Modelling, Design and Optimisation of a Hybrid PSA-Membrane Gas Separation Process

Transcription

1 17 th European Symposum on Computer-Aded Process Engneerng (ESCAPE17) (V. Plesu and P.S. Agach, Edtors) 007 Elsever B.V. All rghts reserved. 1 Modellng, Desgn and Optmsaton of a Hybrd PSA-Membrane Gas Separaton Process Charles O. Aknlab, Dmtros I. Gerogorgs, Mchael C. Georgads and Efstratos N. Pstkopoulos Centre for Process Systems Engneerng, Imperal College London, SW7 AZ, UK Emal: [Charles.Aknlab05, D.Gerogorgs, E.Pstkopoulos]@mperal.ac.uk, mgeorg@otenet.gr Abstract Pressure swng adsorpton (PSA) and membrane-based gas separaton processes are two dfferent alternatves for effectve, contnuous bulk gas separaton at the ndustral scale. Both these processes possess characterstcs that render them advantageous over conventonal cryogenc processes, and they can be combned nto a Hybrd Separaton System (HSS). Dynamc smulaton and optmsaton of a HSS must rely on all mathematcal equatons descrbng the dynamc behavour of PSA and membrane permeaton modules n a sngle flowsheet. The mathematcal model s a set of Partal Dfferental and Algebrac Equatons (PDAE) and has been used to nvestgate two HSS classes, consderng the case of ar separaton. The paper consders two HSS concepts (for same and opposte separaton selectvty), and presents dynamc smulaton and optmsaton results, focusng on the performance of the HSS flowsheet and demonstratng sgnfcant mprovements over the standalone PSA and membrane processes. Keywords: PSA, membrane, gas separaton, modellng, desgn, optmsaton. 1. Introducton and Motvaton Advances n non-cryogenc gas separaton process applcatons over the past 0 years have been drven by the need to mprove effcency and reduce cost, va

2 C.O. Aknlab et al. alternatves to several tradtonal, energy-ntensve gas separaton processes (dstllaton, chemcal absorpton). Hgh-purty hydrogen, whch s foreseen as the fuel for the future, s commercally produced by pressure swng adsorpton (PSA), a typcally low product recovery process. Prevous studes (Srcar et al., 1999; Srcar & Golden, 000) dentfed that ntegratng a membrane module nto PSA can mprove the overall recovery of the separaton process. Membrane gas separaton processes are also shown to be cost-effectve n separatng greenhouse gases from gaseous mxtures at hgh purty (CO capture and sequestraton). Numerous studes (Bhde et al., 1998; Naher et al., 1997, Zolandz & Flemng, 199) show that combnatons of a membrane module and another separaton process offer lower cost and better separaton performance than an all-membrane separaton system. The frst combnaton of a membrane and an adsorpton separaton process s attrbuted to Mercea and Hwang (1994); a PSA unt was used to mprove the O enrchment performance of a Contnuous Membrane Column (CMC), and the combnaton featured superor economcs and separaton performance over both PSA and CMC processes. Feng et al. (1998) proposed an ntegrated process n whch gas permeaton s ncluded n the sequental steps of PSA, hence consderng permeaton occurng n a cyclc fashon. Hydrogen purfcaton from a gaseous mxture has also been studed: results show that a hybrd PSA-membrane acheves hgher purty compared wth a standalone PSA process. Other PSA-membrane combnatons are shown to mprove the performance of ether of the two unts (Srcar et al., 1999; Esteves & Mota, 00), yet none presents a detaled mathematcal model and numercal soluton procedure for smulaton and optmsaton. The man goal of ths paper s thus to study the potental of a PSA-membrane HSS by developng a rgorous mathematcal model for ts dynamc smulaton and optmsaton, and by usng t to obtan relevant results and desgn conclusons. Ar separaton s the exemplary case study for the hybrd gas separaton process.. Process Descrpton: Hybrd Separaton Systems (HSS) All hybrd PSA-membrane processes are classfed nto two categores n the lterature: (a) Membrane followed by PSA (Class I), (b) PSA followed by membrane (Class II). Rgorous mathematcal models combne all equatons descrbng the dynamc behavour of the membrane separaton module nto the cyclc operatng steps of the PSA process; such models are sets of Integral Partal Dfferental and Algebrac equatons (IPDAEs) and ther mplementaton for dynamc smulaton and optmzaton s often challengng and cumbersome. HSS I: In a Class-I HSS flowsheet, the membrane comes before the PSA (Fgure 1a). The frst processng step s feedng fresh compressed gas nto a hollow fbre module: the permeate s obtaned at the shell sde (atmospherc pressure), whle the resdue stream (assumed to be at feed pressure) s obtaned at the tube sde of the fbre module. Dependng on PSA selectvty, the

3 Modellng, Desgn & Optmsaton of a Hybrd PSA-Membrane Gas Separaton Process 3 membrane resdue or permeate s used as PSA feed: n N producton (HSS wth same selectvty) the N -rch (resdue) stream s fed to PSA; n O producton (HSS wth opposte selectvty) the O -rch (permeate) stream s used. Ether the resdue or the recompressed permeate s fed n the frst step (pressursaton), yet the hgh-pressure resdue stream s the only fed n the second step (adsorpton). HSS II: In a Class-II HSS flowsheet, the membrane comes after the PSA (Fgure 1b); Srcar et al. (1999) consdered such a HSS to mprove the recovery of a H PSA process. The cyclc steps of ths HSS start wth fresh feed ntroducton nto the PSA unt; then, the purge gas from each PSA bed passes through the membrane to ncrease recovery. The membrane resdue stream obtaned can be recycled as fresh feed to the PSA bed or (n the case of multple beds), the permeate stream can be used for purgng other beds. Generally, feed condtons for the PSA unt depend on the membrane module (HSS I); feed condtons for the membrane unt depend on the PSA beds effluent (HSS II). The present study s based on separaton selectvty towards the target speces. A bnary gas mxture Hybrd Separaton System (HSS) n whch the gas more adsorbed n the PSA s more permeable through the membrane s a HSS wth same selectvty; when the same gas s the least permeable, then we have a HSS wth opposte selectvty. Polymerc membranes are usually only selectve to O (O beng obtaned as permeate), but for PSA, ether O or N can be more adsorbed (dependng on the adsorbent used). The combned HSS mathematcal model of ths paper thus consders (Aknlab, 006): (a) A dual-bed PSA unt (producng N on carbon molecular seve and O on zeolte 5A), and (b) A steady-state, sothermal, cross-flow permeaton hollow fbre membrane module. a b Fgure 1: The two Hybrd Separaton System (HSS) flowsheets consdered: (a) HSS I, (b) HSS II. 3. Mathematcal Model Formulaton and Dynamc Smulaton The dynamc behavour of standalone PSA beds and membrane modules s studed for varous operatng condtons, to obtan a base case for comparson. An expermentally used polysulphone membrane (Ettouney & Majeed, 1997) s

4 4 C.O. Aknlab et al. consdered, to analyse the cross-flow sothermal membrane model dynamcs. For PSA, feed pressure and product flow rate are vared, and a standard model s used (Nlchan, 1997; Srcar et al., 1999; Srcar & Golden, 000). Both PSA and membrane unts are studed at low pressure ratos (feed to permeate/purge pressure rato), assumng sothermal condtons wthout any pressure losses. Models and smulaton condtons for both modules are presented n Table 1. Table 1: Mathematcal models for membrane separaton and Pressure Swng Adsorpton (PSA). Membrane unt mathematcal model Pressure Swng Adsorpton (PSA) mathematcal model Ar separaton va PERMEA membrane Ntrogen/N Producton on Carbon Molecular Seve C d(qx ) = JdA C ( υc ) 1 εbed q (1) DL + + = 0 z z ε J P H L ( P x P y ) P 180μ(1 εbed ) υ = () = = 0 (14) δ 3 εbed DPARTICLE c dq d(qx) P y = (3) = da da C RT = 1 c dx q ΩD0 * = 0 (4) = ( q q ) da r = 1 c * bqs q = c x (0) = y feed, (5) 1+ bc = 1 Q (0) = Q f (6) Oxygen/O Producton on Zeolte 5A Q (0) = Q C ( C ) q f (7) C υ ε t DL + + ρb = 0 (18) z z Qrx α = (8) ε t = εb + εp( 1 εb ) (19) Qf yfeed, da = πd0ndl (9) Qproduct, Purty = c Qproduct, = 1 Qproduct, covery Qfeed, (10) D0 εp DkDm τp Dk + Dm BED (13) (15) (16) (17) = (0) T D k = 48.5d PORE (1) MW * Re = (11) q = m C RT () 4. Dynamc Smulaton Results and Optmal Base-Case Desgn Membrane Smulaton: A membrane unt s studed for varous module areas (Fgure ). The followng straghtforward conclusons emerge from nspecton:

5 Modellng, Desgn & Optmsaton of a Hybrd PSA-Membrane Gas Separaton Process 5 (a) N enrchment ncreases wth membrane area but decreases wth feed gas flow rate, (b) O enrchment decreases wth membrane area but ncreases wth feed gas flow rate, (c) The membrane area requred for separaton ncreases wth ncreasng stage cut, (d) The membrane area requred for separaton decreases wth ncreasng pressure rato, (e) Permeate (O ) qualty ncreases and resdue (N ) qualty decreases at low stage cut. Thus, we conclude that ths s a desgn sutable for lmtng feed gas loss, hence reducng the area requrements. Fgure : Dynamc smulaton for desgn of a standalone membrane separaton unt (P H /P L = 3). PSA Smulaton: A PSA unt s studed for varous adsorpton bed heghts (Fgure 3), consderng the same pressure ratos and varable product flow rate, subject to balances. The followng straghtforward conclusons are now derved: (a) The product purty ncreases wth pressure rato (at the expense of product recovery), (b) Hgher product recovery s attanable by ncreasng the volumetrc product flow rate, (c) Power requrement ncreases wth pressure, bed sze (heght) and product flow rate, (d) The N and O producton unts reach CSS at 40 cycles and 60 cycles, respectvely, (e) Pressure and PSA bed mole fracton trends conform to Skarstrom cycle standards (Srcar et al., 1999). Fgure 3: Dynamc smulaton for desgn of a standalone PSA separaton unt at CSS condtons. Optmal base-case desgn: The base-case desgn for the membrane hollow-fbre module and the PSA bed focuses on mnmsng the combned operatonal and nvestment costs, achevng the desred target gas purty at mnmum unt sze and energy consumpton. The N -enrched ar for commercal applcatons must

6 6 C.O. Aknlab et al. be of hgh purty (95-99% N ); O -enrched ar must also be of >35% purty. The base case s the maxmsaton of O enrchment (membrane) and of N purty (PSA), assumng there are mnmum power requrements: (a) Membrane: Q= m 3 /s, N :O =79.1:0.9, A=0. m, P H :P L =(3:1) 10 5 bar, (b) PSA: Q prod = m 3 /s, Q purge = m 3 /s, N :O =79.1:0.9, P H :P L =(3:1) 10 5 bar. Table : Performance of standalone PSA unts vs. volumetrc feed flow rates and pressure ratos. Ntrogen/N producton (standalone PSA unt) Oxygen/O producton (standalone PSA unt) Q= m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 Q= m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 N purty (P) % % % O purty (P) % % 71.3 % N recovery (P) 9.0 %.3 % % O recovery (P) % 9.87 % 7.55 % O purty (E) 7.30 %.60 %.5 % N purty (E) % % 79. % Avg. power/w 1.04 W 1.79 W.60 W Avg. power/w 4.35 W 8.47 W W Q= m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 Q= m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 N purty (P) % % % O purty (P) % % % N recovery (P) % 9.9 % 5.1 % O recovery (P) 19.6 % % % O purty (E) 4.78 % 3.98 % 3.4 % N purty (E) % % 79.7 % Avg. power/w 1.17 W 1.97 W.8 W Avg. power/w 4.46 W 8.63 W W Q= 10-5 m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 Q= 10-5 m 3.s -1 P H /P L = 3 P H /P L = 4 P H /P L = 5 N purty (P) 91.4 % % % O purty (P) % % % N recovery (P) 44.9 % % % O recovery (P) 3.48 % % % O purty (E) 5.99 % 5.14 % 4.44 % N purty (E) % % % Avg. power/w 1.30 W.14 W 3.04 W Avg. power/w 4.56 W 8.77 W W 5. Dynamc Optmsaton Results Dynamc optmsaton focuses on maxmsng HSS recovery at the maxmum purty; we seek optmal hybrd gas separaton process condtons that mnmse operatonal costs, because operatonal costs vary nversely wth product recovery (as n most separatons). Operatonal costs of PSA processes are due to mantenance, energy and raw materals; nvestment costs are due to columns, adsorbent, compressor and valves (Cruz, 005). Dynamc optmsaton va successve substtuton s very expensve (Jang et al., 004); thus, smultaneous spatal and temporal dscretsaton (Nlchan, 1997) has been used to accelerate convergence to CSS (all begnnng and end bed condtons have to be dentcal). A lterature heurstc cycle tme constrant prescrbes that adsorpton and desorpton tmes must be equal, to allow that both beds attan equal performance (Jan et al., 003). The optmsaton decson varables are selected to be the PSA bed heght, cycle tme and membrane area, and they have been determned at specfed volumetrc flow rates and at desred pressure ratos. Dynamc optmsaton s performed on the gopt /gproms platform, va nd - order 6-pont orthogonal fnte element collocaton (OCFEM) for the spatal

7 Modellng, Desgn & Optmsaton of a Hybrd PSA-Membrane Gas Separaton Process 7 doman and 1 st -order, 40-pont backward fnte dfferencng (BFDM) for the temporal doman, yeldng mproved result accuracy. Dynamc optmsaton results for the HSS vs. standalone unts are presented n Table 3, and the resultng optmal desgn measures (HSS re-smulaton) are presented n Table 4. HSS product purty and recovery (for same selectvty) are sharply ncreased, at reduced PSA power consumpton (snce recovery s nversely proportonal to the power requred). The mprovement comes at the cost of ncreased membrane area, a fact mplyng lower recovery n the module and a larger number of fbre capllares requred for enrchment, ncreasng the fxed nvestment requrement. Table 3: Performance comparson of HSS vs. standalone unts for same and opposte selectvty. Ntrogen/N producton Same Selectvty Oxygen/O producton Opposte Selectvty PSA (standalone) HSS I HSS II PSA (standalone) HSS I HSS II N purty P % % O purty P % 83.7 % N recovery P 9.0 % 8.89 % O recovery P % % O purty E 7.30 % 0.95 % N purty E % 68.0 % Membrane (standalone) HSS I HSS II Membrane (standalone) HSS I HSS II N enrchment % % O enrchment % % O enrchment %.40 % N enrchment % 68.5 % N recovery % % O recovery % 88.6 % Table 4: Dynamc optmsaton results and performance of the Hybrd Separaton System (HSS I) HSS Decson Varables HSS: PSA Performance HSS: Membrane Performance τ pressurzaton s Product purty/n 98.4 % Resdue enrchment/n % τ adsorpton s Product recovery/n % Resdue recovery/n 7.16 % τ blowdown s Extract purty/o 6.05 % Stage cut % τ purge s Average Power/Watts 0.5 W Number of fbers 6077 τ cycle s L (PSA bed heght) m A (membrane area) m 6. Conclusons A dynamc smulaton and optmsaton strategy has been developed and used for a hybrd (pressure swng adsorpton combned wth membrane) gas separaton process. The HSS combnes the two processes n a sngle flowsheet and consders the dynamcs of each process unt, to acheve desgn for optmal bulk gas separaton performance. Dynamc smulaton of Class-I and Class-II HSS (wth same or opposte selectvty) covers prevous ntegrated PSAmembrane flowsheets publshed n journal and patent lterature. The IPDAE model requres a robust numercal algorthm (DASOLV, gproms ), as the dscretsaton method greatly affects accuracy (due to boundary dscontnutes). Ths mplementaton mproves the accuracy of results and ensures robustness. Dynamc smulaton results obtaned reproduce the HSS behavour and known

8 8 C.O. Aknlab et al. tradeoffs between product recovery and purty n both PSA and membrane separaton processes, and allow the use of the model for optmsaton studes. Advantages of the two processes combned n the ntegrated HSS plant are complementary: ths s llustrated by comparng the HSS to both standalone PSA and membrane unts (feed and product flow rates of compared systems are equal, to establsh a far bass). The HSS gas separaton process has defnte benefts over both standalone unt types: (a) HSS wth opposte selectvty are preferable when hgh product purty and recovery are requred; ths n turn mples slghtly hgher energy costs for effectve performance. (b) HSS wth same selectvty have nferor separaton performance, but appear less energy ntensve and more economcal, due to elmnaton of permeate recompresson. Adsorpton mass transfer and equlbrum sotherm assumptons affect model accuracy; research s ongong towards ensurng robust dynamc optmsaton and quanttatve valdaton. Expermental valdaton of the HSS and the model results wth the use of a plot plant s the current goal that wll be vtal n order to use present optmsaton results for the desgn of a vable ndustral process. Acknowledgement Fnancal support from HYSEPS (EU SES019887) s gratefully acknowledged. References 1. Aknlab, C.O., M.Sc. Thess, Dept. of Chem. Engneerng, Imperal College London (006).. Bhde, B., Voskercyan, A., Stern, S., Journal of Membrane Scence 140(11): 7-49 (1998). 3. Cruz, P., Magalhaes, F., Mendes, A., AIChE Journal 51(5): (005). 4. Esteves, I., Mota, J., Desalnaton 148(1-3): (00). 5. Feng, X., et al., Chemcal Engneerng Scence 53(9): (1998). 6. Jan, S., et al., Separaton & Purfcaton Technology 33(1): 5-43 (003). 7. Jang, L., Fox, V.G., Begler, L.T., AIChE Journal 50(11): (004) 8. L, K., Acharya, D., Hughes, R., Journal of Membrane Scence 5(): (1990). 9. Mercea, P.V., Hwang, S., Journal of Membrane Scence 88(-3): (1994). 10. Naher, T., Ludwg, K. et al., Separaton Scence & Technology 3(9): (1997). 11. Nlchan, S., Ph.D. Thess, Dept. of Chem. Engneerng, Imperal College London (1997). 1. Ruthven, D., Gas Separaton & Purfcaton 5(1): 9-10 (1991). 13. Srcar, S., Golden, T., Separaton Scence & Technology 35(5): (000). 14. Srcar, S., Waldron, W., et al., Separaton & Purfcaton Technology 17(1): 11-0 (1999). 15. Zolandz, R., Flemng, G., n: Membrane Handbook, VNR, New York Cty, USA (199).