Format And Type Fonts CHEMICAL ENGINEERING TRANSACTIONS VOL. 45, 2015 A publication of The Italian Association of Chemical Engineering www.aidic.it/cet Guest Editors: Petar Sabev Varbanov, Jiří Jaromír Klemeš, Sharifah Rafidah Wan Alwi, Jun Yow Yong, Xia Liu Copyright © 2015, AIDIC Servizi S.r.l., ISBN 978-88-95608-36-5; ISSN 2283-9216 DOI: 10.3303/CET1545045 Please cite this article as: Mohd Nawi W.N.R., Wan Alwi S.R., Manan Z.A., Klemeš J.J., 2015, A new algebraic pinch analysis tool for optimising co2 capture, utilisation and storage, Chemical Engineering Transactions, 45, 265-270 DOI:10.3303/CET1545045 265 A New Algebraic Pinch Analysis Tool for Optimising CO2 Capture, Utilisation and Storage Wan Norlinda Roshana Mohd Nawi a,b , Sharifah Rafidah Wan Alwi* ,a,b , Zainuddin Abdul Manan a,b , Jiří Jaromír Klemeš c a Process Systems Engineering Centre (PROSPECT), Research Institute on Sustainable Environment, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia b Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia c Centre for Process Integration and Intensification – CPI2, Faculty of Information Technology, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary shasha@cheme.utm.my Optimal CO2 reduction planning can curb the rise in environmental emissions due to the increase in energy demand and utilisation. Carbon (more precisely, CO2) Capture and Storage (CCS) has been one of the proposed solutions to control CO2 emissions. However, mitigating CO2 emissions via CO2 storage in geological reservoirs without utilisation is neither a sustainable solution, nor really a clean technology option. This paper introduces a new algebraic method for targeting the optimum CO2 capture, utilisation and storage based on the Pinch Analysis approach. A new Total Site CO2 Integration concept is introduced. The concept is to capture CO2 with certain quality from various plants on the Total Site and inject it into CO2 headers. The CO2 headers are divided into certain composition ranges. The CO2 headers can satisfy the CO2 demands for various industries located along the headers, which require CO2 as its raw material. The CO2 can be further regenerated, and mixed as needed with pure CO2 generated from one or multiple centralised CO2 plant if required. The excess CO2 is to be sent to geological storage. The proper utilisation of CO2 will reduce the amount of CO2 needed to be stored. This will extend the geological carbon storage-life capacity. Aside from estimating CO2 utilisation, this method also allows an industrial site planner to identify the suitable industries that can act as CO2 sources or CO2 demands for a given region. 1. Introduction The increase of CO2 emissions induced by use of fossil fuels has initiated an urgent need for proper CO2 reduction planning that includes CO2 sequestration, utilisation and storage. Many studies dealt with carbon capture and storage (CCS) to mitigate climate change by capturing CO2 into geological sequestration (Diamante et al., 2014), biological fixation (Geerlings and Zevenhoven, 2013) or utilisation (Man et al., 2014). CCS is a tool for CO2 reduction in the atmosphere. It involves the capture of CO2 from an industrial plant and its storage in secure reservoirs, to enable the usage of fossil fuels while controlling the CO2 emitted into the atmosphere. CCS is an integrated process made up of three distinct parts; CO2 capture, transport and storage. Capture technology aims to produce a concentrated stream of CO2 that can be compressed, transported and stored. Transport of captured CO2 is mostly by pipeline, however it depends on the distance and cost. The sequestration of the captured carbon is the final part of the process (Oh, 2010). Earlier work in CCS by Tan et al. (2009) determines the CO2 emission target while minimising the need of power plant retrofit. The authors used a Pinch Analysis (PA) graphical methodology, which provides useful insights for the planning and optimisation of power generation. A study of CCS using Carbon Constrained Energy Planning (CCEP) was also demonstrated with insight and optimisation based targeting techniques for multi-period scenarios (Ooi et al., 2014). Related to CCS, Soundararajan et al. (2014) studied the carbon capture technology in order to improve the CO2 capture efficiency. The assessment of the CCS 266 however revealed that the technology not only demands major capital investments, it is also not suitable for ocean territories and when there is limited land for geological storage. CCS has merely been adopted as a transitional technology (Câmara et al., 2013). A derivative of CCS, namely CO2 capture, utilisation and storage (CCUS) is the potential technology to utilise captured CO2 as an alternative to mitigate climate change (Pérez-Fortes et al., 2014). Utilisation or conversion of the captured CO2 into value-added products, such as solvent and pharmaceutical products, has the potential to generate additional revenue and compensate part of the high cost of implementing the CCS technology. A new plant with CCS technology has an incremental cost of about 7 % for 25 % of CO2 avoidance (Lee and Hashim, 2014). Many challenges consequently exist in achieving the successful CO2 utilisation, including the development of technologies capable of economically fixing CO2 in stable products for indirect storage. The technological investigation to discover new applications and reaction, which do not use energy that exceed the CO2 utilised are needed to reduce the net CO2 emission (US DOE, 2014). Carbon capture and utilisation (CCU) on a coal gasification process has resulted in increased process carbon element efficiency and in carbon footprint reduction (Man et al., 2014). There are recent works on CO2 emission reduction that look into the potential CO2 reduction planning and management methods. Munir et al. (2012) have introduced Carbon Pinch Analysis (CPA) to target the minimum fresh carbon and carbon emission for stationary point sources in a refinery industrial park. The paper considered Carbon Management Hierarchy (CMH) in minimising the CO2 emissions. An algorithmic method called Generic Carbon Cascade Analysis (GCCA) technique was introduced by Manan et al. (2014) to systematically analyse the carbon minimisation options including direct reuse, source and demand manipulations, regeneration reuse and carbon sequestration. The work resulted in an accurate tool to set the minimum carbon emission target and maximum carbon recovery. The papers however do not consider the utilisation of specific CO2 headers or integration with the existing CCS planning and development. This paper presents a new algebraic technique and a procedure to obtain the total site target for the CO2 utilisation and storage integration. Total Site (TS) heat inetgration involves the integration of heat recovery among multiple processes and/or plants interconnected by common utilities on an industrial site. The method was introduced by Dhole and Linnhoff (1993) and further developed into TS heat recovery targeting by Klemeš et al. (1997). A comprehensive overview on the method developments in Total Site Heat Integration (TSHI) can be referred to Klemeš et al. (2013). The concept of TSHI has been adapted to the new Total Site Carbon Integration (TSCI) concept introduced in this work. Currently, there are CO2 header pipes being planned to be constructed in many regions to channel captured CO2 from industries to geological reservoirs. For example in China, CO2 sources from various industries located in different districts or provinces are identified to send their captured CO2 and sequester to the dedicated geological storage via pipe line transport (Global CCS Institute, 2014). The idea is, as CO2 utilisation technologies begins to mature, and as more industries which require different purity of CO2 as their demands are constructed, it will be possible for these industries to tap the CO2 from the constructed headers. This will subsequently reduce the amount of CO2 stored in the geological reservoirs and lengthen the reservoirs life time. Several questions remain to be addressed such as: 1) Can different CO2 purity headers be created based on the various industry carbon capture technologies? The charge for the industries to inject their CO2 into the higher purity headers will be less than the lower purity headers. (2) How will the different purity CO2 (sources) injected into the headers affect the overall purity of CO2 inside the header? (3) How can the amount of CO2 purity required by the industries (demands) be satisfied? Can a centralised pure CO2 generator plant be built to balance the CO2 purity required by the demands? And what shall the capacity be? (4) How much CO2 will be finally stored in the geological reservoirs after it has been utilised by the demands along the headers? The Carbon Total Site Problem Table Algorithm (CTS-PTA) has been developed to address all these issues. The tool can be used for CCUS planners to design future CO2 headers and develop proper CCUS policies and mechanisms to maximise the CO2 utilised and minimise the CO2 stored. 2. Methodology Following is the developed methodology for TSCI. 2.1 Step 1: Set the number of CCUS header for the region and decide its header CO2 purity Decide on the number of CCUS header for the region and the flue gas CO2 purity which needs to be transported along the pipe lines. For example, the first header (H1) can be set to only accept flue gas with CO2 purity which a geological sequestration (the final destination) can accept e.g. 80 to 100 %. The second header (H2) can be set at a lower purity for demands which do not need a high purity CO2. For example it can transport flue gas between 50 to 79.99 % CO2 purity. Since Header 2 flue gas cannot be 267 sent to a geological sequestration as the final destination (since its purity is lower than 80 %), the flue gas within this line must be fully consumed by the last demand at the end of its pipeline. This can be controlled by allowing only limited amount of sources to be injected into this header. 2.2 Step 2: Identify the CO2 sources and demands Identify the industries along the header which can capture CO2 (Sources). Obtain the sources gas flowrate (FT) and the gas CO2 purity (PCO2). Identify also the industries which can utilise CO2 (Demands). Obtain the demands FT and the minimum PCO2 it can accept. The amount of CO2 (FCO2) within the gas can be calculated by using Eq(1) as described by Munir et al. (2012). Other gases flowrate (FOG) such as N2, O2, CO, NOx and SOx can be calculated using Eq(2). T. 100 (1) T (2) 2.3 Step 3: Construct CO2 Total Site-Problem Table Algorithm (CTS-PTA) Construct the CTS-PTA to determine the amount of CO2 target based on TS concept. The procedure is as follows: i. Sources and demands are arranged based on its location along Header 1 and 2 from the beginning of the pipe line until the end of the pipe line. After the end of the Header 1 line, the remaining gas within Header 1 will be sent to the geological reservoir. The sources and demands number and the header the CO2 will be injected into or taken out for utilisation are listed in Columns 1 and 2. ii. PCO2 and FT from each sources and demands are listed in Columns 3 and 4. The demand flowrate is listed as negative values to indicate it is extracting the flue gas from the header, while the sources flowrate is listed as positive values to indicate it is adding more flue gas into the header. iii. FCO2 and FOG are determined using Eq(1) and Eq(2) and listed in Columns 5 and 6. iv. The next key step is to match the sources and sinks requirement by performing FT and FCO2 cascading for Header 1 first.  At the sources’ locations, FT and FCO2 for H1 are cumulated from the top to the bottom row starting from zero as shown in Columns 7 and 8 using Eq(3) and Eq(4). The header CO2 purity (PH1) after cumulating all the sources is calculated by using Eq(5) and listed in Column 9. (3) (4) (5)  At the demands’ locations, FT and FCO2 are cumulated from the top to the bottom row with FT,H1-D, FT,H2-D, FCO2,H1-D and FCO2,H2-D values as shown in Eq(6) and Eq(7). FT,H2-D and FCO2,H2-D calculations will be explained in Step v. The FT,H1-D and FCO2,H1-D values are derived from utilisation rule 1 or 2 equations as described next. + (6) + (7) Utilisation Rule 1: Demand requires a higher CO2 purity (PCO2,D,i) (e.g. 95 %) than the cumulated CO2 purity in Header 1 (PCO2,H1,i-1) (e.g. 87 %). This indicated the demand need to blend the header gas with pure CO2 which is taken from the centralised CO2 generator in order to satisfy the demand requirement. Eq(8) and Eq(9) are used to determine the amount of FCO2,H1-D (Column 10) and FT,H1-D (Column 11) supplied from Header 1 to the demand and Eq 10 is used to estimate the flowrate of pure CO2 (FCO2, FC-D) needed to satisfy the demand purity for H1 (Column 12). If ⁄ (8) (9) (10) Utilisation Rule 2: Demand requires equal or lower CO2 purity (PCO2,D,i) (e.g. 85 %) than the cumulated CO2 purity in Header 1 (PCO2,H1,i-1) (e.g. 87 %). In this case, FT from header 1 is directly supplied to demand, FT,H1-D (Column 11) as the purity demand requirement is fulfilled Eq(11). This is with the 268 assumption that the demand can accept equal or higher purity sources. FCO2,H1-D (Column 10) can be calculated from Eq(12). If , (11) (12) The last row for Cum FT and Cum FCO2 gives the minimum target of FT and FCO2 to be sent to geological storage for carbon mitigation initiative. The summation of Column 12 gives the total amount of pure CO2 which needs to be supplied by the centralised pure CO2 generator (FCO2,FC) as shown in Eq(13). ∑ (13) v. Next, the same procedures as iv are applied to perform the FT and FCO2 cascading for Header 2. However, the cumulative FT and FCO2 equation for Header 2 is calculated using Eq(14) and 15 as shown in Columns 13 and 14. (14) (15) For utilisation rule 1, instead of using pure CO2, the cleaner flue gas from Header 1 will be utilised. The amount of FT taken from Header 1 and Header 2 for satisfying a demand at Header 2 (FT,H2-D, FT,H1-D) can be calculated using Eq(16) and Eq(17). The other equations are similar by replacing H1 with H2. FT,H2-D,i = (16) FT,H1-D,i = (17) As stated previously, there should not be any excess FT and FCO2 at the last row of Cum FT,H2 and Cum FCO2,H2. Hence, part of the sources (preferably the one with lower purity) into Header 2 should be reduced until the last row of Cum FT,H2 and Cum FCO2,H2 gives a zero value. 3. Case study The new CTS-PTA method is illustrated using a hypothetical case study. The source and demand data for this case study is listed in Table 1. Table 1: Data for CO2 sources and demands. Source (S)/ Demand (D) Description PCO2, % FT, t/h FCO2, t/h FOG, t/h S1 Natural gas power plant 88 179.9 158.3 21.6 S2 Coal power plant 85 92.9 79.0 13.9 S3 Refinery plant 60 100.0 60.0 40.0 S4 Oil power plant1 80 118.1 94.5 23.6 S5 Oil power plant2 80 118.1 94.5 23.6 D1 Beverage plant 99 50.0 49.5 0.5 D2 Methanol production 50 83.3 41.7 41.7 D3 Enhanced oil recovery (EOR) 80 208.3 166.6 41.7 D4 Chemical Plant 70 20.0 14.0 6.0 Header 1 (H1) was set for purity range between 80 to 100 % and Header 2 (H2) was set for purity range between 50 to 79.99 %. From Table 1, S1, S2, S4 and S5 can supply CO2 gas to H1, while S3 to H2. D1 and D3 can extract CO2 gas from H1, while D2 and D4 can extract gas from H2 and H1. Table 2 shows the CTS-PTA for the case study. Based on the CTS-PTA, the minimum amount of remaining CO2 gas to be sent to geological reservoirs (FT,ST) is 289.1 t/h. By summing Column 12, the centralised pure CO2 generator needs to generate 46.7 t/h of CO2. From Table 2b, it can be seen there are excess Cum FT,H2 at the last row. As Header 2 cannot have excess, this value is deducted with a source from H2 i.e. S3. Instead of injecting 100 t/h of S3, only 94.9 t/h is injected to get the last row of Cum FT,H2 to be zero. This is 269 also the pinch point of the system. Note that prior to considering TSCI, the CO2 (e.g. S3 with FT,S3 = 94.9 t/h) from lower purity (less than 80 %), which cannot be stored might still be emitted to the environment. The amount of CO2 gas sent to geological reservoirs will also be higher at 509.1 t/h if utilisation is not being considered. The new TSCI concept has helped reduce 43 % of CO2 to be stored. Table 2a: CTS-PTA for Case Study 1. 1 2 3 4 5 6 7 8 9 10 11 i S/ D Hea- der PCO2,S/D % FT,S/D, t/h FCO2,S/D t/h FOG,S/D t/h Cum FT,H1 t/h Cum FCO2,H1 t/h PCO2,H1 FCO2,H1-D t/h FT,H1-D t/h 1 S1 H1 88 179.9 158.3 21.6 179.9 158.3 0.88 2 S2 H1 85 92.9 79.0 13.9 272.9 237.3 0.87 3 S3 H2 60 100.0 60.0 40.0 272.9 237.3 0.87 4 S4 H1 80 118.1 94.5 23.6 391.0 331.8 0.85 5 D1 H1 99 -50.0 -49.5 -0.5 -2.8 -3.3 387.7 329.0 0.85 6 D2 H2 50 -83.3 -41.7 -41.7 387.7 329.0 0.85 7 S5 H1 80 118.1 94.5 23.6 505.8 423.5 0.84 8 D3 H1 80 - 208.3 -166.6 -41.7 -174.4 -208.3 297.5 249.1 0.84 9 D4 H2 70 -20.0 -14.0 -6.0 -7.1 -8.4 FT,ST = 289.1 FCO2,ST = 242.01 PCO2,ST = 0.84 Table 2b: CTS-PTA for Case Study 1 (continue). 1 4 12 13 14 15 16 17 i S/D FT, t/h FCO2, FC-D t/h Cum FT,H2 t/h Cum FCO2,H2 t/h PCO2,H2 FCO2,H2-D t/h FT,H2-D, t/h 1 S1 179.9 0.0 0.0 0 2 S2 92.9 0.0 0.0 0 3 S3 100.0 100.0 60.0 0.60 4 S4 118.1 100.0 60.0 0.60 5 D1 -50.0 46.7 100.0 60.0 0.60 6 D2 -83.3 -50.0 -83.3 16.7 10.0 0.60 7 S5 118.1 16.7 10.0 0.60 8 D3 -208.3 16.7 10.0 0.60 9 D4 -20.0 -6.9 -11.6 5.1 3.0 0.60 Reduce to 94.9 Excess 270 4. Conclusion A new algebraic targeting method for Total Site Carbon Integration (TSCI) known as CTS-PTA has been developed. A new concept of CO2 integration which maximises the carbon capture, utilisation and storage have been introduced. The algebraic targeting method has been applied to a hypothetical case study to determine the potential CO2 exchange by using CO2 headers at different purities, and a centralised pure CO2 generator. Application of the new technique has resulted in 43 % reduction of carbon storage. The targeting technique enables planners to conduct further analysis and feasibility studies of CCUS system. Further works can include analysis of more scenarios and techno-economic study. Acknowledgement The authors would like to thank the Ministry of Higher Education Malaysia and Universiti Teknologi Malaysia for providing the research funds for this project under the Vote No. Q.J130000.2544.07H45, and acknowledge the financial support of the Hungarian Project TÁMOP-4.2.2.B-15/1/KONV-2015-0004 "A Pannon Egyetem tudományos műhelyeinek támogatása". References Câmara G., Andrade C., Silva Júnior A., Rocha P., 2013, Storage of carbon dioxide in geological reservoirs: Is it a cleaner technology?, Journal of Cleaner Production, 47, 52-60. Dhole V.R, Linnhoff B., 1993, Total Site Targets for Fuel, Co-generation, Emission and Cooling. Computers and Chemical Engineering, 17, S101–S109. Diamante J.A.R., Tan R.R., Foo D.C.Y., Ng D.K.S., Aviso K.B., Bandyopadhyay S., 2014, Unified pinch approach for targeting of carbon capture and storage (CCS) systems with multiple time periods and regions, Journal of Cleaner Production, 71, 67-74. Geerlings H., Zevenhoven R., 2013, CO2 mineralisation-bridge between storage and utilisation of CO2. Annu Rev Chem Biomol Eng, 4, 103-17. Global CCS Institute, 2014, The global status report accessed 13.02.2015. Klemeš J., Dhole V.R., Raissi K., Perry S.J., Puigjaner L., 1997, Targeting and Design Methodology for Reduction of Fuel, Power and CO2 on Total Site. Applied Thermal Engineering, 7 , 993–1003. Klemeš J J., Varbanov P.S., Kravanja, Z., 2013, Recent Developments in Process Integration, Chemical Engineering Research and Design, 91, 2037-2053. Lee M.Y., Hashim H., 2014, Modelling and optimisation of CO2 abatement strategies. Journal of Cleaner Production, 71, 40-47. Man Y., Yang S., Xiang D., Li X., Qian Y., 2014, Environmental impact and techno-economic analysis of the coal gasification process with/without CO2 capture, Journal of Cleaner Production, 71, 59-66. Manan Z.A., Wan Alwi S.R., Sadiq M.M., Varbanov P., 2014, Generic Carbon Cascade Analysis technique for carbon emission management, Applied Thermal Engineering, 70, 1141-1147. Munir S.M., Manan Z.A., Wan Alwi S.R., 2012, Holistic carbon planning for industrial parks: a waste-to- resources process integration approach, Journal of Cleaner Production, 33, 74-85. Oh T.H., 2010, Carbon capture and storage potential in coal-fired plant in Malaysia—A review, Renewable and Sustainable Energy Reviews, 14, 2697-2709. Ooi R.E.H., Foo D.C.Y., Tan R.R., 2014, Targeting for carbon sequestration retrofit planning in the power generation sector for multi-period problems, Applied Energy, 113, 477-487. Pérez-Fortes M., Bocin-Dumitriu A., Tzimas E., 2014, Techno-Economic Assessment of Carbon Utilisation Potential in Europe, Chemical Engineering Transactions, 39, 1453-1458, DOI: 10.3303/CET1439243. Soundararajan R., Gundersena T., Ditarantob M., 2014, Oxy-Combustion Coal Based Power Plants: Study of Operating Pressure, Oxygen Purity and Downstream Purification Parameters, Chemical Engineering Transactions, 39, 229-234, DOI: 10.3303/CET1439039. Tan R.R., Ng D.K.S., Foo D.C.Y., 2009, Pinch Analysis Approach to Carbon-constrained Planning for Sustainable Power Generation, Journal of Cleaner Production, 17, 940-944. US DOE (Department of Energy), 2014, CO2 Utilization Focus Area accessed 20.10.2014.