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Santanu Bandyopadhyay - One of the best experts on this subject based on the ideXlab platform.
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Maximising heat recovery in batch processes via product streams storage and shifting
Journal of Cleaner Production, 2016Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:In a batch process, either direct or indirect heat integration may be employed. The former involves direct heat transfer from hot to Cold process streams. In the latter, heat from a hot process stream is first transferred to an intermediate fluid where the heat is stored until it is finally transferred to a Cold stream. Storage of product streams allows direct heat integration to be delayed, thereby providing an opportunity for energy conservation while avoiding the use of an intermediate fluid. This paper presents a new methodology for batch heat integration that involves the direct storage of product streams within the procedure to set the minimum Utility targets. Application of the proposed methodology on illustrative examples demonstrates that significant energy reduction can be achieved by shifting product streams on the time scale. Potential reductions of 33.2% Cold Utility and 45.1% hot Utility were estimated for the first example when the product stream was stored. Similarly, reductions of 3.5% Cold Utility and 6.5% hot Utility were observed for a two-product batch plant when the cooling requirement for one of the products was shifted on time scale.
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A Linear Mathematical Model to Determine the Minimum Utility Targets for a Batch Process
Chemical engineering transactions, 2015Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:This paper presents a mathematical model to determine the minimum Utility targets for a batch process. The model was developed based on the source-demand classification of process streams where each stream was simultaneously treated as a source at its shifted supply temperature and as a demand at its shifted target temperature. The proposed model was formulated as a linear programming model (LP) and hence, guarantees the global optimal solution. The mathematical model can be used to calculate the Utility targets for any fixed-schedule batch process. As the formulation is linear solutions, it can be guaranteed to be globally optimal. Applications of the proposed mathematical formulation on two illustrative examples demonstrate significant energy saving potential. Potential reductions of 52 % in hot Utility and 48 % in Cold Utility have been estimated for the first example. Similarly, reductions of 71 % in hot Utility and 65 % in Cold Utility can be potentially achieved for the second example.
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Indirect thermal integration for batch processes
Applied Thermal Engineering, 2014Co-Authors: Nitin Dutt Chaturvedi, Santanu BandyopadhyayAbstract:Abstract Rigorous algorithms to target the minimum Utility requirements for single as well as cyclic batch processes are proposed in this paper. Practically, heat integration between two different time intervals requires indirect integration through intermediate fluid. Targets, calculated via proposed methodology, account for indirect thermal integration in batch process. The proposed methodology overcomes limitations of existing methodologies and guarantees the optimality as it is proved to be optimum using rigorous mathematical arguments. This methodology is applicable to any fixed-scheduled batch process. Applicability of the proposed methodology is demonstrated through illustrative examples. In one of the illustrative examples, a reduction of 18.7% and 16.4% (in comparison to time slice model) is observed in hot and Cold Utility requirements, respectively.
Zainuddin Abdul Manan - One of the best experts on this subject based on the ideXlab platform.
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A mathematical model for energy targeting of a batch process with flexible schedule
Journal of Cleaner Production, 2017Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan AlwiAbstract:This paper presents a mathematical model to determine the minimum energy targets for a batch process with flexible schedule. Techniques developed for flexible-schedule batch processes typically result in nonlinear formulations. The proposed model was formulated as a mixed integer linear programming model (MILP). The model is developed based on the source-demand classification of process streams instead of the typical classification of hot and Cold streams. In such classification, each stream is simultaneously treated as a source at its shifted supply temperature, and as a demand at its shifted target temperature. Such classification eliminates the model's non-linearity and reduces its complexity as well as the solution time. The mathematical model can be used to calculate the Utility targets for a flexible-schedule batch process. Application of the proposed mathematical formulation demonstrates significant energy saving potential. The first illustrative example predicted a potential reduction of 11% Cold Utility and 14% hot Utility. In the second illustrative example, up to 35% hot Utility reduction and 62% Cold Utility reduction could be achieved.
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Maximising heat recovery in batch processes via product streams storage and shifting
Journal of Cleaner Production, 2016Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:In a batch process, either direct or indirect heat integration may be employed. The former involves direct heat transfer from hot to Cold process streams. In the latter, heat from a hot process stream is first transferred to an intermediate fluid where the heat is stored until it is finally transferred to a Cold stream. Storage of product streams allows direct heat integration to be delayed, thereby providing an opportunity for energy conservation while avoiding the use of an intermediate fluid. This paper presents a new methodology for batch heat integration that involves the direct storage of product streams within the procedure to set the minimum Utility targets. Application of the proposed methodology on illustrative examples demonstrates that significant energy reduction can be achieved by shifting product streams on the time scale. Potential reductions of 33.2% Cold Utility and 45.1% hot Utility were estimated for the first example when the product stream was stored. Similarly, reductions of 3.5% Cold Utility and 6.5% hot Utility were observed for a two-product batch plant when the cooling requirement for one of the products was shifted on time scale.
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A Linear Mathematical Model to Determine the Minimum Utility Targets for a Batch Process
Chemical engineering transactions, 2015Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:This paper presents a mathematical model to determine the minimum Utility targets for a batch process. The model was developed based on the source-demand classification of process streams where each stream was simultaneously treated as a source at its shifted supply temperature and as a demand at its shifted target temperature. The proposed model was formulated as a linear programming model (LP) and hence, guarantees the global optimal solution. The mathematical model can be used to calculate the Utility targets for any fixed-schedule batch process. As the formulation is linear solutions, it can be guaranteed to be globally optimal. Applications of the proposed mathematical formulation on two illustrative examples demonstrate significant energy saving potential. Potential reductions of 52 % in hot Utility and 48 % in Cold Utility have been estimated for the first example. Similarly, reductions of 71 % in hot Utility and 65 % in Cold Utility can be potentially achieved for the second example.
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heat exchanger network cost optimization considering multiple utilities and different types of heat exchangers
Computers & Chemical Engineering, 2013Co-Authors: Sharifah Rafidah Wan Alwi, Zainuddin Abdul MananAbstract:Abstract Supertargeting based on composite curves (CC) is widely used to determine the optimum approach temperature (Δ T min ) that yields the minimum total cost for heat exchange networks (HEN). Supertargeting using CC has two key limitations. Firstly, the HEN area calculations are drastically simplified through the assumption that CC segments may be considered as pseudo-single hot and Cold streams exchanging heat via only one exchanger that is governed by a single cost correlation. Secondly, the current Supertargeting approach of considering only one hot and one Cold Utility level may lead to a crude estimation of the total HEN cost and the optimum Δ T min . This work presents the stream temperature vs. enthalpy plot supertargeting (STEPS) method that overcomes these limitations. This paper proves that supertargeting based on CC can lead to up to 50% error in the total cost target and poor Δ T min estimations.
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Retrofit of palm oil refinery to improve energy consumption and reduce fouling costs
1994Co-Authors: Zainuddin Abdul Manan, Feruz Mohd YusofAbstract:This paper presents the results of a detailed process integration retrofit study done on a palm oil refinery. The study, which is based on pinch technology is aimed at optimizing the energy consumption and recovering losses from the process streams of the existing plant. Bulk of the losses can be attributed to suboptimal heat recovery network structure and heat exchanger fouling effects. Previous pinch-based studies on fouling costs reductions were focused on grassroot designs. Retrofit studies reported for palm oil refineries were slightly different in approach and did not take into account of the effects of heat exchanger fouling. The presents study demonstrates that notwithstanding the existing integration scheme employed in the refinery, energy savings of 71% in hot Utility and 52% in Cold Utility with payback period of less than 2 years is possible. The proposed scheme eliminates the need for routine maintenance downtime dedicated for cleaning of fouled exchangers. As a result, energy consumption is further improved and productivity increased.
Nitin Dutt Chaturvedi - One of the best experts on this subject based on the ideXlab platform.
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A mathematical model for energy targeting of a batch process with flexible schedule
Journal of Cleaner Production, 2017Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan AlwiAbstract:This paper presents a mathematical model to determine the minimum energy targets for a batch process with flexible schedule. Techniques developed for flexible-schedule batch processes typically result in nonlinear formulations. The proposed model was formulated as a mixed integer linear programming model (MILP). The model is developed based on the source-demand classification of process streams instead of the typical classification of hot and Cold streams. In such classification, each stream is simultaneously treated as a source at its shifted supply temperature, and as a demand at its shifted target temperature. Such classification eliminates the model's non-linearity and reduces its complexity as well as the solution time. The mathematical model can be used to calculate the Utility targets for a flexible-schedule batch process. Application of the proposed mathematical formulation demonstrates significant energy saving potential. The first illustrative example predicted a potential reduction of 11% Cold Utility and 14% hot Utility. In the second illustrative example, up to 35% hot Utility reduction and 62% Cold Utility reduction could be achieved.
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Maximising heat recovery in batch processes via product streams storage and shifting
Journal of Cleaner Production, 2016Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:In a batch process, either direct or indirect heat integration may be employed. The former involves direct heat transfer from hot to Cold process streams. In the latter, heat from a hot process stream is first transferred to an intermediate fluid where the heat is stored until it is finally transferred to a Cold stream. Storage of product streams allows direct heat integration to be delayed, thereby providing an opportunity for energy conservation while avoiding the use of an intermediate fluid. This paper presents a new methodology for batch heat integration that involves the direct storage of product streams within the procedure to set the minimum Utility targets. Application of the proposed methodology on illustrative examples demonstrates that significant energy reduction can be achieved by shifting product streams on the time scale. Potential reductions of 33.2% Cold Utility and 45.1% hot Utility were estimated for the first example when the product stream was stored. Similarly, reductions of 3.5% Cold Utility and 6.5% hot Utility were observed for a two-product batch plant when the cooling requirement for one of the products was shifted on time scale.
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A Linear Mathematical Model to Determine the Minimum Utility Targets for a Batch Process
Chemical engineering transactions, 2015Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:This paper presents a mathematical model to determine the minimum Utility targets for a batch process. The model was developed based on the source-demand classification of process streams where each stream was simultaneously treated as a source at its shifted supply temperature and as a demand at its shifted target temperature. The proposed model was formulated as a linear programming model (LP) and hence, guarantees the global optimal solution. The mathematical model can be used to calculate the Utility targets for any fixed-schedule batch process. As the formulation is linear solutions, it can be guaranteed to be globally optimal. Applications of the proposed mathematical formulation on two illustrative examples demonstrate significant energy saving potential. Potential reductions of 52 % in hot Utility and 48 % in Cold Utility have been estimated for the first example. Similarly, reductions of 71 % in hot Utility and 65 % in Cold Utility can be potentially achieved for the second example.
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Indirect thermal integration for batch processes
Applied Thermal Engineering, 2014Co-Authors: Nitin Dutt Chaturvedi, Santanu BandyopadhyayAbstract:Abstract Rigorous algorithms to target the minimum Utility requirements for single as well as cyclic batch processes are proposed in this paper. Practically, heat integration between two different time intervals requires indirect integration through intermediate fluid. Targets, calculated via proposed methodology, account for indirect thermal integration in batch process. The proposed methodology overcomes limitations of existing methodologies and guarantees the optimality as it is proved to be optimum using rigorous mathematical arguments. This methodology is applicable to any fixed-scheduled batch process. Applicability of the proposed methodology is demonstrated through illustrative examples. In one of the illustrative examples, a reduction of 18.7% and 16.4% (in comparison to time slice model) is observed in hot and Cold Utility requirements, respectively.
M. Angela A. Meireles - One of the best experts on this subject based on the ideXlab platform.
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New proposal for production of bioactive compounds by supercritical technology integrated to a sugarcane biorefinery
Clean Technologies and Environmental Policy, 2014Co-Authors: Diego T. Santos, Juliana Q. Albarelli, Adriano V. Ensinas, François Maréchal, Maurício A. Rostagno, M. Angela A. MeirelesAbstract:The construction of a supercritical fluid extraction (SFE) plant inside or in close proximity to a sugarcane biorefinery producing first and second generation ethanol demonstrated to be very promising, increasing the economic potential of the SFE process in up to 57 %, since the SFE plant could use directly the ethanol, CO_2, heat, and electricity already available, with lower prices. In this study, Brazilian ginseng roots were used as model bioactive compounds source and first the statistical influence of the extraction conditions including pressure (10–20 MPa), temperature (323–363 K), and CO_2/ethanol proportion ratio (90:10, 50:50, and 0:100 %, w/w) on the β-ecdysone content in the extracts was experimentally evaluated and compared with literature results. SFE process evaluated experimentally at the present study showed higher selective extraction for β-ecdysone from Brazilian ginseng roots, providing an extract with up to 2.16 times higher β-ecdysone than the results obtained in previous studies. Thermal integration of the SFE process diminished energy requirements of the process, resulting in a reduction of Cold Utility requirement of 87 % and a final electricity demand of 7.5 kWh/g of β-ecdysone in the extract. In a situation in which the Brazilian ginseng roots price was increased to 4.71 USD/g, only the SFE integrated with the biorefinery solution would be economically feasible. Finally, the selling of the ginseng roots leftover could be an interesting answer to increase the economical attractiveness of the integrated SFE process to the biorefinery.
Sharifah Rafidah Wan Alwi - One of the best experts on this subject based on the ideXlab platform.
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A mathematical model for energy targeting of a batch process with flexible schedule
Journal of Cleaner Production, 2017Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan AlwiAbstract:This paper presents a mathematical model to determine the minimum energy targets for a batch process with flexible schedule. Techniques developed for flexible-schedule batch processes typically result in nonlinear formulations. The proposed model was formulated as a mixed integer linear programming model (MILP). The model is developed based on the source-demand classification of process streams instead of the typical classification of hot and Cold streams. In such classification, each stream is simultaneously treated as a source at its shifted supply temperature, and as a demand at its shifted target temperature. Such classification eliminates the model's non-linearity and reduces its complexity as well as the solution time. The mathematical model can be used to calculate the Utility targets for a flexible-schedule batch process. Application of the proposed mathematical formulation demonstrates significant energy saving potential. The first illustrative example predicted a potential reduction of 11% Cold Utility and 14% hot Utility. In the second illustrative example, up to 35% hot Utility reduction and 62% Cold Utility reduction could be achieved.
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Maximising heat recovery in batch processes via product streams storage and shifting
Journal of Cleaner Production, 2016Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:In a batch process, either direct or indirect heat integration may be employed. The former involves direct heat transfer from hot to Cold process streams. In the latter, heat from a hot process stream is first transferred to an intermediate fluid where the heat is stored until it is finally transferred to a Cold stream. Storage of product streams allows direct heat integration to be delayed, thereby providing an opportunity for energy conservation while avoiding the use of an intermediate fluid. This paper presents a new methodology for batch heat integration that involves the direct storage of product streams within the procedure to set the minimum Utility targets. Application of the proposed methodology on illustrative examples demonstrates that significant energy reduction can be achieved by shifting product streams on the time scale. Potential reductions of 33.2% Cold Utility and 45.1% hot Utility were estimated for the first example when the product stream was stored. Similarly, reductions of 3.5% Cold Utility and 6.5% hot Utility were observed for a two-product batch plant when the cooling requirement for one of the products was shifted on time scale.
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A Linear Mathematical Model to Determine the Minimum Utility Targets for a Batch Process
Chemical engineering transactions, 2015Co-Authors: Nitin Dutt Chaturvedi, Zainuddin Abdul Manan, Sharifah Rafidah Wan Alwi, Santanu BandyopadhyayAbstract:This paper presents a mathematical model to determine the minimum Utility targets for a batch process. The model was developed based on the source-demand classification of process streams where each stream was simultaneously treated as a source at its shifted supply temperature and as a demand at its shifted target temperature. The proposed model was formulated as a linear programming model (LP) and hence, guarantees the global optimal solution. The mathematical model can be used to calculate the Utility targets for any fixed-schedule batch process. As the formulation is linear solutions, it can be guaranteed to be globally optimal. Applications of the proposed mathematical formulation on two illustrative examples demonstrate significant energy saving potential. Potential reductions of 52 % in hot Utility and 48 % in Cold Utility have been estimated for the first example. Similarly, reductions of 71 % in hot Utility and 65 % in Cold Utility can be potentially achieved for the second example.
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heat exchanger network cost optimization considering multiple utilities and different types of heat exchangers
Computers & Chemical Engineering, 2013Co-Authors: Sharifah Rafidah Wan Alwi, Zainuddin Abdul MananAbstract:Abstract Supertargeting based on composite curves (CC) is widely used to determine the optimum approach temperature (Δ T min ) that yields the minimum total cost for heat exchange networks (HEN). Supertargeting using CC has two key limitations. Firstly, the HEN area calculations are drastically simplified through the assumption that CC segments may be considered as pseudo-single hot and Cold streams exchanging heat via only one exchanger that is governed by a single cost correlation. Secondly, the current Supertargeting approach of considering only one hot and one Cold Utility level may lead to a crude estimation of the total HEN cost and the optimum Δ T min . This work presents the stream temperature vs. enthalpy plot supertargeting (STEPS) method that overcomes these limitations. This paper proves that supertargeting based on CC can lead to up to 50% error in the total cost target and poor Δ T min estimations.