Format And Type Fonts CHEMICAL ENGINEERING TRANSACTIONS VOL. 39, 2014 A publication of The Italian Association of Chemical Engineering www.aidic.it/cet Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Peng Yen Liew, Jun Yow Yong Copyright © 2014, AIDIC Servizi S.r.l., ISBN 978-88-95608-30-3; ISSN 2283-9216 DOI: 10.3303/CET1439004 Please cite this article as: Deng C., Zhou Y., Li Y., Feng X., 2014, Flowrate targeting for interplant hydrogen networks, Chemical Engineering Transactions, 39, 19-24 DOI:10.3303/CET1439004 19 Flowrate Targeting for Interplant Hydrogen Networks Chun Deng* a , Yuhang Zhou a , Yantao Li b , Xiao Feng c a State Key Laboratory of Heavy Oil Processing, College of Chemical Engineering, China University of Petroleum, Beijing, 102249, China b Karamay petrochemical company design, Karamay, Xinjiang Autonomous Region, China, 834003 c New Energy Research Institute, China University of Petroleum, Beijing, 102249, China chundeng@cup.edu.cn In this paper, the improved problem table (IPT) is referred to locate the flowrate targets of interplant hydrogen conservation network. Firstly, the flowrate targets for individual hydrogen networks are located and the purge gas streams can be identified via IPT. Next, the IPT is utilized to determine the flowrate targets for the overall interplant hydrogen network. The arising problems with multiple resources and purge gas streams can be coped with by IPT. One example is solved to show the effectiveness and applicability of the proposed approach. The results show that the flowrate of hydrogen utility (0.01) for Plant B is reduced by 1,784 Nm 3 /h and the hydrogen utility (0.05) for Plant A is totally conserved. 1. Introduction The processing ratio of high-sulfur, heavy and poor-quality crude oil has been increasing yearly, i.e. Sinopec imported high sulphur crude oil is up to 70 Mt in 2010 and the year-on-year growth reached 17 %. On the other hand, tighter environmental regulations and policies on sulphide and aromatics content are leading to higher oil products quality requirements for refineries. In order to improve the oil products quality, refineries has to increase the depth of hydrotreating and hydrocracking processes, which consume large amount of fresh hydrogen. On the other hand, the operation capacity of traditional continuous catalyst reforming, an important hydrogen producing process, is reduced because of the shrinking market demand for reforming products. Therefore, the gap between these consuming and producing processes aggravates the fresh hydrogen shortage in refineries, making fresh hydrogen a more and more expensive resource for modern refineries. It is quite necessary to enhance the hydrogen network management in the inner refinery plant. However, the recovered hydrogen is sometimes far insufficient to satisfy the sharp increasing demand. Instead of introducing hydrogen production process to produce fresh hydrogen, it is an attractive alternative to recover the hydrogen from other plants (i.e. fertilizer, ethylene plants) in the petrochemical industrial park. Hence, there is a necessity to address the synthesis of interplant hydrogen system. Generally, the methodologies in previous work on the synthesis and retrofit of refinery hydrogen network can be classified into two aspects: pinch technique, such as, hydrogen surplus diagram (Alves and Towler, 2002), gas cascade analysis (Foo and Manan, 2006), improved limiting composite curve (Agrawal and Shenoy, 2006) and mathematical programming approaches, such as first superstructure model with pressure constraint (Hallale and Liu, 2001), systematic methodology for the selection of appropriate purifiers (Liu and Zhang, 2004), state-space superstructure (Liao et al., 2010), multi-component and integrated flash calculation (Jia and Zhang, 2011), hydrogen sulphide removal process embedded optimisation model (Zhou et al., 2012), total exergy consumption of the hydrogen utility and compressor work (Wu et al., 2012), strategy for hydrogen integration in petroleum refining (Smith et al., 2012), and key factor analysis for hydrogen integration (Deng et al., 2013). However, few researches have been reported on the synthesis of interplant hydrogen network in the literature. Gas cascade analysis is utilized to locate the interplant hydrogen conservation network with unassisted integration scheme (Chew et al., 2010) and assisted integration scheme (Chew et al., 2010). In the flowrate targeting for interplant hydrogen networks, the arising problems, such as network with multiple-resources and purge gas stream identification, are mailto:chundeng@cup.edu.cn 20 coped with via their former proposed techniques, water cascade analysis (Foo, 2007) and waste stream identification(Ng et al., 2007). In this paper, the Improved Problem Table - IPT (Deng and Feng, 2011) is explored to target the flowrate of interplant hydrogen network. Flowrate targets for individual hydrogen networks are determined and the purge gas streams for each hydrogen network can be identified via IPT firstly. Next, the improved problem table is employed to determine the flowrate targets for the overall interplant hydrogen network. One literature example is analysed to illustrate the applicability of the proposed approach. 2. Problem statement The problem can be stated as follows. Given several refinery or chemical plants, there is a set of hydrogen-consuming utilities in each plant, their outlet streams are treated as a set of internal hydrogen sources ( i NSR ) while inlet streams treated as a set of hydrogen sinks ( j NSK ). Each hydrogen source is specified by its outlet flow rate ( SRi F ) and outlet hydrogen purity ( SRi y ). Each hydrogen sink has inlet flow rate ( SKj F ) and lower limit of inlet hydrogen purity ( lim SKj y ). Hydrogen sources can be reused/recycled to fulfil the requirements of hydrogen sinks. Besides, a set of external hydrogen sources or hydrogen utilities ( u NHU ) are needed for supplement. To reduce the common dosage of hydrogen, the internal hydrogen sources would be recycle/reused as much as possible. And the surplus hydrogen sources are discharged to fuel system. For the interplant integration scheme of three refinery or chemical plants, the surplus hydrogen sources discharged from Plant A can be allocated to Plant B, and high purity of hydrogen from Plant B would be allocated to Plant C, and surplus hydrogen sources would be distributed from Plant C to Plant A. This paper aims to target the minimum hydrogen utility flow rates for interplant hydrogen networks. 3. Flowrate targeting for interplant hydrogen networks by IPT In this section, IPT is referred to locate the minimum flow rates of hydrogen utilities for individual plants and interplants (two and three plants).The limiting data shown in Table 1 for three plants are extracted, Plant A (Alves and Towler, 2002), Plant B (Hallale and Liu, 2001) and Plant C (Foo and Manan, 2006). Note that all the flowrate units are unified to be Nm 3 /h. 3.1 Flowrate targeting for individual hydrogen networks The minimum flow rates of hydrogen utilities for individual plants (i.e. Plant A) are targeted by IPT and the detailed steps for IPT can be referred to the literature (Deng and Feng, 2011). Step 1: Tabulate all purities of hydrogen sources and sinks (data for Plant A shown in Table 1) in decreasing order in the first column (Table 2). Do not repeat the same purity that occurs more than once. Add one more arbitrary purity at the bottom of the column so that it is the smallest value. The arbitrary purity serves to provide an end point and facilitates the plotting of the last segment of the limiting composite curve. The second column shows impurities that is 1- y. Step 2: Tabulate the net flow rates in the third column (Table 2) by subtracting the sum of the flow rates of the hydrogen sources from the sum of the flow rates of hydrogen sinks in each purity interval. Besides, the net flow rate corresponds to the reciprocal of the slope of a segment on the limiting composite curve. And the last value in the third column (Table 2) which is obtained by subtracting the sum of all flow rates of the hydrogen sources from the sum of all flow rates of the hydrogen sinks determines the minimum net flow rate of external hydrogen sources for the network. For a given hydrogen network, the value is a constant. For Plant A, the minimum net flow rate for external hydrogen sources is 13,410 Nm 3 /h. Step 3: Tabulate the net mass loads in the fourth column (Table 2). The net mass loads for each purity internal are the products of the net flow rates and the purity differences of the corresponding intervals. Step 4: Tabulate the cumulative mass loads in the fifth column (Table 2). The first row has no cumulative mass load so that it equals zero. The cumulative mass loads of other rows are accumulated by the net mass loads above the row. The impurity column can be plotted against the cumulative mass load column to obtain the limiting composite curve and it is omitted for simplification. Step 5: Tabulate the possible hydrogen supply flow rates for each purity ( v u FHU ) in the sixth column using Eq(1). v cum HUu HUu M F y y      (1) 21 Table 1: Limiting hydrogen data Hydrogen Network Hydrogen Sources Purity (fraction) Flow rate (Nm 3 /h) Hydrogen Sinks Purity (fraction) Flow rate (Nm 3 /h) A SRU 0.93 50,303 HCU 0.8061 201,197 CRU 0.8 33,530 NHT 0.7885 14,531 HCU 0.75 145,305 DHT 0.7757 44,707 NHT 0.75 11,177 CNHT 0.7514 58,117 DHT 0.73 27,942 CNHT 0.7 36,885 Fresh supply A 0.95 22,353 (current) B S1 0.91 390,705 D1 0.928 446,520 S2 0.85 558,150 D2 0.8757 669,780 Fresh supply B 0.99 223,260 (current) C SR1 0.983 6,451 SK1 0.999 9,677 SR2 0.85 6,048 SK2 0.986 2,242 SR3 0.96 2,302 SK3 0.975 6,451 SR4 0.95 6,451 SK4 0.975 4,838 SR5 0.9 9,677 SK5 0.97 9,677 SR6 0.983 3,226 SK6 0.9 12,096 SR7 0.975 6,451 Fresh supply C 0.999 Table 2: Implementation of IPT for Plant A Purity (fraction) Impurity (fraction) Net flow rate (Nm 3 /h) Net load (Nm 3 /h) Cumulative load (Nm 3 /h) Fresh supply A (Nm 3 /h) Flow rate above Pinch (Nm 3 /h) Flow rate for Purge gas stream (Nm 3 /h) 0.95 0.05 0.93 0.07 0.8061 0.1939 -50,303 -6,233 -6,233 -43,312 0.8 0.2 150,894 920 -5,312 -35,414 0.7885 0.2115 117,363 1,350 -3,962 -24,535 0.7757 0.2243 131,895 1,688 -2,274 -13,048 0.7514 0.2486 176,602 4,291 2,017 10,157 0.75 0.25 234,719 329 2,346 11,729 0.73 0.27 78,237 1,565 3,911 17,775 0.7 0.3 50,295 1,509 5,419 21,678 8,267 0.65 0.35 13,410 671 6,090 20,300 13,410 where cum M   and y  denotes the cumulative mass load and purity concentration for vth purity level and HUu y denotes the purity of uth external hydrogen source. The maximum value in sixth column of Table 2 is 21,678 Nm 3 /h (=268.82 mol/s) and it is marked in bold. It is bigger than the minimum net flow rate (13,410 Nm 3 /h) determined in Step 2 and the maximum value (21,678 Nm 3 /h) is considered to be the minimum flow rate of fresh hydrogen, and the corresponding impurity concentration (0.3) is identified as the pinch impurity concentration. The result is agree with that reported in the literature(Alves and Towler, 2002). Negative values in the sixth column indicate that internal hydrogen sources can meet the demand of hydrogen sinks without the supply of external fresh hydrogen sources. Besides, if the maximum value in the sixth column is smaller than the minimum net flow rate determined in Step 2, the minimum net flow rate is considered as the the minimum flow rate of fresh hydrogen for the network. Step 6 (Only for the network with multiple external hydrogen sources): Tabulate all possible flow rates of other external hydrogen sources in the following columns. Step 7: Identify purge gas streams discharged from the network. On the pinch (the impurity concentration is 0.3), the accumulated hydrogen flow rate is 21,678 Nm 3 /h. It can be considered as an internal hydrogen 22 source with the impurity of 0.3. Then for each impurity interval above 0.3, the required flowrates can be calculated via Eq.(2) and all possible flow rates for are listed in the seventh column of Table 2 and the maximum value (13,410 Nm 3 /h) determines the target. Therefore, only 13,410 Nm 3 /h of hydrogen source at the impurity of 0.3 needs to be distributed to the system and the residual flow rate 8,268 Nm 3 /h (=21,678 Nm 3 /h –13,410 Nm 3 /h) is identified as the purge gas stream WH1 (0.3). pinch arbitrarycum cum pinch pinch pinch M M F y y y y y           (2) Step 8: Use nearest neighbours algorithm (NNA)(Prakash and Shenoy, 2005) to design the hydrogen network. The hydrogen network for Plant A consumes 21,678 Nm 3 /h of hydrogen utility (0.05) and discharge 8,267 Nm 3 /h of purge gas stream (0.3), which are identical to those calculated by IPT. Similarly, IPT is used to target the hydrogen network for Plants B and C. For Plant B, the minimum hydrogen utility (impurity of 0.01) is located as 204,125 Nm 3 /h with pinch impurity concentration (0.15) and the purge gas stream is identified as 36,680 Nm 3 /h (0.15). For Plant C, the minimum hydrogen utility (impurity of 0.001) is located as 10,097 Nm 3 /h with pinch impurity concentrations (0.017 and 0.05) and the purge gas streams are identified as 2,497 Nm 3 /h (0.05) and 4,838 Nm 3 /h (0.15). 3.2 Flowrate targeting for interplant hydrogen networks Firstly, the interplant integration between two plants is explored. For Plants A-B, the purge gas stream from Plant B is identified as 36,680 Nm 3 /h (0.15). The impurity concentration (0.15) of purge gas stream of Plant B is lower than the pinch impurity concentration for Plant A (0.3). Therefore, the purge gas stream of Plant B can be allocated to Plant A and the minimum flowrate for purge gas stream of Plant B is located as 36,130 Nm 3 /h. The purge gas stream of Plant B is sufficient and the fresh supply A is totally conserved. The flow rates for hydrogen utilities can be further reduced from 21,678 Nm 3 /h (0.05) + 204,125 Nm 3 /h (0.01) to 204,125 Nm 3 /h (0.01). The interplant hydrogen network for Plants A-B can be synthesized by NNA (Prakash and Shenoy, 2005). Similarly, the interplant integration for Plants B-C and Plants A-C are investigated and the IPTs and interplant hydrogen networks are omitted for brevity. Next, the interplant integration among three plants is investigated. The purge gas streams from Plants B-C are identified as 4,838 Nm 3 /h (0.15) (Plant C) + 37,393 Nm 3 /h (0.15) (Plant B). The impurity concentrations for the purge gas streams are less than the pinch impurity (0.3) of Plant A. Therefore, the purge gas streams of Plants B-C can be allocated to Plant A and the minimum flowrate for purge gas stream of Plants B-C is located as 36,130 Nm 3 /h. The interplant hydrogen network for Plants A-B-C as shown in Figure 1 can be synthesized by NNA (Prakash and Shenoy, 2005) and it is marked as Scenario 1. The flow rates for hydrogen utilities are targeted as 10,097 Nm 3 /h (0.001, Plant C) + 202,341 Nm 3 /h (0.01, Plant B). The purge gas streams are identified as 6,101 Nm 3 /h (0.15, Plant B) + 22,710 Nm 3 /h (0.3, Plant A). In addition, the purge gas stream from Plants C-A is identified as 10,203 Nm 3 /h (0.3) and there are two hydrogen streams from Plant C to Plant A. And the purge gas stream from Plant B is identified as 36, 680 Nm 3 /h (0.15), which is less than the pinch impurity concentration (0.3) of Plant A. Therefore the purge gas stream of Plant B can be allocated to Plant A and the minimum flowrate for purge gas stream of Plant B is located as 27,130 Nm 3 /h. The interplant hydrogen network for Plants A-B-C as shown in Figure 2 can be synthesized by NNA(Prakash and Shenoy, 2005) and it is marked as Scenario 2. The flow rates for hydrogen utilities are targeted as 10,097 Nm 3 /h (0.001, Plant C) + 204,125 Nm 3 /h (0.01, Plant B). The purge gas streams are identified as 9,550 Nm 3 /h (0.15, Plant B) + 21,055 Nm 3 /h (0.3, Plant A). Besides, the interplants B-A would be integrated with Plant C. The purge gas streams of Plant C would allocated to Plant B or Plant A. If the purge gas streams of Plant C is distributed to Plant B, the results and interplant network are identical to those in Scenario 1. Otherwise, the results and interplant network are identical to those in Scenario 2. Compare the results of Scenario 1 with those of Scenario 2, in Scenario 1, cross-plant gas streams are 2,497 Nm 3 /h (0.05, from Plant C to Plant B), 4,838 Nm 3 /h (0.15, from Plant C to Plant A) and 31,292 Nm 3 /h (0.15, from Plant B to Plant A). In Scenario 2, cross-plant gas streams are 2,497 Nm 3 /h (0.05) and 4,838 Nm 3 /h (0.15) (from Plant C to Plant A), and 27,130 Nm 3 /h (0.15, from Plant B to Plant A). Due to the different direction of 2,497 Nm 3 /h (0.05) of cross-plant gas stream (from Plant C to Plant B in Scenario 1 while from Plant C to Plant A in Scenario 2), Plant B consumes 1,784 Nm 3 /h of hydrogen utility in Scenario 1 less than that in Scenario 2. It means that Scenario 1 is better than Scenario 2. In addition, compared with the flowrate targets for individual hydrogen network, the flowrate targets for overall hydrogen network is reduced from 10,097 Nm 3 /h (0.001, Plant C) + 204,125 Nm 3 /h (0.01, Plant B) + 21,678 Nm 3 /h (0.05, Plant A) to 10,097 Nm 3 /h (0.001, Plant C) + 202,341 Nm 3 /h (0.01, Plant B). For P F 23 Plant B, the flowrate of hydrogen utility (0.01) is reduced by 1,784 Nm 3 /h. Besides, the hydrogen utility (0.05) for Plant A is totally conserved. Fresh Supply C SK1 99.9% 9677 SK2 98.6% 2242 SK3 97.5% 6451 SK4 97.5% 4838 SK5 97% 8064 SK6 90% 12096 SR1 98.3% 6451 SR6 98.3% 3226 SR7 97.5% 6451 SR3 96% 2302 SR4 95% 6451 SR5 90% 9677 SR2 85% 6048 9677 6451 420 1822 1683 3155 1474 619 3226 2745 9677 1209 1210 4838 95% 2497 99.9% 10097 Reactor1 Reactor2 Fresh Supply B 92.8% 446520 87.57% 669780 99% 202341 99219 91% 344804 91% 45901 103122 85% 520757 85% 37393 SRU CRU HCU NHT DHT CNHT 78.85% 14531 80.61% 201197 77.57% 44707 93% 50303 75.14% 58117 80% 33530 85% 36130 22326 75% 128568 5594 75% 8937 8210 75% 16737 75% 2240 70% 22710 70% 14175 18417 15113 73% 21384 73% 6548 31292 6101 Figure 1: Interplant hydrogen network for A-B-C (Scenario 1) Fresh Supply C SK1 99.9% 9677 SK2 98.6% 2242 SK3 97.5% 6451 SK4 97.5% 4838 SK5 97% 8064 SK6 90% 12096 SR1 98.3% 6451 SR6 98.3% 3226 SR7 97.5% 6451 SR3 96% 2302 SR4 95% 6451 SR5 90% 9677 SR2 85% 6048 9677 6451 420 1822 1683 3155 1474 619 3226 2745 9677 1209 1210 85% 4838 95% 2497 SRU CRU HCU CNHT NHT DHT 75% 126710 80.61% 201197 93% 50303 80% 33530 19309 75.14% 58117 70% 15830 2335 3108 44860 75% 247 75% 11177 73% 23312 78.85% 14531 77.57% 44707 14221 70% 21055 99.9% 10097 75% 18349 Fresh supply B Reactor1 Reactor2 100470 103655 99% 204125 91% 346050 85% 521470 91% 44655 92.8% 446520 87.57% 669780 85% 36680 27130 9550 73% 4629 Figure 2: Interplant hydrogen network for A-B-C (Scenario 2) 24 4. Conclusions In this paper, the flowrate targets for interplant hydrogen conservation networks are located via the former proposed improved problem table (IPT). Firstly, the flowrate targets for individual hydrogen networks are determined and the purge gas streams are identified via IPT. Next, the improved problem table is utilized to locate the flowrate targets for the overall interplant hydrogen network. The network with multiple resources and purge gas streams can be deal with by IPT. The example with three plants illustrates the effectiveness and applicability of the proposed approach. The results show that the flowrate of hydrogen utility (0.01) for Plant B is reduced by 1,784 Nm 3 /h and the hydrogen utility (0.05) for Plant A is totally conserved. Acknowledgements Financial support provided by the National Basic Research Program of China (No. 2012CB720500) and National Natural Science Foundation of China united with China National Petroleum Corporation (No. U1162121) are gratefully acknowledged. The research is also supported by Science Foundation of China University of Petroleum, Beijing (No.YJRC-2011-08). References Agrawal V., Shenoy U.V., 2006, Unified conceptual approach to targeting and design of water and hydrogen networks, AIChE Journal, 52, 1071-1082. Alves J.J., Towler G.P., 2002, Analysis of refinery hydrogen distribution systems, Industrial & Engineering Chemistry Research, 41, 5759-5769. Chew I.M.L., Foo D.C.Y., Ng D.K.S., Tan R.R., 2010, Flowrate Targeting Algorithm for Interplant Resource Conservation Network. Part 1: Unassisted Integration Scheme, Industrial & Engineering Chemistry Research, 49, 6439-6455. 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