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Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil
Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24 June 15-18, 2014, Budapest, Hungary. Copyright © 2014 Elsevier B.V. All rights reserved.
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil Bruno S. Custódioa,c, Henrique A. Matosa*, Fernando G. Martinsb, António L. Oliveirac a
CPQ/CERENA, DEQ, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal; b LEPABE, Departamento de Engenharia Química, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal; c FIMA Produtos Alimentares, Sociedade Anónima, Marinhas de D. Pedro, 2690-361 Santa Iria de Azóia, Portugal. [email protected]
Abstract This work addresses the application of a detailed Pinch Analysis modelling technique, developed in Excel/VBA, for a multipurpose refinery batch plant. This application is focused on developing a tool that enables a quick analysis of Heat Integration to improve the energy-efficiency by rescheduling the operations. The developed tool was used with a real case study process data of a vegetable oil’s refining plant. Several scenarios of re-scheduling were used to still accomplish the demand from the downstream plant production. This study show that a reduction of about 15 % in both utilities consumption can be achieved by some scenarios compared to the current vegetable refining scheduling. Also the results show that the integrated approach leads to better synchronization between production plant and the utility system. Thereby, the integrated approach leads to significant reduction in energy costs and gas emissions, showing advantages for future improvements based on rescheduling and indirect/direct heat exchange opportunities. Also the results of this work indicate a great potential of the use of HENs in real Batch Process systems for refining vegetable oils and present an important enhancement on the industrial plant thermal energy efficiency. Keywords: Pinch Analysis; Batch processing; Time Slice Model (TSM); Rescheduling; Refining Vegetable Oil.
1. Introduction For batch systems, Pinch Analysis and the development of direct heat recovery projects are much more difficult to perform than for continuous processes. For example, in these systems, many streams are present for only certain time periods, which restrict the possibilities for heat exchange. In addition they usually do not evolve at constant temperatures with constant heat capacity flow rates. In many situations, much heating and/or cooling are done in situ in vessels were the contents gradually change the temperature. Nonetheless, Pinch Analysis can be applied to batch processes, with suitable modifications. Such Heat Integration approach and Pinch Analysis techniques have been initially establish by Kemp and Deakin in 1989 to obtain the energy targets for the batch
1610
B. Custódio et al.
operation, were they expanded the concept of the Time Slice Model (TSM) of Kemp and MacDonald (1987, 1988). The TSM takes the schedule of streams into account and split into several time intervals, where each sub-process is associated to each time slice. Ian Kemp in 2007 described the basic procedures of using TSM for Heat Integration of Batch Processes. Some recent works have been developed applying several programming techniques to improve the integration of Batch Processes (Friedler, 2010). Mixed Integer Linear Programming (MILP) has also been considered to improve Batch Processes by attempting Rescheduling (Jia, 2013). In this work an Excel/VBA application is presented based on Pinch Analysis procedures for batch processes. The main goal of this application is to create an advanced software tool of data manipulation In\Out, analysis, and displaying of the energy saving potentials in a Batch Process system and also to give the incentive to improve the direct Heat Integration through quick rescheduling. The energy targets calculated by this tool are based on the time – temperature cascade analysis methodology (Kemp, 2007). In general this methodology gives targets for maximum heat recovery within a batch system and for a TSM, from which rescheduling opportunities can be obtained. Moreover, the created application takes the schedule of streams into account for Batch Process systems and split into several time intervals, where each sub-process is associated to each time slice. The Pinch Analysis method was implemented in FIMA refinery plant in St. Iria, Portugal, a multipurpose refinery batch plant. The plant produces in batch mode about 36,000 t/y of vegetable oils, which creates a real industrial case study for the implementation of this kind of analysis. In this way, opportunities for Heat Integration were explored.
2. The Pinch Analysis and the Excel/VBA tool The evaluation of the optimal energy saving potential by rescheduling in a Batch Process system is a difficult task because the existence of a large number of possibilities. The Excel/VBA tool proposed in this work was developed for helping to define the rescheduling opportunities of the operating process with savings in energy consumption. The main features of this tool are presented in Figure 1. The algorithm is described as follows: Step 1: Define the number of stream j max in the case study process. Step 2: Insert the steams data from the case study process (j=1; j=2; j=3;...; j max) and choose the specific minimum temperature difference ΔTmin. Step 3: If the time event of each stream are independent from each other insert the desired time deviation td and the corresponding number of feasible iteration i max otherwise select first the stream that are dependent on each other. Step 4: Start the Pinch Analysis modelling simulation considering the methodology of Kemp (2007). Step 5: Creation of the table of results of the required hot utility and cold utility in the process for each iteration and the corresponding graphs.
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil 1611 Start
Define the number of stream j max in the the case study process Insert the steams data from the case study process (j=1; j=2; j=3;...; j max) and choose ΔTmin
is the time event of each stream independent from each other?
No
Select the streams that are dependent on each other
Yes Insert the desired time deviation td and the corresponding number of feasible iteration i max. i=0; tdi=0 and j=1 Start the pinch analysis modelling simulation considering the methodology of Kemp (1990)
No i=i+1 and tdi=td*i
Calculate the required hot utility and cold utility in the process
Is i >i max?
No
Yes j=j+1; i=1 and tdi=td Is j >j max?
Yes
Creation of the table of results for each iteration and the corresponding graph.
Figure 1. Flowchart for the Pinch Analysis modelling with Excel/VBA programming
The user has to provide the data time intervals of all operations and the streams source data (until a maximum of 10 streams). The target values calculated by the Excel/VBA tool indicate automatically the best opportunities of rescheduling to minimize the energy consumption.
3. Case study The methodologies described above are applied to a real industrial case of a refinery of vegetable oil. 3.1. Process description. The first step of the production process in the refinery is the preparation of the vegetable oil. The oil arrive in raw or semi-refined state to the plant from tanks or vessels, being subjected to prior treatment at the refinery. The raw materials are: Sunflower, Corn, Soybeans (non-genetically modified) Palm oil and its derivatives such palm stearin or palm olein and coconut oil. These raw materials are firstly subject to a control quality and after they proceed to three different processing operations in the refinery: • Neutralization to remove the impurities and the acidity of the oil, with a solution of caustic soda; • Bleaching to remove all natural colours of the oil by taking out all pigments, such as chlorophyll and carotenoids; • Deodorization to eliminate the taste and odour of the natural oil by heating the oil up to a temperature in the range (230-260 °C) under a vacuum pressure of 2 to 10 mm Hg absolute.
1612
B. Custódio et al.
70 º C V acuo Vacuo
Hydrogenation
Parque de tanques de óleos Brutos
Desarej e ador Desarejador
Balanças 25 t X 2
85ºC
Buff f er 6 t Buffer
ATM
SCD 170 ºC
Balança óleos brutos
1
10 00 ºc 100 245 ºC H2
H1
H3
Caldeira Geka
65 Bar Max. 360 ºC
Neutralization 60ºC
690 L
Deodorization Gás Natural
Unidade de vacuo
ATM
ATM
ATM
Torre de Marley
ATM
ATM
24º c
Vap A.180 ºC, 14 bar
N1
80ºC ~ 90ºC
N3
N2
CONDENSADOS DA MARGARINARIA
TANQUE 40m3
N4
N5
98 ºC
¾Lavagem do chão ¾Lavagem Neutralizadores
100- 90 ºC
90ºC
95 ºC
80ºC
Filtro Gaf
60ºC PC
Parque de tanques de óleos Neutros e Branqueados Filtro Gaf
60 ºC
Sala Oleos
Parque de tanques de óleos Hidrogenados
Figure 2. Process flowsheet of the vegetable oil’s refinery.
Finally, the pre-treated oil are sent to margarine plant, more properly to the storage room for the finalizing preparation of the oil (the fat phase). Figure 2 presents the process flowsheet for the treatment of the oil at the refinery. 3.2. Analysis of the neutralization process. The data of the case study are represented in the Table 1, this represents a part of the refining process. The plant production scheduling was used for the products (A1) and (A2) in the neutralization process. Each product occupies, respectively, the reactors N5 and N4. The products hold also distinct process operations. For example the product A1 is heated first from 50 ºC to 110 ºC, then the product is cooled to 95 ºC, and then heated to 105 ºC. Finally the product is cooled to 50 ºC (Stream 1, 2, 3 and 4 of Table 1). For the product A2 the process is more simplified. The product is heated first from 50 ºC to 85 ºC and finally cooled to 60 ºC. The neutralization reactors operate under reduced pressure. They are cylindrical vessels and their height is approximately 1.5 times the diameter. The two reactors contain Heat Transfer Systems. Steam or cold water can be passed through that coils system to obtain the target values of the temperatures. The cycle time of the process is 1.5 h and the streams exist during the following time periods: Cold stream 1: 0–0.2 h; Hot stream 2: 0.4–0.6 h; Cold stream 3: 0.7–1 h; Hot stream 4: 1.1–1.3 h; Cold stream 5: 0.5–0.9 h and Hot stream 6: 1.2–1.5 h Through the heat cascades it was possible to obtain for each time interval placed side by side the visualization of the heat load and the wanted targets. The targets obtained are the Maximum Energy Recovery (MER) within that time interval by direct heat exchange. The TSM targets are 1087 kWh hot utility and 1125 kWh cold utility. Table 1. Data for the existing case in the refinery
N5 A1 N4 A2
Stream
Type
1 2 3 4 5 6
cold hot cold hot cold hot
Ti
Tf 50 110 94 105 50 100
110 95 105 50 85 60
Ti´ 55 105 99 100 55 95
Tf´ 115 90 110 45 90 55
Cp (kW/K) -58.3 58.3 -38.9 58.3 -24.6 32.8
Q (kW) -3500 875 -428 3208 -862 1314
Operational times Start (h) End (h) 0 0.4 0.7 1.1 0.5 1.2
0.2 0.6 1 1.3 0.9 1.5
Q (kWh) -700 175 -128 642 -345 394
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil 1613 1250 1211 1200
1150
1100 1087
1087
1087
1087
1050
Utility Consumption kWh
1173
1173
1173
1000 1001
1001
950 0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Iteration
Figure 3. Graphical representation of the consumption of the process utilities obtained by the Excel/VBA tool for 15 scheduling scenarios/iterations. (---- Cold Utility; ____ Hot Utility)
3.3. Results of Excel/VBA software tool. The results are given automatically in a graphical representation, allowing for an easy assessment of rescheduling opportunities (Figure 3 and 4). It can be seen that the opportunities for rescheduling exist. From the several TSM iterations, we obtain five opportunities (Iteration 3; 4; 5; 10 and 11), which implements time deviation for the streams 5 and 6 (-0.3 h; -0.2 h; -0.1 h; 0.4 h and 0.5 h), respectively. The iteration twelve was not considered due to violation of the specific minimum temperature difference ΔTmin. The best result introduces requirements of 1,001 kWh of hot utility and 1,038 kWh of cold utility. These streams (5 and 6) are mutually dependent of the time scheduling of the reactor N4 and the remaining streams to the reactor N5. The corresponding heat recovery is a potential value of 172.4 kWh. This saving of about 15 % is obtained for each utility compared with the former requirements without heat integration (1,173 kWh and 1,211 kWh).
Figure 4. New time event diagram from the iteration 3 with saving of 15 % in each utility.
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B. Custódio et al.
4. Conclusions Heat recovery in batch processes is possible, but generally gives lower absolute savings than for continuous processes, because energy use is generally lower and there are major constraints on whether hot and cold streams coexist at the same time. The case study shows that Pinch Analysis can identify substantial benefits on batch processes, and also on other time-dependent situations. The two most commonly useful techniques for batch and time-dependent processes are the TSM and the time event Gantt chart. These are the key points in evaluating heat exchange and for rescheduling possibilities. This work was able to find that these techniques by applying a framework developed with Excel/VBA programming. It was possible to indicate a direct target saving near 15 %, and also demonstrate that was possible through an easy assessment of rescheduling opportunities. Further work will be focused on the operational issues for applying this results and new studies about the opportunities created by including the indirect heat storage strategy.
References F. Friedler, 2010, Process integration, modelling and optimisation for energy saving and pollution reduction, Applied Thermal Engineering, 30, 16, 2270-2280. I.C. Kemp, 2007, Pinch Analysis and Process Integration: A User Guide on Process Integration for the Efficient Use of Energy, Second Edition, Elsevier, UK I.C. Kemp, 1990, Application of the time-dependent cascade analysis in process integration, Journal of Heat Recovery System and CHP, 10, 4, 423-425. I.C. Kemp, A.W. Deakin, 1989, The cascade analysis for energy and process integration of batch processes, Part 1: Calculation of energy targets, Chemical Engineering Research and Design 67, 495-509. I.C. Kemp, E.K. Macdonald, 1987, Energy and process integration in continuous and batch processes, IChemE Symposium Series, 105, 185-200, Institution of Chemical Engineers, Rugby, UK. I.C. Kemp, E.K. Macdonald, 1988. Application of pinch technology to separation, reaction and batch processes. IChemE Symposium Series, 109, 239-257, Institution of Chemical Engineers, Rugby, UK. Y. Jia, W. Xiao, G.H. He, 2013, Petri Net Methodology for Optimization of Heat Integration and Batch Process Scheduling, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA), Kuala Lumpur, Malaysia.
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil Bruno S. Custódioa,c, Henrique A. Matosa*, Fernando G. Martinsb, António L. Oliveirac a
CPQ/CERENA, DEQ, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal; b LEPABE, Departamento de Engenharia Química, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal; c FIMA Produtos Alimentares, Sociedade Anónima, Marinhas de D. Pedro, 2690-361 Santa Iria de Azóia, Portugal. [email protected]
Abstract This work addresses the application of a detailed Pinch Analysis modelling technique, developed in Excel/VBA, for a multipurpose refinery batch plant. This application is focused on developing a tool that enables a quick analysis of Heat Integration to improve the energy-efficiency by rescheduling the operations. The developed tool was used with a real case study process data of a vegetable oil’s refining plant. Several scenarios of re-scheduling were used to still accomplish the demand from the downstream plant production. This study show that a reduction of about 15 % in both utilities consumption can be achieved by some scenarios compared to the current vegetable refining scheduling. Also the results show that the integrated approach leads to better synchronization between production plant and the utility system. Thereby, the integrated approach leads to significant reduction in energy costs and gas emissions, showing advantages for future improvements based on rescheduling and indirect/direct heat exchange opportunities. Also the results of this work indicate a great potential of the use of HENs in real Batch Process systems for refining vegetable oils and present an important enhancement on the industrial plant thermal energy efficiency. Keywords: Pinch Analysis; Batch processing; Time Slice Model (TSM); Rescheduling; Refining Vegetable Oil.
1. Introduction For batch systems, Pinch Analysis and the development of direct heat recovery projects are much more difficult to perform than for continuous processes. For example, in these systems, many streams are present for only certain time periods, which restrict the possibilities for heat exchange. In addition they usually do not evolve at constant temperatures with constant heat capacity flow rates. In many situations, much heating and/or cooling are done in situ in vessels were the contents gradually change the temperature. Nonetheless, Pinch Analysis can be applied to batch processes, with suitable modifications. Such Heat Integration approach and Pinch Analysis techniques have been initially establish by Kemp and Deakin in 1989 to obtain the energy targets for the batch
1610
B. Custódio et al.
operation, were they expanded the concept of the Time Slice Model (TSM) of Kemp and MacDonald (1987, 1988). The TSM takes the schedule of streams into account and split into several time intervals, where each sub-process is associated to each time slice. Ian Kemp in 2007 described the basic procedures of using TSM for Heat Integration of Batch Processes. Some recent works have been developed applying several programming techniques to improve the integration of Batch Processes (Friedler, 2010). Mixed Integer Linear Programming (MILP) has also been considered to improve Batch Processes by attempting Rescheduling (Jia, 2013). In this work an Excel/VBA application is presented based on Pinch Analysis procedures for batch processes. The main goal of this application is to create an advanced software tool of data manipulation In\Out, analysis, and displaying of the energy saving potentials in a Batch Process system and also to give the incentive to improve the direct Heat Integration through quick rescheduling. The energy targets calculated by this tool are based on the time – temperature cascade analysis methodology (Kemp, 2007). In general this methodology gives targets for maximum heat recovery within a batch system and for a TSM, from which rescheduling opportunities can be obtained. Moreover, the created application takes the schedule of streams into account for Batch Process systems and split into several time intervals, where each sub-process is associated to each time slice. The Pinch Analysis method was implemented in FIMA refinery plant in St. Iria, Portugal, a multipurpose refinery batch plant. The plant produces in batch mode about 36,000 t/y of vegetable oils, which creates a real industrial case study for the implementation of this kind of analysis. In this way, opportunities for Heat Integration were explored.
2. The Pinch Analysis and the Excel/VBA tool The evaluation of the optimal energy saving potential by rescheduling in a Batch Process system is a difficult task because the existence of a large number of possibilities. The Excel/VBA tool proposed in this work was developed for helping to define the rescheduling opportunities of the operating process with savings in energy consumption. The main features of this tool are presented in Figure 1. The algorithm is described as follows: Step 1: Define the number of stream j max in the case study process. Step 2: Insert the steams data from the case study process (j=1; j=2; j=3;...; j max) and choose the specific minimum temperature difference ΔTmin. Step 3: If the time event of each stream are independent from each other insert the desired time deviation td and the corresponding number of feasible iteration i max otherwise select first the stream that are dependent on each other. Step 4: Start the Pinch Analysis modelling simulation considering the methodology of Kemp (2007). Step 5: Creation of the table of results of the required hot utility and cold utility in the process for each iteration and the corresponding graphs.
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil 1611 Start
Define the number of stream j max in the the case study process Insert the steams data from the case study process (j=1; j=2; j=3;...; j max) and choose ΔTmin
is the time event of each stream independent from each other?
No
Select the streams that are dependent on each other
Yes Insert the desired time deviation td and the corresponding number of feasible iteration i max. i=0; tdi=0 and j=1 Start the pinch analysis modelling simulation considering the methodology of Kemp (1990)
No i=i+1 and tdi=td*i
Calculate the required hot utility and cold utility in the process
Is i >i max?
No
Yes j=j+1; i=1 and tdi=td Is j >j max?
Yes
Creation of the table of results for each iteration and the corresponding graph.
Figure 1. Flowchart for the Pinch Analysis modelling with Excel/VBA programming
The user has to provide the data time intervals of all operations and the streams source data (until a maximum of 10 streams). The target values calculated by the Excel/VBA tool indicate automatically the best opportunities of rescheduling to minimize the energy consumption.
3. Case study The methodologies described above are applied to a real industrial case of a refinery of vegetable oil. 3.1. Process description. The first step of the production process in the refinery is the preparation of the vegetable oil. The oil arrive in raw or semi-refined state to the plant from tanks or vessels, being subjected to prior treatment at the refinery. The raw materials are: Sunflower, Corn, Soybeans (non-genetically modified) Palm oil and its derivatives such palm stearin or palm olein and coconut oil. These raw materials are firstly subject to a control quality and after they proceed to three different processing operations in the refinery: • Neutralization to remove the impurities and the acidity of the oil, with a solution of caustic soda; • Bleaching to remove all natural colours of the oil by taking out all pigments, such as chlorophyll and carotenoids; • Deodorization to eliminate the taste and odour of the natural oil by heating the oil up to a temperature in the range (230-260 °C) under a vacuum pressure of 2 to 10 mm Hg absolute.
1612
B. Custódio et al.
70 º C V acuo Vacuo
Hydrogenation
Parque de tanques de óleos Brutos
Desarej e ador Desarejador
Balanças 25 t X 2
85ºC
Buff f er 6 t Buffer
ATM
SCD 170 ºC
Balança óleos brutos
1
10 00 ºc 100 245 ºC H2
H1
H3
Caldeira Geka
65 Bar Max. 360 ºC
Neutralization 60ºC
690 L
Deodorization Gás Natural
Unidade de vacuo
ATM
ATM
ATM
Torre de Marley
ATM
ATM
24º c
Vap A.180 ºC, 14 bar
N1
80ºC ~ 90ºC
N3
N2
CONDENSADOS DA MARGARINARIA
TANQUE 40m3
N4
N5
98 ºC
¾Lavagem do chão ¾Lavagem Neutralizadores
100- 90 ºC
90ºC
95 ºC
80ºC
Filtro Gaf
60ºC PC
Parque de tanques de óleos Neutros e Branqueados Filtro Gaf
60 ºC
Sala Oleos
Parque de tanques de óleos Hidrogenados
Figure 2. Process flowsheet of the vegetable oil’s refinery.
Finally, the pre-treated oil are sent to margarine plant, more properly to the storage room for the finalizing preparation of the oil (the fat phase). Figure 2 presents the process flowsheet for the treatment of the oil at the refinery. 3.2. Analysis of the neutralization process. The data of the case study are represented in the Table 1, this represents a part of the refining process. The plant production scheduling was used for the products (A1) and (A2) in the neutralization process. Each product occupies, respectively, the reactors N5 and N4. The products hold also distinct process operations. For example the product A1 is heated first from 50 ºC to 110 ºC, then the product is cooled to 95 ºC, and then heated to 105 ºC. Finally the product is cooled to 50 ºC (Stream 1, 2, 3 and 4 of Table 1). For the product A2 the process is more simplified. The product is heated first from 50 ºC to 85 ºC and finally cooled to 60 ºC. The neutralization reactors operate under reduced pressure. They are cylindrical vessels and their height is approximately 1.5 times the diameter. The two reactors contain Heat Transfer Systems. Steam or cold water can be passed through that coils system to obtain the target values of the temperatures. The cycle time of the process is 1.5 h and the streams exist during the following time periods: Cold stream 1: 0–0.2 h; Hot stream 2: 0.4–0.6 h; Cold stream 3: 0.7–1 h; Hot stream 4: 1.1–1.3 h; Cold stream 5: 0.5–0.9 h and Hot stream 6: 1.2–1.5 h Through the heat cascades it was possible to obtain for each time interval placed side by side the visualization of the heat load and the wanted targets. The targets obtained are the Maximum Energy Recovery (MER) within that time interval by direct heat exchange. The TSM targets are 1087 kWh hot utility and 1125 kWh cold utility. Table 1. Data for the existing case in the refinery
N5 A1 N4 A2
Stream
Type
1 2 3 4 5 6
cold hot cold hot cold hot
Ti
Tf 50 110 94 105 50 100
110 95 105 50 85 60
Ti´ 55 105 99 100 55 95
Tf´ 115 90 110 45 90 55
Cp (kW/K) -58.3 58.3 -38.9 58.3 -24.6 32.8
Q (kW) -3500 875 -428 3208 -862 1314
Operational times Start (h) End (h) 0 0.4 0.7 1.1 0.5 1.2
0.2 0.6 1 1.3 0.9 1.5
Q (kWh) -700 175 -128 642 -345 394
Pinch Analysis of an Industrial Batch Process for the Refining of Vegetable Oil 1613 1250 1211 1200
1150
1100 1087
1087
1087
1087
1050
Utility Consumption kWh
1173
1173
1173
1000 1001
1001
950 0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Iteration
Figure 3. Graphical representation of the consumption of the process utilities obtained by the Excel/VBA tool for 15 scheduling scenarios/iterations. (---- Cold Utility; ____ Hot Utility)
3.3. Results of Excel/VBA software tool. The results are given automatically in a graphical representation, allowing for an easy assessment of rescheduling opportunities (Figure 3 and 4). It can be seen that the opportunities for rescheduling exist. From the several TSM iterations, we obtain five opportunities (Iteration 3; 4; 5; 10 and 11), which implements time deviation for the streams 5 and 6 (-0.3 h; -0.2 h; -0.1 h; 0.4 h and 0.5 h), respectively. The iteration twelve was not considered due to violation of the specific minimum temperature difference ΔTmin. The best result introduces requirements of 1,001 kWh of hot utility and 1,038 kWh of cold utility. These streams (5 and 6) are mutually dependent of the time scheduling of the reactor N4 and the remaining streams to the reactor N5. The corresponding heat recovery is a potential value of 172.4 kWh. This saving of about 15 % is obtained for each utility compared with the former requirements without heat integration (1,173 kWh and 1,211 kWh).
Figure 4. New time event diagram from the iteration 3 with saving of 15 % in each utility.
1614
B. Custódio et al.
4. Conclusions Heat recovery in batch processes is possible, but generally gives lower absolute savings than for continuous processes, because energy use is generally lower and there are major constraints on whether hot and cold streams coexist at the same time. The case study shows that Pinch Analysis can identify substantial benefits on batch processes, and also on other time-dependent situations. The two most commonly useful techniques for batch and time-dependent processes are the TSM and the time event Gantt chart. These are the key points in evaluating heat exchange and for rescheduling possibilities. This work was able to find that these techniques by applying a framework developed with Excel/VBA programming. It was possible to indicate a direct target saving near 15 %, and also demonstrate that was possible through an easy assessment of rescheduling opportunities. Further work will be focused on the operational issues for applying this results and new studies about the opportunities created by including the indirect heat storage strategy.
References F. Friedler, 2010, Process integration, modelling and optimisation for energy saving and pollution reduction, Applied Thermal Engineering, 30, 16, 2270-2280. I.C. Kemp, 2007, Pinch Analysis and Process Integration: A User Guide on Process Integration for the Efficient Use of Energy, Second Edition, Elsevier, UK I.C. Kemp, 1990, Application of the time-dependent cascade analysis in process integration, Journal of Heat Recovery System and CHP, 10, 4, 423-425. I.C. Kemp, A.W. Deakin, 1989, The cascade analysis for energy and process integration of batch processes, Part 1: Calculation of energy targets, Chemical Engineering Research and Design 67, 495-509. I.C. Kemp, E.K. Macdonald, 1987, Energy and process integration in continuous and batch processes, IChemE Symposium Series, 105, 185-200, Institution of Chemical Engineers, Rugby, UK. I.C. Kemp, E.K. Macdonald, 1988. Application of pinch technology to separation, reaction and batch processes. IChemE Symposium Series, 109, 239-257, Institution of Chemical Engineers, Rugby, UK. Y. Jia, W. Xiao, G.H. He, 2013, Petri Net Methodology for Optimization of Heat Integration and Batch Process Scheduling, Proceedings of the 6th International Conference on Process Systems Engineering (PSE ASIA), Kuala Lumpur, Malaysia.