A DYNAMIC SIMULATION MODEL OF REVERSE OSMOSIS DESALINATION SYSTEMS

A DYNAMIC SIMULATION MODEL OF REVERSE OSMOSIS DESALINATION SYSTEMS Chen-Jen Lee, You-Syuan Chen and Gow-Bin Wang Department of Chemical and Material Engineering / Green Technology Reearch Center Chang Gung Unierity, Taiwan 33302 Correponding Author E-mail: gbwang@mail.cgu.edu.tw ABSTRACT It i known that the water dealination indutry wa tarted early in the 20th century and true expanion and pread of thi indutry occurred during the 1960. The multi-tage flah (MSF) unit and reere omoi (RO) proce are the mot popular dealination ytem for the indutry tandard. In recent year, the market hare of RO dealination ha widely expanded becaue of ignificant improement and adantage in membrane technology. To obtain the feaible operating condition of the RO dealination ytem, an efficient and accurate proce model ued in the plant i neceary. Thi work trie to tudy the dynamic characteritic and proce operation apect of a large-caled RO dealination plant. The teady-tate and dynamic mathematical model for the membrane module and RO plant preented in the literature are firt tudied. The feaible dynamic RO model are then utilized to deelop the oerall proce flow heet for the indutrial cale RO dealination proce by uing powerful commercial proce deign imulator. Satifactory reult of the teady-tate and dynamic operating condition of the propoed RO proce flow heet are compared to thoe hown in the literature. Keyword: Dynamic Simulation; Model; Deign; Reere Omoi; Dealination Sytem. 1. INTRODUCTION The water dealination indutry wa tarted early in the 20th century. True expanion and pread of the water dealination indutry occurred during the 1960. There are eeral commercial method uch a multitage flah (MSF), multi effect ditillation (MED), apor compreion (VC) ditillation, reere omoi (RO), and electrodialyi (ED) propoed for water dealination. Table 1 illutrate the worldwide capacity for eeral commercial dealination proce (Lee, 2009). It i apparent that multitage flah and reere omoi technologie remain the main tandard in today eawater dealination indutry. Alatiqi et al. [1999] preented a reiew for the control loop and intrumentation ued in MSF and RO plant. Van der Bruggen and Vandecateele [2002] proided an oeriew of important proce improement in eawater dealination uing RO, MSF, MED and ED. Recently, the market hare of RO dealination ha ignificantly increaed becaue of low operating temperature, modular deign, low energy requirement and low water production cot. The piral wound module i mot popular among RO membrane module. Many mathematical model hae been propoed to characterize the eparatie propertie of membrane during the pat two decade. But far fewer model hae been deeloped to 1

decribe the whole membrane module. Senthilmurugan et al. [2005] deeloped a teady-tate model for the piral wound module uing a three-parameter nonlinear membrane tranport model. Abba [2005] preented a emi-rigorou teady-tate model for imulation and analyi of an indutrial medium-cale brackih water RO plant baed on piral-wound membrane module. Senthilmurugan et al. [2005] deeloped a teady-tate model for the piral wound module uing a three-parameter nonlinear membrane tranport model. Recently, Oh et al. [2009] propoed a implified imulation model baed on the olution-diffuion theory and multiple fouling mechanim to analyze the operation, optimization and performance of RO ytem. Kaghazchi et al. [2010] preented a emi-rigorou teady-tate model to imulate and inetigate the operaton and performance of two indutrial eawater RO plant baed on piral-wound membrane module. A mentioned by Marriott and Sorenen [2003], due to the complex mechanim of flow through membrane module and lot of idealized aumption, exiting RO unit model are uually proce pecific and are only alid within a limited operating range. They deeloped a detailed mathematical model of a general membrabe eparation proce from rigorou ma, momentum and energy balance and diregard ome common aumption. Thi work trie to tudy the dynamic characteritic and proce operation apect of an indutrial largecaled RO dealination plant. The feaible teady-tate and dynamic model of the membrane module and RO plant preented in the literature are effectiely combined to deelop the oerall proce flow heet for the indutrial cale RO dealination proce by uing powerful commercial proce deign imulator. Simulation reult of the teady-tate and dynamic operating condition of the propoed RO proce flow heet are compared to thoe hown in the literature. Table 1: Worldwide capacity for eeral commercial dealination proce (Lee, 2009) Dealination proce MSF RO MED ED VC TOTAL % total world capacity (1996) 56 31 5 5 3 100 % total world capacity (2003) 36.1 51.6 3.0 4.5 4.8 100 2. RO DESALINATION SYSTEM DESCRIPTION Reere omoi i a preure-drien membrane proce ued to eparate olute and olent of the ame order of molecular ize. It i well known the mot common application of RO unit i the eparation of alt from water to obtain portable water. There are four type of membrane module aailable in the marketplace: plate and frame, hollow-fiber, piral-wound and tubular. Among thee membrane module, the piral wound module occupie the larget market hare due to it relatie eae of cleaning, fabrication technology and ery large urface area per unit olume. In general, the RO dealination ytem include feed and 2

product treatment unit, membrane module, feed pump and energy recoery deice (ERD). Figure 1 how a implified ketch of the RO plant. The Jeddah 1 RO dealination plant Phae II in the Kingdom of Saudi Arabia wa commercially operated on 1994. Jeddah 1 RO plant ha a production capacity of 30 MGPD (113,600 m 3 /day). At that time, combining phae I and phae II plant gae the larget eawater RO plant in the world. By uing actual operating data from thi large cale commercial RO dealination plant, Al-Shayji [1998] firt deeloped a neural-network approach for the prediction and optimization of proce performance ariable of thi RO plant. Table 2 gie deign pecification for thi indutrial dealination proce (Al-Shayji, 1998). Thi work trie to tudy the dynamic characteritic and proce operation apect of the mentioned large cale RO dealination plant. The feaible dynamic RO model are tudied to deelop the oerall proce flow heet for the indutrial cale RO dealination proce by uing powerful commercial proce deign imulator. Figure 1: Schematic diagram of the reere omoi proce Table 2: Deign pecification for an indutrial RO Plant (Al-Shayji, 1998) 3

3. MODELING OF A SPIRAL WOUND MODULE In general, the following factor may directly affect the performance of RO dealination procee: (1) Effectiene of the pre-treatment unit. (2) Membrane: type, ize and the number of module ued and their arrangement. (3) Rate and degree of fouling and cleaning ability. (4) Operating condition uch a feed preure, temperature and permeate recoery. (5) Efficiency of pump and energy recoery deice. In thi tudy, the effectiene of the pretreatment unit i neglected and a binary ytem i conidered. The piral wound module with general property i ued in the RO membrane module. To inetigate the dynamic characteritic and proce operation apect of an indutrial RO dealination plant, the teady-tate and dynamic mathematical model for the membrane module are deeloped below. 3.1 Model Aumption The main aumption ued for the RO model deriation include: (1) The olutiondiffuion model i alid for the tranport mechanim of the olute and olent through the membrane. (2) The RO membrane module i non-porou and i treated a a flat heet with pacer. (3) The RO proce i iothermal. (4) Omoi preure i proportional to the alt concentration and preure drop in permeate ide i negligible. (5) The film model theory and Fick law for diffuion are applicable for calculating concentration polarization effect. (6) Diffuion coefficient i independent of olute concentration. (7) Ma tranfer coefficient i contant for a gien fluid condition. 3.2 Membrane Tranport Modeling Senthilmurugan et al. [2005] and Oh et al. [2009] hae applied the olution-diffuion model modified with the concentration polarization theory for analyzing the operation, optimization and performance of RO ytem. According to the chematic diagram of the RO proce hown in Figure 1, the following teady-tate membrane tranport equation can be deried. The olent flux, J, through the membrane i gien by J L P P ) L [ P ( P )] (1) ( f lo f d where L i the olent tranport parameter, P f i the feed preure and P lo i the preure lo by omoi preure Δπ and the preure drop along a RO ytem P d. Here, L, Δπ and P d are expreed by (Oh et al., 2009) L L 0 e 1 1 1( T 293) 2Pf 293 R c 1 A A m (2) ( c c RT (3) m p ) 2 zd h P d 1 (4) 4

where L 0 i the intrinic olent tranport parameter, T i the temperature, ηi the icoity, R c i the reitance due to cake formation, A i the membrane area occupied by precipitation, A m i the total membrane area, and α 1 and α 2 are two contant for olent tranport. c m and c p are olute concentration at the membrane urface on the feed ide and olute concentration on the permeate ide, repectiely. R i the ideal ga contant.γ 1 andγ 2 are two contant for preure drop along a RO ytem. z, d h andν denote the feed olution elocity on the bulk olution ide, hydraulic diameter and kinematic icoity, repectiely. The olute flux, J, through the membrane i gien by J J c L c c ) (5) p ( m p where L i the olute tranport parameter L L 0 e 1 ( T 273) 273 (6) where L 0 i the intrinic olute tranport parameter and β 1 i contant for olute tranport. Accumulation of the impermeable olute on the membrane urface lead to the deelopment of a concentration polarization layer which may be determined by the concentration polarization. That i J cm c p k e (7) c c b p where c b i the olute concentration in the bulk olution and k i the ma tranfer coefficient for the back diffuion of the olute k zd 0.5510 h 0.4 D 0.17 cb 0.77 D d h (8) whereρi the denity and D i the olute diffuion coefficient. 3.3 Feed and Permeate Channel Flow Modeling Marriott and Sorenen [2003] hae deeloped a two-dimention flow model to decribe flow in the axial and piral direction on both the feed and permeate ide. According to the chematic diagram of a flat membrane enelope hown in Figure 2, the following dynamic ma balance can be deried. cb Fz 1 cb 1 J cb z D J t z h z z h (9) where c b i the olute molar flux in the axial direction and h i the channel height on the feed ide. In thi work, the effect of the olute molar flux in the piral direction i neglected for implifying Eq. 9. On the other hand, the effect of the change in concentration due to the flux of olent through the membrane i not conidered in Eq. 9. A mentioned by Lee et al. [2001], Eq. 9 can be modified a 5

Figure 2: Sketch of a piral wound module (Marriott and Sorenen, 2003) cb Fz 1 1 cb 1 1 J J cb cbz D J J t z h h z z h h c b (10) Furthermore, the oerall material balance for the feed and the permeate ide propoed by Senthilmurugan et al. [2005] are gien by d z dz J h (11) d p dp J h p (12) where p i the feed olution elocity on the permeate ide and h p i the channel height on the permeate ide. 3.4 Simulation Reult for a Sprial Wound Module In thi work, the relatie mathematical model for the membrane module depicted aboe are applied for RO proce imulation. Mot of the alue of parameter and pecification are taken from the literature of Senthilmurugan et al. [2005] and Oh et al. [2009]. Some unknown parameter are found from the literature of Lee et al. [1999] and Abba [2007]. Here, the RO ytem imulation model i built on Apen Cutom Modeler platform. The model i then ued for analyzing the effect of the ariation of the feed parameter on the permeate flowrate. A hown in Figure 3, the permeate flowrate i een to decreae with increaing feed concentration. In Figure 4, the permeate flowrate i een to increae with increaing feed preure. The aboe imulation reult are conitent with thoe reported by Senthilmurugan et al. [2005]. 6

Qp(m 3 /*10 5 ) 1.48 1.47 1.46 1.45 1.44 1.43 1.42 1.41 1.4 1.39 0 0.5 1 1.5 2 2.5 3 3.5 Cf(kg/m 3 ) Figure 3: Permeate flowrate. feed concentration for a piral wound module Qp(m 3 /)*10 5 2.5 2 1.5 1 0.5 0 15 20 25 30 35 Pf(bar) Figure 4: Permeate flowrate. feed preure for a piral wound module 4. DYNAMIC SIMULATION MODEL OF AN INDUSTRIAL RO PLANT Thi work trie to tudy the dynamic characteritic and proce operation apect of a large-caled RO dealination plant. Jeddah 1 RO plant commercially operated in Saudi Arabia i taken a a demontration example. The feaible dynamic RO model are tudied to build the oerall proce flow heet for the indutrial cale RO on Apen Cutom Modeler platform. Satifactory reult of the teady-tate and dynamic operating condition of the indutrial RO dealination ytem are compared to thoe hown in the literature. 4.1 Proce Flowheet of an Indutrial RO Plant In general, the RO dealination ytem include feed and product treatment unit, membrane module, feed pump and energy recoery deice (ERD). The Jeddah 1 RO dealination plant Phae II in the Kingdom of Saudi Arabia wa commercially operated on 1994. Thi Jeddah 1 Phae II plant ha a production capacity of 15 MGPD (56,800 m 3 /day) with 10 train. That i, the production capacity i about 5,680 m 3 /day for each train. By uing deign pecification of thi indutrial dealination proce gien in Table 2 (Al-Shayji, 1998), the oerall RO proce flow heet of thi indutrial RO plant i built on Apen Cutom Modeler platform. Figure 5 illutrate the propoed RO proce flow heet. 7

Figure 5: Propoed proce flowheet for RO dealination ytem 4.2 Simulation Reult for an Indutrial RO Plant According to the oerall RO proce flow heet built on Apen Cutom Modeler platform, Table 3 how part of the imulation reult. In thi cae, the obtained production capacity i about 2,670 m 3 /day for each train. The correponding recoery ratio i about 16.5 %. Thee reult are about half of thoe gien in Table 2. In thi direction, the 148 RO piece for each train ought to be rearranged for the propoed RO flow heet. The effect of the ariation of the feed flowrate and feed preure on the recoery ratio i hown in Figure 6. Table 3: Simulation reult for the indutrial RO Plant Input Brine output Permeate output Flow rate (m 3 /hr) 676.2 565.41 111.15 Concentration (mole/m 3 ) 746.5 1068.72 1.62 Preure (bar) 80 80 1.01 Temperature (K) 300 300 300 40 35 30 25 recoery20 15 10 5 0 0 100 200 300 400 500 600 input flow rate m 3 /hr T300P80 T300P70 T300P60 T300P50 Figure 6: Recoery ratio. feed flowrate for the propoed RO flow heet 8

5. CONCLUSIONS In recent year, the market hare of RO dealination ha widely expanded becaue of ignificant improement and adantage in membrane technology. To obtain the feaible operating condition of the RO dealination ytem, an efficient and accurate proce model ued in the plant i neceary. Thi work trie to tudy the dynamic characteritic and proce operation apect of a large-caled RO dealination plant. The feaible teady-tate and dynamic model for the membrane module and RO plant preented in the literature are utilized to deelop the oerall proce flow heet for the indutrial cale RO dealination proce. The oerall RO proce flow heet of the indutrial RO plant i ucefully built on Apen Cutom Modeler platform. Simulation reult of the teady-tate and dynamic operating condition demontrate the atifactory effectiene of the propoed RO proce flow heet. ACKNOWLEDGEMENTS Financial upport from Chang Gung Unierity (UERPD 280261) and Minitry of Education (EZRPD 280071) i gratefully acknowledged. REFERENCES 1. Abba A., Simulation and Analyi of an Indutrial Water Dealination Plant, Chemical Engineering and Proceing, 44, 999-1004, 2005. 2. Abba A., On the Performance Limitation of Reere Omoi Water Dealination Sytem, International Journal of Nuclear Dealination, 2, 205-218, 2007. 3. Alatiqi I. M., Ettouney H. M. and El-Deouky H., Proce Control in Water Dealination Indutry: an Oeriew, Dealination, 126, 15-32, 1999. 4. Al-Shayji K. A., Modeling, Simulation and Optimization of Large-cale Commercial Dealination Plant. Doctoral Diertation of Chemical Engineering Department at Virginia Polytechnic Intitute and State Unierity, Virginia, USA, 1998. 5. Kaghazchi T., Mehri M., Raanchi M. T. and Karari A., A Mathematical Modeling for Two Indutrial Seawater Dealination Plant in the Perian Gulf Region, Dealination, 252, 135-142, 2010. 6. Lee C. J., Dynamic Modeling and Control of an Indutrial Multitage Flah Dealination Proce. M.S. Thei of Dept. of Chemical and Material Engineering, Chang Gung Unierity, Tao-Yuan, Taiwan, 2009. 7. Lee S., Kim J. and Lee C. H., Analyi of CaSO4 Scale Formation Mechanim in Variou Nanofiltration Module, Journal of Membrane Science, 163, 63 74, 1999. 8. Lee S. and Lueptow R. M., Rotating Reere Omoi: a Dynamic Model for Flux and Rejection, Journal of Membrane Science, 192, 129 143, 2001. 9. Marriott J. I. and Sorenen E., A General Approach to Modelling Membrane Module, Chemical Engineering Science, 58, 4975 4990, 2003. 10. Oh H. J., Hwang T. M. and Lee S., A Simplified Simulation Model of RO Sytem for Seawater Dealination, Dealination, 238, 128 139, 2009. 11. Senthilmurugan S., Ahluwalia A. and Gupta S. K., Modeling of a Spiral-wound Module and Etimation of Model Parameter Uing Numerical Technique, Dealination, 173, 269-286, 2005. 12. Van der Bruggen B. and Vandecateele C., Ditillation. Membrane Filtration: Oeriew of Proce Eolution in Seawater Dealination, Dealination, 143, 207-218, 2002. 9

Brief Biography of the Preenter Chen-Jen Lee receied B.S. degree in Chemical Engineering from Chang Gung Unierity, Tao-Yuan, Taiwan, in 2009. He i currently puruing the Ph.D. degree at the Department of Chemical and Material Engineering, Chang Gung Unierity. Hi main reearch interet include eawater dealination proce imulation, proce modeling and control. 10