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A Software for the Calculation of the Exergetic Efficiency in Distillation Columns
10th International Symposium on Process Systems Engineering - PSE2009 Rita Maria de Brito Alves, Claudio Augusto Oller do Nascimento and Evaristo Chalbaud Biscaia Jr. (Editors) © 2009 Elsevier B.V. All rights reserved.
1005
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns Cauê T. O. G. Costa1,*, Eduardo M. Queiroz1 and Fernando L. P. Pessoa1 1
Escola de Química – Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, n. 149, Edifício Centro de Tecnologia, Bloco E, Sala 209,CEP 21941-909, Rio de Janeiro - RJ, Brazil. * E-mail address: [email protected]
Abstract Many processes in chemical industries consume a lot of energy and often operate inefficiently. This implies high operation costs, which can be reduced through improvements in the use of energy in the process. Distillation is an important unit operation that is widely used in industry and requires an excessive energy demand. The exergetic analysis, which is based on the second law of thermodynamics, is an alternative to minimize this demand. Exergy or availability is the measure of the maximum amount of stream energy that can be converted into shaft work if the stream is taken to the reference state. This property may be applied to measure the quality of energy employed in a process. Therefore, the purpose of this study is to develop a program to calculate the exergetic efficiency and suggest, if necessary, possible operational changes that lead to the reduction of energy losses by irreversibilities in distillation columns. The preliminary conclusion is that exergy analysis is vital for evaluating inefficiencies in industrial processes and thus the exergetic analysis can be used as an important tool not only for process synthesis but also for process optimization activities. Keywords: exergy, distillation column, exergetic efficiency.
1. Introduction Among the common utilized in industry processes, most attention was given to distillation, an important unit operation that is widely used and requires an excessive energy demand (Pessoa 2005). To evaluate the energy consumption, efficiencies based in the produced work-supplied energy ratio are often used. But not all energy can be turned into work, according to the second law of thermodynamics (Szargut et al 1988). Thus, it is important measure the availability in industrial plants. The exergetic or availability analysis can be used as alternative to minimize the irreversibility, resulting in a better consume of energy. Exergy is defined as the amount of work obtainable when some matter is brought to a state of thermodynamic equilibrium with the common components of the natural surroundings by means of reversible process, involving interactions only with the above-mentioned components of nature. This state property may be applied to measure the quality of energy employed in a process (Szargut et al 1988). The purpose of this work is to develop a software capable of calculate the exergetic efficiency in distillation columns, working with a simulator process, and to suggests improvements for a better exergetic utilization.
1006
C.T.O.G. Costa et al.
2. Bibliographic Review The exergetic analysis has been largely applied in processes of power generation, although not much applied in distillation processes (Maia 2001). This concept was introduced by Rant and is directly related with the second law of thermodynamic. Smith et al, presenting at chapter 5 a detailed description about the second law and entropic balance. The generated entropy is proportional to the destructed exergy in a process, as shown in the law of Gouy-Stodola:
δB = T0 S p where δB is the exergy losses, T0 is the reference state temperature and S P is the entropy produced. Szargut et al defined the concept of exergy as in the preview section and deduces the law of Gouy-Stodola abovementioned. They also show various forms of exergy calculation to different thermal, chemical and metallurgic processes; the physical, chemical and radioactive flow exergy calculation. Beyond, they show a data base for the standard exergy to dry air and sea water components, and reference reactions for calculation of the standard exergy to these reference environments. Røsjorde et al studied the entropy production in diabatic and adiabatic separations of propylene/propane, optimizing lower entropy production, and evaluating and discussing the effects of changing operational conditions and the geometry of the column. The main conclusions are that for less generation of entropy it was necessary increase the areas of heat exchange in the reboiler and condenser and the number of trays. Araujo et al studied the case of purification of EDC. In his work, showed ways of calculating the exergetic efficiency in different approaches and identified that most of the exergtic lost in the proposed separations occurs in the condenser. Koeijer et al evaluted the production of entropy and exergetic losses on the experimental column and identified that the column loses less exergy when there is heat exchange in the trays. Maia explained the concept of the reversible column and quasi-reversible column proposed by Zemp (1994). And also optimizing separations networks through the exergetic analysis for 3, 4 and 5 components systems. Rivero et al simulated and evaluated the exergy losses in Tertiary Amyl Methyl Esther production comparing the system with the adiabatic and diabatic and measuring the Exergy Improvement Potential.
3. Algorithm development Exergy is not conservative, opposed to energy (Szargut 1988). This thermodynamic property flows through the system boundaries by three different ways: mass flows, heat and shaft work (Rivero 2001). As previously described, to the system availability balance evaluation of the studied system, it is necessary computing the exergetic inputs and outputs of the system, the holdup factor and also the exergetic losses. Figure 1 shows a separation system in the process simulator UniSim® Design from Honeywell. It describes a system made by a simple distillation column operating in steady-state; the exergetic inputs are given by the feed (F), and the heat added in the reboiler (E-200). The exergetic outputs are the products (D and B), and also the heat removed in the condenser (E-100). Since the described system is in steady-state, the
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns
1007
holdup term is null. For a more rigorous approach, it is also necessary to consider the heat lost by the column for the surroundings, which can be calculated in a system energy balance.
Figure 1 – Distillation column in HYSYS To measure the exergy of stream, the procedure described by Maia, physical exergy is calculated by H – T0*S, where H is the flow enthalpy, S is the entropy and T0 is the reference temperature. The chemical exergy was neglected. The calorific contribution is given by the involved heat multiplied by the efficiency of Carnot engine for the system. It is easily justified by the fact that the efficiency of this engine is the maximum thermodynamically allowed. Thus, the exergetic balance is given by the equation:
§
δB = B feed − Bdist − Bbot + Q reb ¨¨1 − ©
where
δB
T T0 · § ¸¸ − Qcond ¨¨1 − 0 Treb ¹ © Tcond
· § T ¸¸ − Qcol ¨¨1 − 0 ¹ © Tcol
is the heat of is the lost work, B is the exergy of a stream in kJ/h, Q
col is the heat lost to environment and Tcol is the mean equipment or column, Q temperature of the column. The minimum work of separation Wmin was computed and is given for the equation:
Wmin = (Bdist + Bbot ) − (B feed ) For the calculated the exergetic efficiency, used the following equation:
η=
Wmin Wmin + δB
· ¸¸ ¹
1008
C.T.O.G. Costa et al.
The algorithm was developed in MATLAB® from The MathWorks, for use with the UniSim® Design process simulator. The flow rate, temperature, pressure, composition, enthalpy and entropy of each flow are the data input, and also the involved heat in the process heat exchangers.
4. Results and Discussion The model was tested initially with a quaternary separation proposed by Yeomans et al. The column was feed by a current saturated liquid at 12 bar discharge of 100kmol/h with 30% propane, 30% n-butane, 20% n-pentane and 20% n-hexane. The separation target was to recovery 98% of light and heavy key component of the feed in the top and bottom product, respectively. The model chosen was the thermodynamic equation of state of Peng-Robinson. Columns were tested, 25 and 13 stages, with food in the trays 11 and 6. In both simulations, the values of the exergetic balance were very close to the law of GouyStodola, resulting in an absolute difference in the order of 10-9 and relative difference of 10-14. Table 1 shows the results for these simulations:
Trays/Feed 25/11/ 13/6/
Exergy Losses 53120 KJ/h 55623 KJ/h
Minimum Work 140930 KJ/h 139800 KJ/h
Exergetic efficiency 72.63% 71.54%
Table 1: Results of first simulation of system with propane, n-butane, n-pentane and nhexane. It is important to point out that the lost exergy in both cases has a little difference when they are compared to the total exergy, but the difference is significative on the period of one year. With the validated model, focuses on another system of separation, the distillation of the isomers n-butane and i-butane. The column was fed with a flow of saturated liquid 100kmol / h. The pressure was 12bar and target was 95% purity of the products. Two columns were simulated, which varied was the number of stages, 60/30 and 50/25. The results follow below:
Trays/Feed 60/30 50/20
Exergy Losses 111500 KJ/h 147520 KJ/h
Minimum Work 123350 KJ/h 123570 KJ/h
Exergetic efficiency 52.52% 45.58%
Table 2: Results of simulation of system with n-butane and i-butane. Observe that in these simulations, the differences were significant. Due to difficulty of separation of these compounds, there is the need greater height of columns to hold it. In a difference of 10 stages of the reduction efficiency is almost 7%. As the third simulation to evaluate the software, used a system with 50% propane and 50% n-butane. The pressure and flow of the supply current was the same also with previous simulations of saturated liquid, and a target was used for purity of 98%. To evaluated, it was tested columns with 18, 16 and 10 trays, and the feed stage, 7, 6 and 4. The results follow in the table 3:
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns
Trays/Feed 18/7/ 16/6/ 10/4/
Exergy Losses 122470 KJ/h 147660 KJ/h 512320 KJ/h
Minimum Work 170710 KJ/h 170670 KJ/h 170730 KJ/h
1009
Exergetic efficiency 58.23% 53.61% 24.99%
Table 3: Results of simulation of system with propane and n-butane. Similarly to the previous example, reducing the number of stages results in higher exergy losses. The system in question has a minimum theoretical stages equal to 6.5. When approaching this value, simulating with 10 stages, occurs a high exergy destruction The results obtained using the computational program were excellent. One can seen that it is necessary more exergy for components which are more difficult to separate, which can be compensated using more trays. When the number of stages is close to the minimum number of stages there is a big reduction of efficiency.
5. Conclusions A software was developed and the results demonstrated that it can be used as a powerful tool for process engineer in the evaluation of energetic efficiency of distillation column. Neverthe less it is necessary to use a process simulator to obtain the column data. The software was capable to identify the better process operational conditions and to decrease the exergy lost and the energy consume. Using this program together an economic evaluation software it is possible to select the best operational conditions, optimizing in all aspects (efficiency and economic).
References A. B. Araujo, R. P. Brito, L. S. Vasconcelos, 2007, Exergetic analysis of distillation processes— A case study, Energy Journal, 29, 1185-1193. G. de Koeijer, R. Rivero, 2003, Entropy production and exergy loss in experimental distillation columns, Chemical Engineering Science 58,1587–1597 A. Hepbasli, 2008, A key revew on exergetic analysis and assessment of renewable energy resources for a sustainable future, Renewable and Sustainable Energy Reviews, 12, 593-661 A. P. Hinderink,F. P. J. M. Kerkhof, A. B. K. Lie, J. De Swaan Arons,H. J. Van Der Kooi, 1996, Exergy analysis with a flowsheeting simulator—I. Theory: calculating exergies of material streams. Chem Eng Sci,51,4693–700. M. L. O. Maia, 2001, Síntese e otimização de Sistemas de Destilação utilizando a Análise Exergética, UNICAMP, doctoral thesis. L. S. Moussa, 2001, Análise Termodinâmica de Colunas de Destilação Visando à Otimização Exergética, UNICAMP, masther thesis. F. L. P. Pessoa, 2005, O uso eficiente de energia em colunas de destilação, UFRJ R. Rivero, 2001, Exergy Simulations and optimization of adiabatic and diabatic binary destillation, Energy Journal, 26, 561-593. R. Rivero, M. Garcia, J. Urquiza, 2004, Simulation, exergy analysis and application of diabatic distillation to a tertiary amyl methyl ether production unit of a crude oil refinery, Energy Journal, 29, 467-489. A. Røsjorde, S. Kjelstrup, 2005, The second law optimal state of a diabatic binary tray distillation column, Chemical Engineering Science 60, 1199 – 1210 J. M. Smith,H. C. Van Ness, M. M. Abbott,2000, Introdução á Termodinâmica da Engenharia Química. Rio de Janeiro, LTV Editora. J. Szargut, D. R. Morris, F. R. Steward, 1988, Exergy analysis of Thermal, Chemical and metallurgic Process.
1010
C.T.O.G. Costa et al.
H. Yeomans, I. E. Grossmann, 1999, Nonlinear disjunctive programming models for the synthesis of heat integrated distillation sequences, Computers and Chemical Engineering 23, 1135–1151 R. J. Zemp, 1994, Thermodynamic Analysis of Separation Systems. Inglaterra, UMIST, doctoral thesis
1005
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns Cauê T. O. G. Costa1,*, Eduardo M. Queiroz1 and Fernando L. P. Pessoa1 1
Escola de Química – Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, n. 149, Edifício Centro de Tecnologia, Bloco E, Sala 209,CEP 21941-909, Rio de Janeiro - RJ, Brazil. * E-mail address: [email protected]
Abstract Many processes in chemical industries consume a lot of energy and often operate inefficiently. This implies high operation costs, which can be reduced through improvements in the use of energy in the process. Distillation is an important unit operation that is widely used in industry and requires an excessive energy demand. The exergetic analysis, which is based on the second law of thermodynamics, is an alternative to minimize this demand. Exergy or availability is the measure of the maximum amount of stream energy that can be converted into shaft work if the stream is taken to the reference state. This property may be applied to measure the quality of energy employed in a process. Therefore, the purpose of this study is to develop a program to calculate the exergetic efficiency and suggest, if necessary, possible operational changes that lead to the reduction of energy losses by irreversibilities in distillation columns. The preliminary conclusion is that exergy analysis is vital for evaluating inefficiencies in industrial processes and thus the exergetic analysis can be used as an important tool not only for process synthesis but also for process optimization activities. Keywords: exergy, distillation column, exergetic efficiency.
1. Introduction Among the common utilized in industry processes, most attention was given to distillation, an important unit operation that is widely used and requires an excessive energy demand (Pessoa 2005). To evaluate the energy consumption, efficiencies based in the produced work-supplied energy ratio are often used. But not all energy can be turned into work, according to the second law of thermodynamics (Szargut et al 1988). Thus, it is important measure the availability in industrial plants. The exergetic or availability analysis can be used as alternative to minimize the irreversibility, resulting in a better consume of energy. Exergy is defined as the amount of work obtainable when some matter is brought to a state of thermodynamic equilibrium with the common components of the natural surroundings by means of reversible process, involving interactions only with the above-mentioned components of nature. This state property may be applied to measure the quality of energy employed in a process (Szargut et al 1988). The purpose of this work is to develop a software capable of calculate the exergetic efficiency in distillation columns, working with a simulator process, and to suggests improvements for a better exergetic utilization.
1006
C.T.O.G. Costa et al.
2. Bibliographic Review The exergetic analysis has been largely applied in processes of power generation, although not much applied in distillation processes (Maia 2001). This concept was introduced by Rant and is directly related with the second law of thermodynamic. Smith et al, presenting at chapter 5 a detailed description about the second law and entropic balance. The generated entropy is proportional to the destructed exergy in a process, as shown in the law of Gouy-Stodola:
δB = T0 S p where δB is the exergy losses, T0 is the reference state temperature and S P is the entropy produced. Szargut et al defined the concept of exergy as in the preview section and deduces the law of Gouy-Stodola abovementioned. They also show various forms of exergy calculation to different thermal, chemical and metallurgic processes; the physical, chemical and radioactive flow exergy calculation. Beyond, they show a data base for the standard exergy to dry air and sea water components, and reference reactions for calculation of the standard exergy to these reference environments. Røsjorde et al studied the entropy production in diabatic and adiabatic separations of propylene/propane, optimizing lower entropy production, and evaluating and discussing the effects of changing operational conditions and the geometry of the column. The main conclusions are that for less generation of entropy it was necessary increase the areas of heat exchange in the reboiler and condenser and the number of trays. Araujo et al studied the case of purification of EDC. In his work, showed ways of calculating the exergetic efficiency in different approaches and identified that most of the exergtic lost in the proposed separations occurs in the condenser. Koeijer et al evaluted the production of entropy and exergetic losses on the experimental column and identified that the column loses less exergy when there is heat exchange in the trays. Maia explained the concept of the reversible column and quasi-reversible column proposed by Zemp (1994). And also optimizing separations networks through the exergetic analysis for 3, 4 and 5 components systems. Rivero et al simulated and evaluated the exergy losses in Tertiary Amyl Methyl Esther production comparing the system with the adiabatic and diabatic and measuring the Exergy Improvement Potential.
3. Algorithm development Exergy is not conservative, opposed to energy (Szargut 1988). This thermodynamic property flows through the system boundaries by three different ways: mass flows, heat and shaft work (Rivero 2001). As previously described, to the system availability balance evaluation of the studied system, it is necessary computing the exergetic inputs and outputs of the system, the holdup factor and also the exergetic losses. Figure 1 shows a separation system in the process simulator UniSim® Design from Honeywell. It describes a system made by a simple distillation column operating in steady-state; the exergetic inputs are given by the feed (F), and the heat added in the reboiler (E-200). The exergetic outputs are the products (D and B), and also the heat removed in the condenser (E-100). Since the described system is in steady-state, the
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns
1007
holdup term is null. For a more rigorous approach, it is also necessary to consider the heat lost by the column for the surroundings, which can be calculated in a system energy balance.
Figure 1 – Distillation column in HYSYS To measure the exergy of stream, the procedure described by Maia, physical exergy is calculated by H – T0*S, where H is the flow enthalpy, S is the entropy and T0 is the reference temperature. The chemical exergy was neglected. The calorific contribution is given by the involved heat multiplied by the efficiency of Carnot engine for the system. It is easily justified by the fact that the efficiency of this engine is the maximum thermodynamically allowed. Thus, the exergetic balance is given by the equation:
§
δB = B feed − Bdist − Bbot + Q reb ¨¨1 − ©
where
δB
T T0 · § ¸¸ − Qcond ¨¨1 − 0 Treb ¹ © Tcond
· § T ¸¸ − Qcol ¨¨1 − 0 ¹ © Tcol
is the heat of is the lost work, B is the exergy of a stream in kJ/h, Q
col is the heat lost to environment and Tcol is the mean equipment or column, Q temperature of the column. The minimum work of separation Wmin was computed and is given for the equation:
Wmin = (Bdist + Bbot ) − (B feed ) For the calculated the exergetic efficiency, used the following equation:
η=
Wmin Wmin + δB
· ¸¸ ¹
1008
C.T.O.G. Costa et al.
The algorithm was developed in MATLAB® from The MathWorks, for use with the UniSim® Design process simulator. The flow rate, temperature, pressure, composition, enthalpy and entropy of each flow are the data input, and also the involved heat in the process heat exchangers.
4. Results and Discussion The model was tested initially with a quaternary separation proposed by Yeomans et al. The column was feed by a current saturated liquid at 12 bar discharge of 100kmol/h with 30% propane, 30% n-butane, 20% n-pentane and 20% n-hexane. The separation target was to recovery 98% of light and heavy key component of the feed in the top and bottom product, respectively. The model chosen was the thermodynamic equation of state of Peng-Robinson. Columns were tested, 25 and 13 stages, with food in the trays 11 and 6. In both simulations, the values of the exergetic balance were very close to the law of GouyStodola, resulting in an absolute difference in the order of 10-9 and relative difference of 10-14. Table 1 shows the results for these simulations:
Trays/Feed 25/11/ 13/6/
Exergy Losses 53120 KJ/h 55623 KJ/h
Minimum Work 140930 KJ/h 139800 KJ/h
Exergetic efficiency 72.63% 71.54%
Table 1: Results of first simulation of system with propane, n-butane, n-pentane and nhexane. It is important to point out that the lost exergy in both cases has a little difference when they are compared to the total exergy, but the difference is significative on the period of one year. With the validated model, focuses on another system of separation, the distillation of the isomers n-butane and i-butane. The column was fed with a flow of saturated liquid 100kmol / h. The pressure was 12bar and target was 95% purity of the products. Two columns were simulated, which varied was the number of stages, 60/30 and 50/25. The results follow below:
Trays/Feed 60/30 50/20
Exergy Losses 111500 KJ/h 147520 KJ/h
Minimum Work 123350 KJ/h 123570 KJ/h
Exergetic efficiency 52.52% 45.58%
Table 2: Results of simulation of system with n-butane and i-butane. Observe that in these simulations, the differences were significant. Due to difficulty of separation of these compounds, there is the need greater height of columns to hold it. In a difference of 10 stages of the reduction efficiency is almost 7%. As the third simulation to evaluate the software, used a system with 50% propane and 50% n-butane. The pressure and flow of the supply current was the same also with previous simulations of saturated liquid, and a target was used for purity of 98%. To evaluated, it was tested columns with 18, 16 and 10 trays, and the feed stage, 7, 6 and 4. The results follow in the table 3:
A Software for the Calculation of the Exergetic Efficiency in Distillation Columns
Trays/Feed 18/7/ 16/6/ 10/4/
Exergy Losses 122470 KJ/h 147660 KJ/h 512320 KJ/h
Minimum Work 170710 KJ/h 170670 KJ/h 170730 KJ/h
1009
Exergetic efficiency 58.23% 53.61% 24.99%
Table 3: Results of simulation of system with propane and n-butane. Similarly to the previous example, reducing the number of stages results in higher exergy losses. The system in question has a minimum theoretical stages equal to 6.5. When approaching this value, simulating with 10 stages, occurs a high exergy destruction The results obtained using the computational program were excellent. One can seen that it is necessary more exergy for components which are more difficult to separate, which can be compensated using more trays. When the number of stages is close to the minimum number of stages there is a big reduction of efficiency.
5. Conclusions A software was developed and the results demonstrated that it can be used as a powerful tool for process engineer in the evaluation of energetic efficiency of distillation column. Neverthe less it is necessary to use a process simulator to obtain the column data. The software was capable to identify the better process operational conditions and to decrease the exergy lost and the energy consume. Using this program together an economic evaluation software it is possible to select the best operational conditions, optimizing in all aspects (efficiency and economic).
References A. B. Araujo, R. P. Brito, L. S. Vasconcelos, 2007, Exergetic analysis of distillation processes— A case study, Energy Journal, 29, 1185-1193. G. de Koeijer, R. Rivero, 2003, Entropy production and exergy loss in experimental distillation columns, Chemical Engineering Science 58,1587–1597 A. Hepbasli, 2008, A key revew on exergetic analysis and assessment of renewable energy resources for a sustainable future, Renewable and Sustainable Energy Reviews, 12, 593-661 A. P. Hinderink,F. P. J. M. Kerkhof, A. B. K. Lie, J. De Swaan Arons,H. J. Van Der Kooi, 1996, Exergy analysis with a flowsheeting simulator—I. Theory: calculating exergies of material streams. Chem Eng Sci,51,4693–700. M. L. O. Maia, 2001, Síntese e otimização de Sistemas de Destilação utilizando a Análise Exergética, UNICAMP, doctoral thesis. L. S. Moussa, 2001, Análise Termodinâmica de Colunas de Destilação Visando à Otimização Exergética, UNICAMP, masther thesis. F. L. P. Pessoa, 2005, O uso eficiente de energia em colunas de destilação, UFRJ R. Rivero, 2001, Exergy Simulations and optimization of adiabatic and diabatic binary destillation, Energy Journal, 26, 561-593. R. Rivero, M. Garcia, J. Urquiza, 2004, Simulation, exergy analysis and application of diabatic distillation to a tertiary amyl methyl ether production unit of a crude oil refinery, Energy Journal, 29, 467-489. A. Røsjorde, S. Kjelstrup, 2005, The second law optimal state of a diabatic binary tray distillation column, Chemical Engineering Science 60, 1199 – 1210 J. M. Smith,H. C. Van Ness, M. M. Abbott,2000, Introdução á Termodinâmica da Engenharia Química. Rio de Janeiro, LTV Editora. J. Szargut, D. R. Morris, F. R. Steward, 1988, Exergy analysis of Thermal, Chemical and metallurgic Process.
1010
C.T.O.G. Costa et al.
H. Yeomans, I. E. Grossmann, 1999, Nonlinear disjunctive programming models for the synthesis of heat integrated distillation sequences, Computers and Chemical Engineering 23, 1135–1151 R. J. Zemp, 1994, Thermodynamic Analysis of Separation Systems. Inglaterra, UMIST, doctoral thesis