 as antiscalant control additive in MSF plants

Scale formation on heat transfer surfaces, which is one of the basic problems in the distillation of seawater, can be effectively controlled or minimized by the addition of chemical additives. The most popular additives polyphosphate and Belgard EVN have extensively been used as scale control additives in Multi Stage Flash (MSF) plants in Kuwait. In 1988, a new product was introduced by Ciba-Geigy known as Belgard EV 2000. Belgard EV 2000 is an aqueous solution of an organic acid which acts either as threshold inhibitor or increases the adsorption of scale so as to reduce adhesion to metal surface. Ciba-Geigy collaborated with MEW in conducting a trial which is designed to show whether Belgard EV 2000 is a more cost-effective alternative than the currently used products Belgard EVN and polyphosphate. The present paper speculates the evaluation of Belgard EV 2000 as antiscaling agent in MSF plants. This additive was tested by the Ministry of Electricity and Water (ME&W) on unit A4 of Doha East Power & Water Production Station. The duration of the trial was from 18th April to 28th August, 1988, on a 130-day trial using low brine temperature (90°C), with a unit capacity of 6.0 migd. This additive exhibited satisfactory performance during the test period and successfully controlled the deposition of alkaline scale. No significant changes were observed in heater fouling when the dose level of Belgard EV 2000 was reduced from 2.5 ppm and maintained at 1.5 ppm. The brine heater and heat gain sections were inspected at the end of the trial period and the condenser tubes were found to be clean, which confirmed the capability of Belgard EV 2000 in controlling alkaline scale formation, in spite of the fact that the evaporator was not fitted with a sponge ball cleaning system.

Towards improved automation for desalination processes, Part II: Intelligent control

The frontiers of automatic control are expanding to keep abreast of the state-of-the-art technology. Innovative concepts in control systems have relegated what was considered a satisfactory solution a decade ago to obsolescence today. One novel feature is artificial intelligence (AI) which has ability to cope with uncertainties that we encounter in today's complex process control. Intelligent control systems are becoming almost commonplace worldwide incorporating special features such as expert systems, self-tuning, self-diagnosis, life management, equipment health monitoring, modelling and simulation. Thus, a trend towards larger desalination plants necessitates more sophisticated automation technology. In view of the benefits that can be realized from the application of artificial intelligence in the control field of desalination processes, intelligent control is the application of AI in control, employing methods like expert systems, neural networks, fuzzy logic and pattern recognition. Thereby, learning and decision making are the most important features of intelligent control. The application of intelligent control is necessary due to computational complexity, nonlinear behaviour with many degrees of freedom, and the presence of uncertainty in control environment. Intelligent control can be used at different levels of control systems. On the highest level, monitoring of data, selection of algorithms, selection of objective functions, and assigning of values for the setpoints are the main aims. On the level of advanced regulatory control, process identification can be supported by intelligent control, e.g. selecting of structures by expert systems, implementing neural networks for parameter estimation etc. Expert systems, assisted by pattern recognition, can be used at this level for tuning of adaptive controllers. Adaptation of controller parameters according to an intelligent strategy can also be provided by neural networks. Also, expert systems can be used to assist the design of advanced control systems. In the large field of design of conventional control systems, artificial intelligence methods can be used to provide intelligent user interface, to select the best algorithms, to consider design heuristics for optimization of feedback control loops etc. The varying and uncertain conditions in a multistage flash (MSF) desalination plant during its operation in the annual cycle of seasons under different situations of loads and disturbances, point out that no single fixed strategy, no matter how advanced it may be, is likely to be either valid or possible at all times under all conditions in all the sub-systems related to the plant. This paper is addressed to some aspects of artificial intelligence (AI) which aims at equipping the process with the capability for continual analysis and assessment of the situations that arise during the course of operation of the plant leading to the choice and implementation of an appropriate course of action in process control. At the outset MSF plant conditions calling for consideration of advanced control strategies with AI support are highlighted. Then some aspects of AI applicable to plant control are reviewed, finally, suggestions towards intelligent control of MSF plants are made pointing also to the possibility of an integrated system for Process Control and Care.

Towards improved automation for desalination processes, Part I: Advanced control

The desalination process industries have largely tried to solve control problems by conventional rather than modern control techniques that are attracting widespread industrial applications and revolutionizing process control as a result of advances in control theory. Control systems are designed from mathematical models that are generally imperfect descriptions of real processes. It is widely accepted that conventional PID or PI controllers may not provide satisfactory performance in view of non-linearity and uncertainty in the real world of desalination processes. It is essential that control systems operate satisfactorily over a wide range of process conditions. The practice of multi stage flash (MSF) desalination process control, process design, optimization, conspicuously lags behind contemporary theoretical developments. Conventional process control techniques do not ensure the safest and the most profitable operation of processes when compared with advanced process control which uses the knowledge of process economics and provides insight into the process to maintain essential variables at optimum setpoints. This paper is an attempt to promote excellence and innovation in desalination engineering and to remove barriers to advanced process control. Attempted here is brief clarification of some aspects of advanced control strategies in terms of answers to the questions: Advance control strategies: What are they? Where and when are they applicable? and What can be expected of them? Although the reference here is to MSF plants, some of the observations and remarks are also relevant to process control practice in general. In the end, the conclusions point out the complexity of the real world control problem which behoves us to advocate the application of techniques such as self-optimizing control strategies and artificial intelligence (AI) leading to an integrated system of intelligent control.

The MSF desalination process and its prospects for the future

The history of MSF (Multi-Stage Flash) desalination for commercial production took place in the Arabian Gulf in the late fifties. Today MSF plants over 4000 m 3/d produce over 7 million m 3/d water of which 80 % are in the Arabian Gulf. The author's relationship with desalination from 1952 till now is given; major developments and milestones reviewed; and accumulated data and experience, especially in the Arabian Gulf, for cycle, materials, operation, scale control and treatment are discussed. Control development and philosophy, optimization of plant performance for single and dual purpose plants, the method of cost allocation for dual purpose plant (power cum desalination), programs for cost calculation, and recommendations for type, size, scope of supply and materials, and for further research and development are given.

Simulation and design of MSF desalination processes

A mathematical model has been developed to simulate or design multistage flash (MSF) desalination processes. Stage by stage calculations have been carried out to determine variations in fluid properties and flow conditions. The generated set of simultaneous equations is solved by matrix algebra. The reliability of the precise model has been verified by comparing its predictions with operational data obtained from a test performed on a 23,496 m 3/d MSF plant and with short-cut methods in which simple and approximate equations are used. There is a very close agreement between the measured vapour temperatures and those predicted from the precise matrix analysis. The maximum deviation between the model's vapour rate predictions and those estimated from short-cut methods does not exceed 3.5%. The impact of uncertainties on the physical properties values on the behaviour of the short-cut method in which equal temperature intervals are assumed is also investigated.

Hybrid desalting systems

Currently, most large scale seawater desalting complexes are dual-purpose Multi-Stage Flash (MSF) plants producing both power and desalinated water. These plants produce high purity distilled water and also provide excess electrical power for sale at a typical ratio of 10 MWe power per 1 million gallon per day (MGD) of water. In the hybrid MSF/RO desalination power process, a seawater Reverse Osmosis (RO) plant is combined with either a new or existing dual purpose MSF/power plant with the following advantages: 1. The capital cost of the combined RO-MSF plant can be reduced. 2. A common, considerably smaller seawater intake can be used, in view of the smaller feedwater requirements for RO plants. 3. Product waters from the RO and MSF plants are blended to obtain suitable product water quality. Taking advantage of the fact that the MSF product typically exceeds potable water specifications, the product water specification in the RO system can thereby be reduced. 4. A single stage RO process can be used and the RO membrane life can be extended because of the reduced product water specification. 5. Electric power production from the MSF plant can be efficiently utilized in the RO plant, thereby reducing net export power production. 6. By blending with RO product water, the temperature of the MSF product water is reduced.

Experience with desalination plants in Libya

Multi Stage Flash plants have introduced into Libya since 1976. Over the period up to 1988 the installed capacity has grown to approximately 300,000 cu.m per day. Of this figure only 2 3 is operable. The availability of the plants is low representing less than 66 days/year. The most important problems are maintenance and unavailability of the skilled personnel. The Libyan experience with solving problems of seawater intake and corrosion are discussed. Also projection of future needs for desalination capacity are made.

Studies on MSF desalination — process design, construction and startup of a prototype MSF plant in India

A Desalination Experimental Facility (DEF) comprising multistage flash (MSF) unit of capacity 15 cubic meter/day with three stages had earlier been commissioned and operated for about two years to study the basic parameters of the MSF process. On the basis of operational experience and the data collected from experiments and the information available in literature a 33 stage 425 cubic meter/day MSF plant was designed, fabricated, installed and the same is under commissioning. This prototype plant was first such unit in India. This paper gives the considerations for the design of 425 cubic meter/day prototype MSF plant and the factors to be considered for scale-up to commercial size plants. The problems experienced during the module fabrication, erection and initial startup of the plant are highlighted.

Optimum design for a hybrid desalting plant

Dual purpose multistage flash desalination plant provides fresh water with low cost at high desalting capacity, but requires high installment cost. Two stage reverse osmosis desalination plant requires only half of the multistage flash installment cost while producing water with comparable price. By combining sea water reverse osmosis plant with the dual purpose multistage flash plant, the capital and operating cost can be reduced and the excess power can be efficiently utilized. The design parameters for such a hybrid plant will be the applied pressure and the recovery of the reverse osmosis plant and the number of stages and heat transfer areas for the multistage flash plant. The objective is to minimize the cost of water satisfying maximum total dissolved salt. Different cost scenarios are suggested and their effect on the optimum parameters are investigated. It is concluded from this study that the savings obtained from scaling-up is more than that obtained from hydridization.