OPTIMIZATION OF CRYOGENIC CARBON CAPTURE AND LNG PROCESSES BY SHAFTWORK TARGETING AND MATHEMATICAL PROGRAMMING

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1 OPTIMIZATION OF CRYOGENIC CARBON CAPTURE AND LNG PROCESSES BY SHAFTWORK TARGETING AND MATHEMATICAL PROGRAMMING Orakotch Padungwatanaroj a, Kitipat Siemanond a : a The Petroleum and Petrochemical College, Chulalongkorn University, Bangkok, Thailand Keywords: Optimization, Exergy analysis, Mathematical modelling, Low-temperature process ABSTRACT Nowadays, low-temperature process; which is called sub-ambient condition; plays a fundamental role in many industrial processes using refrigeration system. To deal with subambient condition, large amount of energy is required for shaft work and operating cost. The combination of pinch and exergy analysis helps identify the potential to minimize shaft work in low-temperature process because the strength point of this method is that all process stream properties of temperature, enthalpy, and exergy are considered as a graphical presentation. In this research, there are two approaches of energy minimization which are shaft work targerting by graphical method (Linnhoff, 1992) and mathematical programming by using Non-Linear Programming model (NLP) (Colmenares and Seider, 1989). Cryogenic carbon capture and liquefied natural gas (LNG) process (Fazlollahi, 2015) is chosen as a base case of this work because LNG is worthy utilized as a refrigerant for capturing carbon dioxide in exhausted flue gas from power plant. According to the result, shaft work is reduced comparing with base case, by using both methods. *p.orakotch@gmail.com INTRODUCTION Low-temperature industrial process is the process using refrigeration system. The concerning problems of process related to sub-ambient condition are high energy requirement and operating cost. So, all industrial plants try to save an energy by using several methods. Normally, there are two systematic design methods. The first one is based on graphical diagrams of thermodynamics and the other one is based on mathematical programming. Pinch analysis; also known as heat integration; is a practical method for design and improvement of hot-and-cold utility system to reach the lowest energy consumption. Composite curves and grand composite curves are simple graphical tools for pinch analysis which identify a minimum hot and cold utilities, efficiently. Another method is an exergy analysis which all stream properties are concerned (temperature, pressure and composition). Nevertheless, there are some limitations which are an analysis of equipment unit level and no association between exergy and cost. Then, the combination of pinch analysis and exergy analysis (Linnhoff, 1992) was key success factor for minimizing energy requirements in subambient processes. Moreover, mathematical programming (Colmenares and Seider, 1989) which helps design the refrigeration system is also applied to this work as well. The model is NLP optimization model and objective function is shaft work minimization. In this research, the combination of pinch analysis and exergy analysis Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 1

(Linnhoff, 1990) and mathematical programming (Colmenares and Seider, 1989) were applied to reduce the energy requirement of cryogenic carbon capture and LNG process (Fazlollahi, 2015) as shown in

Therefore, the objective of this research is to optimize the process in order to get the minimal shaft work. EXPERIMENTAL A.

2 (Linnhoff, 1990) and mathematical programming (Colmenares and Seider, 1989) were applied to reduce the energy requirement of cryogenic carbon capture and LNG process (Fazlollahi, 2015) as shown in Figure1. This process was designed with heat exchangers and refrigeration system by ASPEN plus 8.8 program and GAMS. Therefore, the objective of this research is to optimize the process in order to get the minimal shaft work. EXPERIMENTAL A. Graphical method Figure1: Cryogenic carbon capture and LNG process Pinch analysis is combined with exergy analysis by converting composite curves (CCs) and grand composite curve (GCC) in form of temperature versus enthalpy to exergy composite curves (ECCs) and exergy grand composite curve (EGCCs) in term of Carnot factor (η) vesus enthalpy. The equation of Carnot factor (η) and temperature is shown in equation (1). (Linnhoff, 1990) (1) W is shaft work, is cooling duty by refrigeration system, c is the Carnot efficiency and T 0 is the environment temperature. For overall exergy balance in sub-ambient process, exergy supplied to heat exchanger network (HEN) is equal to summation of exergy supplied to process and exergy loss in HEN. This method helps design the process by manipulating refrigeration system until the area between hot and cold composite curves in ECC gets closer to each other, resulting in reduced exergy loss. EGCC also helps design the process as well and is better than using ECCs because EGCC can identify level of refrigerant which is suitable for temperature ranges. Thus, hot and cold utilities in process are adjusted until the shaded area ((σt 0 ) HEN) ), proportional to exergy loss, gets the minimum value. Thus, the reduction of shaft work is ( ) (2) where ex is the exergetic efficiency of refrigeration system and ( ) is the reduction of shaded area. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 2

Refrigeration level Figure2: Exergy Composite curve and Exergy grand composite curve B.

The objective function consists of total shaft work of refrigeration system with equality and inequality constraints.

The objective function is given by Figure3: Simple refrigeration model For simple refrigeration ( TC) (3) For cascade refrigeration ( CT) + (4) which

3 Refrigeration level Figure2: Exergy Composite curve and Exergy grand composite curve B. Mathematical modelling The non-linear programming model (NLP) for refrigeration system is applied to cryogenic carbon capture and LNG process. The objective function consists of total shaft work of refrigeration system with equality and inequality constraints. To formulate NLP model, these following definitions and equations must be defined. The objective function is given by Figure3: Simple refrigeration model For simple refrigeration ( TC) (3) For cascade refrigeration ( CT) + (4) which approximately shaft work is shown in equation (5) FR CpR (hac hbc ); (5) Condenser duty and evaporator duty equations are represented in equation (6) to (9) For simple refrigeration Q FR (TRCDO TRCDI ); (6) Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 3

4 η η Q FR (TRO TRI ); (7) For cascade refrigeration Q FR (TRCDO TRCDI ); (8) Q FR (THO THI ) + Q ; (9) Heat balances of hot stream I in interval J D(I, J ) D(I, J ) + SU (K, S(I, K, J )) R(I, J ); (10) Heat balances of hot stream I in interval J SU (I, S(I, K, J ) P(K, J ); (11) Outlet refrigerant temperature of evaporator (Q,, /FR CpR ) + TRI TRO ; (12) Outlet temperature of compressor TRCO( ) TRO( ) ( + ), (13) Enthalpy and other properties equation are applied by using simulation data form Aspen Hysys V8.8. RESULTS AND DISCUSSION The base-case cryogenic carbon capture has been simulated by Aspen plus V8.8 and using Peng Robinson equation of state as fluid package for thermodynamics properties. The ambient conditions are assumed at 25 C ( K) and 1 bar. A. Improved process by shaft work targeting For refrigeration system of base-case LNG process, mixed refrigerant (CH , C 2 H , C 3 H , C 4 H , C 5 H ) is applied for cooling natural gas to LNG. Refrigerant properties which are type of refrigerant, temperature and pressure must be adjusted to achieve the lowest energy consumption or shaft work requirement in this system. Hot and cold stream of base case are plotted as exergy composite curves and exergy grand composite curve as shown in Figure ,000, Enthalpy(kJ/hr) (a) Figure4: (a) Exergy composite curves and (b) exergy grand composite curve of base case Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page ,000, Enthalphy (KJ/hr) level1 level2 level3 (b)

To minimize shaft work, the base-case refrigeration of tree levels are considered to adjust as shown in figure4 (b).

The lowest shaft-work case is case 3 which is approximately 9.29 % reduction in shaft work.

5 To minimize shaft work, the base-case refrigeration of tree levels are considered to adjust as shown in figure4 (b). According to the area between cold utility and EGCCs curve, the highest area and net shaft work of unit E12 must be reduced. There are 3 alternative cases for E12 modification shown in table1. The lowest shaft-work case is case 3 which is approximately 9.29 % reduction in shaft work. Level 2 of refrigeration system is an unknown cooling part which cannot be modified the refrigeration and Level 3 consumes lower shaft work than level 1 apparently so shaft work of base case can reduce by only level 1 modification. As a result, graphical method shows a potential for shaft work minimization but this method also have some error so mathematical method is applied to process as well. Table1 Modified cases B. Improved process by Mathematical modelling Mathematical programming is applied to case study to optimize refrigeration network under these assumptions: (1) Constant heat capacity flow rate; (2) HRAT=10 C (3) Refrigerant pressure inlet of evaporator = 1 bar (4) Layout and pressure drop costs are neglected; (5) Model of refrigeration depends on theoretical conditions. There are 2 model for shaft work reduction; simple refrigeration (figure 5a) and cascade refrigeration (figure 5b). Figure5: (a) Simple refrigeration model and (b) Cascade refrigeration model Table2 The opotimal solution of simple refigeration model validated by Aspen plus V8.8 Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 5

6 As per conditions of improved model by simple refrigeration, total shaft work of process is decreased to 1, kw or 65.43% reduction comparing with base case. Table3 The opotimal solution of cascade refigeration model validated by Aspen plus V8.8 For cascade refrigeration model, an optimal model reduce total shaft work to 1,596.78kW which can be reduced from base case 48.68%.Total shaft work of cascade is still higher than case of simple refrigeration model because cascade refrigeration has a specific constraint that is temperature of exchanged hot must be higher than cold stream 10 C. However, cost of condenser duty reaches the lowest cost consumption in all of cases which is 9, $/hr or 70.96% when compare with base case. Cascade refrigeration can eliminate condenser operated at very low temperature by sending heat of that condenser to a higher stage of refrigeration and so on. Therefore, hot utility for condenser at very low temperature which has high cost is not existence. CONCLUSIONS Mathematical method shows a better improvement of base case than graphical method due to its accuracy and efficiency. The best improved case for Cryogenic carbon capture and liquefied natural gas (LNG) processes is depend on requirement of process. For the lowest total shaft work consumption, case of vary temperature outlet of evaporator and compression ratio is the best which can decrease total shaft work 65.43% comparing with base case. For the lowest cost of condenser duty, cascade refrigeration case spends 9, $ per hour while total shaft work is also decreased 48.68% reduction as well. ACKNOWLEDGEMENTS Authors would like to express our gratitude to Government Budget, The Petroleum and Petrochemical College, Chulalongkorn University, and National Center of Excellence for Petroleum, Petrochemicals and Advanced Materials for funding support. Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 6

7 REFERENCES Colmenares T.R., Seider W.D., (1989). Synthesis of cascade refrigeration systems integrated with chemical processes, Computers chem. Engng, 13, Fazlollahi F., Bown A., Ebrahimzadeh E., Baxter L.L., (2015). Design and analysis of the natural gas liquefaction optimization process- CCC-ES (energy storage of cryogenic carbon capture), Energy, 90, Linhoff B., Dhole V.R., (1992). Shaftwork targets for low-temperature process design. Computers and Chemical Engineering, 47(8), Petrochemical and Materials Technology Tuesday May 23, 2017, Pathumwan Princess Hotel, Bangkok, Thailand Page 7

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