Kooperativer Bibliotheksverbund

UID:

Format: 1 Online-Ressource (XV, 489 p. 257 illus., 220 illus. in color)

Edition: 1st ed. 2024

ISBN: 9783031572708

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-57269-2

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-57271-5

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-57272-2

Language: English

DOI: 10.1007/978-3-031-57270-8

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: XVII, 110 p. 92 illus., 85 illus. in color. , online resource.

ISBN: 9783319917221

Content: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.

Note: Chapter 1- Introduction -- Chapter 2- Process simulators -- Chapter 3- Metaheuristic optimization programs -- Chapter 4- interlinking between process simulators and optimization programs -- Chapter 5- Performance evaluation -- Chapter 6- Optimization of industrial process 1 -- Chapter 7- Optimization of industrial process 2 -- Chapter 8- Bibliography -- Appendix.

In: Springer eBooks

Additional Edition: Printed edition: ISBN 9783319917214

Additional Edition: Printed edition: ISBN 9783319917238

Language: English

DOI: 10.1007/978-3-319-91722-1

URL: https://doi.org/10.1007/978-3-319-91722-1

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (532 pages)

ISBN: 0-12-818179-6 , 0-12-818178-8

Note: Front Cover -- Strategic Planning for the Sustainable Production of Biofuels -- Copyright Page -- Contents -- Preface -- 1 Introduction -- 1.1 Importance of Biofuels and Biorefineries -- 1.2 Strategic Planning -- 1.3 Optimization -- 1.4 Sustainability -- 1.5 Description of the Book -- References -- Further Reading -- 2 Environmental Aspects in the Strategic Planning of a Biomass Conversion System -- 2.1 Introduction -- 2.2 Outline of the Optimization Model -- 2.3 Mathematical Model -- 2.3.1 Mass Balances -- 2.3.2 Maximum Availability for Feedstocks -- 2.3.3 Maximum Products Demand -- 2.3.4 Maximum Processing Limits -- 2.3.5 Objective Functions -- 2.3.6 Economic Objective -- 2.3.7 Environmental Objective -- 2.4 Solution Strategy -- 2.5 Case Study -- 2.6 Sensitivity Analysis -- 2.7 Concluding Remarks -- 2.8 Nomenclature for Chapter 2 -- 2.8.1 Parameters -- 2.8.2 Variables -- 2.8.3 Indexes -- References -- 3 Optimal Planning and Site Selection for Distributed Multiproduct Biorefineries Involving Economic, Environmental, and Soc... -- 3.1 Introduction -- 3.2 Problem Statement -- 3.3 Model Formulation -- 3.3.1 Mass Balances for Harvesting Sites -- 3.3.2 Mass Balances for Processing Hubs (Secondary Plants) -- 3.3.3 Raw Materials in Hubs -- 3.3.4 Products in Hubs -- 3.3.5 Mass Balances for the Main Plant -- 3.3.6 Raw Materials in the Main Plant -- 3.3.7 Products in the Main Plant -- 3.3.8 Mass Balances for Markets -- 3.3.9 Constraints for Total Product Sales -- 3.3.10 Storage Constraints -- 3.3.11 Transportation Constraints -- 3.3.12 Processing Constraints -- 3.3.13 Availability Constraints -- 3.3.14 Start and End Storage Constraints -- 3.3.15 Objective Functions -- 3.3.15.1 Economic objective function -- 3.3.15.2 Environmental objective function -- 3.3.15.3 Social objective function -- 3.3.16 Remarks on the Model -- 3.4 Case Study -- 3.5 Discussion. , 3.6 Concluding Remarks -- 3.7 Nomenclature -- 3.7.1 Sets -- 3.7.2 Indexes -- 3.7.3 Parameters -- 3.7.4 Variables -- 3.7.5 Binary Variables -- 3.7.6 Boolean Variables -- References -- Further Reading -- 4 Distributed Biorefining Networks for the Value-Added Processing of Water Hyacinth -- 4.1 Introduction -- 4.2 Outline of the Model Formulation -- 4.3 Model Formulation -- 4.3.1 Mass Balance for the Harvesting of Water Hyacinth -- 4.3.2 Availability of the Harvested Water Hyacinth -- 4.3.3 Mass Balance for the Splitters Before the Processing Plants -- 4.3.4 Balances for Mixers Before the Processing Facilities -- 4.3.5 Balances for the Technologies Used in the Processing Facilities -- 4.3.6 Balances for the Mixers Before the Central Processing Facilities -- 4.3.7 Balances for the Technologies of Central Processing Facilities -- 4.3.8 Balances for the Splitters After Each Processing Facility -- 4.3.9 Balances for the Splitters After the Central Processing Facilities -- 4.3.10 Balances for the Markets -- 4.3.11 Demands for the Consumers -- 4.3.12 Balances for the Water Treatment in Each Source -- 4.3.13 Water Treatment Technology in Each Source -- 4.3.14 Mass Balance for the Splitters After the Water Treatment -- 4.3.15 Mass Balance for the Mixers Before Each Water Consumer -- 4.3.16 Component Balance for the Mixers Before Each Water Consumer -- 4.3.17 Demand for Water Consumers -- 4.3.18 Constraints for the Water Quality for Each Consumer -- 4.3.19 Operational Cost for the Processing Facilities -- 4.3.20 Capital Cost for the Processing Facilities -- 4.3.21 Operational Cost for the Central Processing Facilities -- 4.3.22 Capital Cost for the Central Processing Facilities -- 4.3.23 Operational Cost for the Water Treatment Units -- 4.3.24 Capital Cost for the Water Treatment Units -- 4.3.25 Harvesting Cost -- 4.3.26 Water Transportation Cost. , 4.3.27 Biomass Transportation Cost -- 4.3.28 Products Transportation Cost -- 4.3.29 Total Operational Cost -- 4.3.30 Total Capital Cost -- 4.3.31 Total Sales -- 4.3.32 Total Net Annual Cost (Negative of Total Net Profit) -- 4.3.33 Percentage of Eliminated Water Hyacinth -- 4.4 Remarks on the Model -- 4.5 Results -- 4.6 Concluding Remarks -- 4.7 Nomenclature -- 4.7.1 Parameters -- 4.7.2 Variables -- 4.7.3 Binary Variables -- References -- 5 Optimization of the Supply Chain Associated to the Production of Bioethanol From Residues of Agave From the Tequila Proce... -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Model Formulation -- 5.3.1 Mass Balances in Agave Cultivating Areas -- 5.3.2 Maximum Available Agave -- 5.3.3 Mass Balances in Tequila Industry -- 5.3.4 Residues of Agave Bagasse From the Tequila Industry -- 5.3.5 Mass Balances in Distributed Processing Plants for Bioethanol Production -- 5.3.6 Distribution of Products From Processing Plants to Markets -- 5.3.7 Product Demands -- 5.3.8 Cost of the Distributed Bioethanol Processing Plants -- 5.3.9 Transportation Cost for Stalks to Distributed and Central Plants -- 5.3.10 Transportation Cost From the Tequila Industries to Distributed and Central Bioethanol Processing Plants -- 5.3.11 Transportation Cost for Products -- 5.3.12 Objective Function -- 5.4 Case Study -- 5.4.1 Scenario A (Economic Solution With a Constraint of 1% for the Bioethanol Demand in Each Consumption Site) -- 5.4.2 Scenario B (Solution Without Constraint for the Demand of Bioethanol in the Markets) -- 5.4.3 Scenario C (Increasing the Cultivation Area) -- 5.5 Concluding Remarks -- 5.6 Nomenclature -- 5.6.1 Indexes -- 5.6.2 Sets -- 5.6.3 Parameters -- 5.6.4 Variables -- References -- 6 Financial Risk Assessment and Optimal Planning of Biofuels Supply Chains Under Uncertainty -- 6.1 Introduction -- 6.2 Problem Statement. , 6.3 Mathematical Model Formulation -- 6.4 Objective 1: Expected Profit -- 6.5 Objective 2: Worst Case for the Net Annual Profit -- 6.6 Results and Discussion -- 6.6.1 Distribution of Raw Material Price Without Correlation -- 6.6.2 Case With Correlated Values -- 6.7 Concluding Remarks -- 6.8 Nomenclature -- 6.8.1 Variables -- 6.8.2 Binary Variables -- 6.8.3 Parameters -- 7 Stochastic Design of Biorefinery Supply Chains Considering Economic and Environmental Objectives -- 7.1 Introduction -- 7.2 Problem Statement -- 7.3 Mathematical Formulation -- 7.3.1 Availability of Raw Material -- 7.3.2 Mass Balances in the Suppliers -- 7.3.3 Mass Balances in the Processing Facilities -- 7.3.4 Mass Balances in the Markets -- 7.3.5 Demand Constraint -- 7.3.6 Relationships for the Input-Output of the Distributed Material -- 7.3.7 Transportation Limits and Transportation Costs -- 7.3.8 Processing Stages in the Processing Facilities -- 7.3.9 Processing Constraints for the First Stage -- 7.3.10 Processing Constraints for the Second Stage -- 7.3.11 Storage Modeling -- 7.3.12 Revenue From Selling Products -- 7.3.13 Raw Material Production Cost -- 7.3.14 Economic Objective Function -- 7.3.15 Environmental Objective -- 7.4 Solution Approach -- 7.4.1 Definition of the Superstructure -- 7.4.2 Identification of the Parameters Under Uncertainty -- 7.4.3 Sampling for Uncertain Parameters -- 7.4.4 Solving of the Associated Deterministic Optimization Problem -- 7.4.5 Comparison Between Different Supply Chain Topologies -- 7.4.6 Changing of the Upper Limit for the Environmental Impact -- 7.4.7 Standardized Regression Coefficients -- 7.5 Case Study -- 7.6 Computer-Aided Tools -- 7.7 Results and Discussion -- 7.8 Concluding Remarks -- 7.9 Nomenclature -- 7.9.1 Indexes -- 7.9.2 Variables -- 7.9.3 Parameters -- References. , 8 Mixed-Integer Dynamic Optimization for Planning Distributed Biorefineries -- 8.1 Introduction -- 8.2 Problem Statement -- 8.3 Mixed-Integer Dynamic Mathematical Optimization Model -- 8.3.1 Raw Material Inventory at Suppliers -- 8.3.2 Raw Material Inventory at Processing Facilities -- 8.3.3 Raw Material Inventory at Main Processing Facility -- 8.3.4 Product Inventory at Processing Facilities -- 8.3.5 Product Inventory at Main Processing Facility -- 8.3.6 Product Inventory at Distribution Centers -- 8.3.7 Continuity of the Inventories at the Beginning and End of the Time Horizon -- 8.3.8 Raw Material Orders From General Facilities to Suppliers -- 8.3.9 Raw Material Orders From the Main Facility to Suppliers -- 8.3.10 Product Orders From the Distribution Centers to the Facilities -- 8.3.11 Product Orders From the Distribution Centers to the Main Facility -- 8.3.12 Product Orders From Consumers to the Distribution Centers -- 8.3.13 Continuity of the Inventories at the Beginning and End of the Horizon -- 8.3.14 Availability of Raw Material -- 8.3.15 Constraints for the Demand -- 8.3.16 Constraints to Control the Orders From Consumers to Distribution Centers -- 8.3.17 Constraints for Transported Flow Rate at the Outlet and Inlet Locations -- 8.3.18 Transportation Limits -- 8.3.19 Processing -- 8.3.20 Economies of Scale for Processing Facilities -- 8.3.21 Storage Modeling -- 8.3.22 Operating Cost -- 8.3.23 Total Capital Cost -- 8.3.24 Transportation Cost -- 8.3.25 Storage Cost -- 8.3.26 Net Annual Profit -- 8.3.27 Control Product Demand -- 8.4 Nonlinear Model Predictive Control Approach -- 8.5 Solution Approach for the MIDO Problem -- 8.6 Results -- 8.7 Conclusions -- 8.8 Nomenclature -- 8.8.1 Parameters -- 8.8.2 Binary Variables -- 8.8.3 Variables -- References -- Appendices: Code Used in the Book. , Appendix A GAMS Code for Model of Chapter 2, Environmental Aspects in the Strategic Planning of a Biomass Conversion System.

Language: English

UID:

ISBN: 0-443-13572-X , 0-443-13571-1

Series Statement: Developments in environmental modelling ; volume 32

Language: English

UID:

ISBN: 0-443-13572-X , 0-443-13571-1

Series Statement: Developments in environmental modelling ; volume 32

Language: English

UID:

ISBN: 0-443-13572-X , 0-443-13571-1

Series Statement: Developments in environmental modelling ; volume 32

Language: English

UID:

Format: 1 online resource (532 pages)

ISBN: 0-12-818179-6 , 0-12-818178-8

Note: Front Cover -- Strategic Planning for the Sustainable Production of Biofuels -- Copyright Page -- Contents -- Preface -- 1 Introduction -- 1.1 Importance of Biofuels and Biorefineries -- 1.2 Strategic Planning -- 1.3 Optimization -- 1.4 Sustainability -- 1.5 Description of the Book -- References -- Further Reading -- 2 Environmental Aspects in the Strategic Planning of a Biomass Conversion System -- 2.1 Introduction -- 2.2 Outline of the Optimization Model -- 2.3 Mathematical Model -- 2.3.1 Mass Balances -- 2.3.2 Maximum Availability for Feedstocks -- 2.3.3 Maximum Products Demand -- 2.3.4 Maximum Processing Limits -- 2.3.5 Objective Functions -- 2.3.6 Economic Objective -- 2.3.7 Environmental Objective -- 2.4 Solution Strategy -- 2.5 Case Study -- 2.6 Sensitivity Analysis -- 2.7 Concluding Remarks -- 2.8 Nomenclature for Chapter 2 -- 2.8.1 Parameters -- 2.8.2 Variables -- 2.8.3 Indexes -- References -- 3 Optimal Planning and Site Selection for Distributed Multiproduct Biorefineries Involving Economic, Environmental, and Soc... -- 3.1 Introduction -- 3.2 Problem Statement -- 3.3 Model Formulation -- 3.3.1 Mass Balances for Harvesting Sites -- 3.3.2 Mass Balances for Processing Hubs (Secondary Plants) -- 3.3.3 Raw Materials in Hubs -- 3.3.4 Products in Hubs -- 3.3.5 Mass Balances for the Main Plant -- 3.3.6 Raw Materials in the Main Plant -- 3.3.7 Products in the Main Plant -- 3.3.8 Mass Balances for Markets -- 3.3.9 Constraints for Total Product Sales -- 3.3.10 Storage Constraints -- 3.3.11 Transportation Constraints -- 3.3.12 Processing Constraints -- 3.3.13 Availability Constraints -- 3.3.14 Start and End Storage Constraints -- 3.3.15 Objective Functions -- 3.3.15.1 Economic objective function -- 3.3.15.2 Environmental objective function -- 3.3.15.3 Social objective function -- 3.3.16 Remarks on the Model -- 3.4 Case Study -- 3.5 Discussion. , 3.6 Concluding Remarks -- 3.7 Nomenclature -- 3.7.1 Sets -- 3.7.2 Indexes -- 3.7.3 Parameters -- 3.7.4 Variables -- 3.7.5 Binary Variables -- 3.7.6 Boolean Variables -- References -- Further Reading -- 4 Distributed Biorefining Networks for the Value-Added Processing of Water Hyacinth -- 4.1 Introduction -- 4.2 Outline of the Model Formulation -- 4.3 Model Formulation -- 4.3.1 Mass Balance for the Harvesting of Water Hyacinth -- 4.3.2 Availability of the Harvested Water Hyacinth -- 4.3.3 Mass Balance for the Splitters Before the Processing Plants -- 4.3.4 Balances for Mixers Before the Processing Facilities -- 4.3.5 Balances for the Technologies Used in the Processing Facilities -- 4.3.6 Balances for the Mixers Before the Central Processing Facilities -- 4.3.7 Balances for the Technologies of Central Processing Facilities -- 4.3.8 Balances for the Splitters After Each Processing Facility -- 4.3.9 Balances for the Splitters After the Central Processing Facilities -- 4.3.10 Balances for the Markets -- 4.3.11 Demands for the Consumers -- 4.3.12 Balances for the Water Treatment in Each Source -- 4.3.13 Water Treatment Technology in Each Source -- 4.3.14 Mass Balance for the Splitters After the Water Treatment -- 4.3.15 Mass Balance for the Mixers Before Each Water Consumer -- 4.3.16 Component Balance for the Mixers Before Each Water Consumer -- 4.3.17 Demand for Water Consumers -- 4.3.18 Constraints for the Water Quality for Each Consumer -- 4.3.19 Operational Cost for the Processing Facilities -- 4.3.20 Capital Cost for the Processing Facilities -- 4.3.21 Operational Cost for the Central Processing Facilities -- 4.3.22 Capital Cost for the Central Processing Facilities -- 4.3.23 Operational Cost for the Water Treatment Units -- 4.3.24 Capital Cost for the Water Treatment Units -- 4.3.25 Harvesting Cost -- 4.3.26 Water Transportation Cost. , 4.3.27 Biomass Transportation Cost -- 4.3.28 Products Transportation Cost -- 4.3.29 Total Operational Cost -- 4.3.30 Total Capital Cost -- 4.3.31 Total Sales -- 4.3.32 Total Net Annual Cost (Negative of Total Net Profit) -- 4.3.33 Percentage of Eliminated Water Hyacinth -- 4.4 Remarks on the Model -- 4.5 Results -- 4.6 Concluding Remarks -- 4.7 Nomenclature -- 4.7.1 Parameters -- 4.7.2 Variables -- 4.7.3 Binary Variables -- References -- 5 Optimization of the Supply Chain Associated to the Production of Bioethanol From Residues of Agave From the Tequila Proce... -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Model Formulation -- 5.3.1 Mass Balances in Agave Cultivating Areas -- 5.3.2 Maximum Available Agave -- 5.3.3 Mass Balances in Tequila Industry -- 5.3.4 Residues of Agave Bagasse From the Tequila Industry -- 5.3.5 Mass Balances in Distributed Processing Plants for Bioethanol Production -- 5.3.6 Distribution of Products From Processing Plants to Markets -- 5.3.7 Product Demands -- 5.3.8 Cost of the Distributed Bioethanol Processing Plants -- 5.3.9 Transportation Cost for Stalks to Distributed and Central Plants -- 5.3.10 Transportation Cost From the Tequila Industries to Distributed and Central Bioethanol Processing Plants -- 5.3.11 Transportation Cost for Products -- 5.3.12 Objective Function -- 5.4 Case Study -- 5.4.1 Scenario A (Economic Solution With a Constraint of 1% for the Bioethanol Demand in Each Consumption Site) -- 5.4.2 Scenario B (Solution Without Constraint for the Demand of Bioethanol in the Markets) -- 5.4.3 Scenario C (Increasing the Cultivation Area) -- 5.5 Concluding Remarks -- 5.6 Nomenclature -- 5.6.1 Indexes -- 5.6.2 Sets -- 5.6.3 Parameters -- 5.6.4 Variables -- References -- 6 Financial Risk Assessment and Optimal Planning of Biofuels Supply Chains Under Uncertainty -- 6.1 Introduction -- 6.2 Problem Statement. , 6.3 Mathematical Model Formulation -- 6.4 Objective 1: Expected Profit -- 6.5 Objective 2: Worst Case for the Net Annual Profit -- 6.6 Results and Discussion -- 6.6.1 Distribution of Raw Material Price Without Correlation -- 6.6.2 Case With Correlated Values -- 6.7 Concluding Remarks -- 6.8 Nomenclature -- 6.8.1 Variables -- 6.8.2 Binary Variables -- 6.8.3 Parameters -- 7 Stochastic Design of Biorefinery Supply Chains Considering Economic and Environmental Objectives -- 7.1 Introduction -- 7.2 Problem Statement -- 7.3 Mathematical Formulation -- 7.3.1 Availability of Raw Material -- 7.3.2 Mass Balances in the Suppliers -- 7.3.3 Mass Balances in the Processing Facilities -- 7.3.4 Mass Balances in the Markets -- 7.3.5 Demand Constraint -- 7.3.6 Relationships for the Input-Output of the Distributed Material -- 7.3.7 Transportation Limits and Transportation Costs -- 7.3.8 Processing Stages in the Processing Facilities -- 7.3.9 Processing Constraints for the First Stage -- 7.3.10 Processing Constraints for the Second Stage -- 7.3.11 Storage Modeling -- 7.3.12 Revenue From Selling Products -- 7.3.13 Raw Material Production Cost -- 7.3.14 Economic Objective Function -- 7.3.15 Environmental Objective -- 7.4 Solution Approach -- 7.4.1 Definition of the Superstructure -- 7.4.2 Identification of the Parameters Under Uncertainty -- 7.4.3 Sampling for Uncertain Parameters -- 7.4.4 Solving of the Associated Deterministic Optimization Problem -- 7.4.5 Comparison Between Different Supply Chain Topologies -- 7.4.6 Changing of the Upper Limit for the Environmental Impact -- 7.4.7 Standardized Regression Coefficients -- 7.5 Case Study -- 7.6 Computer-Aided Tools -- 7.7 Results and Discussion -- 7.8 Concluding Remarks -- 7.9 Nomenclature -- 7.9.1 Indexes -- 7.9.2 Variables -- 7.9.3 Parameters -- References. , 8 Mixed-Integer Dynamic Optimization for Planning Distributed Biorefineries -- 8.1 Introduction -- 8.2 Problem Statement -- 8.3 Mixed-Integer Dynamic Mathematical Optimization Model -- 8.3.1 Raw Material Inventory at Suppliers -- 8.3.2 Raw Material Inventory at Processing Facilities -- 8.3.3 Raw Material Inventory at Main Processing Facility -- 8.3.4 Product Inventory at Processing Facilities -- 8.3.5 Product Inventory at Main Processing Facility -- 8.3.6 Product Inventory at Distribution Centers -- 8.3.7 Continuity of the Inventories at the Beginning and End of the Time Horizon -- 8.3.8 Raw Material Orders From General Facilities to Suppliers -- 8.3.9 Raw Material Orders From the Main Facility to Suppliers -- 8.3.10 Product Orders From the Distribution Centers to the Facilities -- 8.3.11 Product Orders From the Distribution Centers to the Main Facility -- 8.3.12 Product Orders From Consumers to the Distribution Centers -- 8.3.13 Continuity of the Inventories at the Beginning and End of the Horizon -- 8.3.14 Availability of Raw Material -- 8.3.15 Constraints for the Demand -- 8.3.16 Constraints to Control the Orders From Consumers to Distribution Centers -- 8.3.17 Constraints for Transported Flow Rate at the Outlet and Inlet Locations -- 8.3.18 Transportation Limits -- 8.3.19 Processing -- 8.3.20 Economies of Scale for Processing Facilities -- 8.3.21 Storage Modeling -- 8.3.22 Operating Cost -- 8.3.23 Total Capital Cost -- 8.3.24 Transportation Cost -- 8.3.25 Storage Cost -- 8.3.26 Net Annual Profit -- 8.3.27 Control Product Demand -- 8.4 Nonlinear Model Predictive Control Approach -- 8.5 Solution Approach for the MIDO Problem -- 8.6 Results -- 8.7 Conclusions -- 8.8 Nomenclature -- 8.8.1 Parameters -- 8.8.2 Binary Variables -- 8.8.3 Variables -- References -- Appendices: Code Used in the Book. , Appendix A GAMS Code for Model of Chapter 2, Environmental Aspects in the Strategic Planning of a Biomass Conversion System.

Language: English

UID:

Format: 1 online resource (532 pages)

ISBN: 0-12-818179-6 , 0-12-818178-8

Note: Front Cover -- Strategic Planning for the Sustainable Production of Biofuels -- Copyright Page -- Contents -- Preface -- 1 Introduction -- 1.1 Importance of Biofuels and Biorefineries -- 1.2 Strategic Planning -- 1.3 Optimization -- 1.4 Sustainability -- 1.5 Description of the Book -- References -- Further Reading -- 2 Environmental Aspects in the Strategic Planning of a Biomass Conversion System -- 2.1 Introduction -- 2.2 Outline of the Optimization Model -- 2.3 Mathematical Model -- 2.3.1 Mass Balances -- 2.3.2 Maximum Availability for Feedstocks -- 2.3.3 Maximum Products Demand -- 2.3.4 Maximum Processing Limits -- 2.3.5 Objective Functions -- 2.3.6 Economic Objective -- 2.3.7 Environmental Objective -- 2.4 Solution Strategy -- 2.5 Case Study -- 2.6 Sensitivity Analysis -- 2.7 Concluding Remarks -- 2.8 Nomenclature for Chapter 2 -- 2.8.1 Parameters -- 2.8.2 Variables -- 2.8.3 Indexes -- References -- 3 Optimal Planning and Site Selection for Distributed Multiproduct Biorefineries Involving Economic, Environmental, and Soc... -- 3.1 Introduction -- 3.2 Problem Statement -- 3.3 Model Formulation -- 3.3.1 Mass Balances for Harvesting Sites -- 3.3.2 Mass Balances for Processing Hubs (Secondary Plants) -- 3.3.3 Raw Materials in Hubs -- 3.3.4 Products in Hubs -- 3.3.5 Mass Balances for the Main Plant -- 3.3.6 Raw Materials in the Main Plant -- 3.3.7 Products in the Main Plant -- 3.3.8 Mass Balances for Markets -- 3.3.9 Constraints for Total Product Sales -- 3.3.10 Storage Constraints -- 3.3.11 Transportation Constraints -- 3.3.12 Processing Constraints -- 3.3.13 Availability Constraints -- 3.3.14 Start and End Storage Constraints -- 3.3.15 Objective Functions -- 3.3.15.1 Economic objective function -- 3.3.15.2 Environmental objective function -- 3.3.15.3 Social objective function -- 3.3.16 Remarks on the Model -- 3.4 Case Study -- 3.5 Discussion. , 3.6 Concluding Remarks -- 3.7 Nomenclature -- 3.7.1 Sets -- 3.7.2 Indexes -- 3.7.3 Parameters -- 3.7.4 Variables -- 3.7.5 Binary Variables -- 3.7.6 Boolean Variables -- References -- Further Reading -- 4 Distributed Biorefining Networks for the Value-Added Processing of Water Hyacinth -- 4.1 Introduction -- 4.2 Outline of the Model Formulation -- 4.3 Model Formulation -- 4.3.1 Mass Balance for the Harvesting of Water Hyacinth -- 4.3.2 Availability of the Harvested Water Hyacinth -- 4.3.3 Mass Balance for the Splitters Before the Processing Plants -- 4.3.4 Balances for Mixers Before the Processing Facilities -- 4.3.5 Balances for the Technologies Used in the Processing Facilities -- 4.3.6 Balances for the Mixers Before the Central Processing Facilities -- 4.3.7 Balances for the Technologies of Central Processing Facilities -- 4.3.8 Balances for the Splitters After Each Processing Facility -- 4.3.9 Balances for the Splitters After the Central Processing Facilities -- 4.3.10 Balances for the Markets -- 4.3.11 Demands for the Consumers -- 4.3.12 Balances for the Water Treatment in Each Source -- 4.3.13 Water Treatment Technology in Each Source -- 4.3.14 Mass Balance for the Splitters After the Water Treatment -- 4.3.15 Mass Balance for the Mixers Before Each Water Consumer -- 4.3.16 Component Balance for the Mixers Before Each Water Consumer -- 4.3.17 Demand for Water Consumers -- 4.3.18 Constraints for the Water Quality for Each Consumer -- 4.3.19 Operational Cost for the Processing Facilities -- 4.3.20 Capital Cost for the Processing Facilities -- 4.3.21 Operational Cost for the Central Processing Facilities -- 4.3.22 Capital Cost for the Central Processing Facilities -- 4.3.23 Operational Cost for the Water Treatment Units -- 4.3.24 Capital Cost for the Water Treatment Units -- 4.3.25 Harvesting Cost -- 4.3.26 Water Transportation Cost. , 4.3.27 Biomass Transportation Cost -- 4.3.28 Products Transportation Cost -- 4.3.29 Total Operational Cost -- 4.3.30 Total Capital Cost -- 4.3.31 Total Sales -- 4.3.32 Total Net Annual Cost (Negative of Total Net Profit) -- 4.3.33 Percentage of Eliminated Water Hyacinth -- 4.4 Remarks on the Model -- 4.5 Results -- 4.6 Concluding Remarks -- 4.7 Nomenclature -- 4.7.1 Parameters -- 4.7.2 Variables -- 4.7.3 Binary Variables -- References -- 5 Optimization of the Supply Chain Associated to the Production of Bioethanol From Residues of Agave From the Tequila Proce... -- 5.1 Introduction -- 5.2 Problem Statement -- 5.3 Model Formulation -- 5.3.1 Mass Balances in Agave Cultivating Areas -- 5.3.2 Maximum Available Agave -- 5.3.3 Mass Balances in Tequila Industry -- 5.3.4 Residues of Agave Bagasse From the Tequila Industry -- 5.3.5 Mass Balances in Distributed Processing Plants for Bioethanol Production -- 5.3.6 Distribution of Products From Processing Plants to Markets -- 5.3.7 Product Demands -- 5.3.8 Cost of the Distributed Bioethanol Processing Plants -- 5.3.9 Transportation Cost for Stalks to Distributed and Central Plants -- 5.3.10 Transportation Cost From the Tequila Industries to Distributed and Central Bioethanol Processing Plants -- 5.3.11 Transportation Cost for Products -- 5.3.12 Objective Function -- 5.4 Case Study -- 5.4.1 Scenario A (Economic Solution With a Constraint of 1% for the Bioethanol Demand in Each Consumption Site) -- 5.4.2 Scenario B (Solution Without Constraint for the Demand of Bioethanol in the Markets) -- 5.4.3 Scenario C (Increasing the Cultivation Area) -- 5.5 Concluding Remarks -- 5.6 Nomenclature -- 5.6.1 Indexes -- 5.6.2 Sets -- 5.6.3 Parameters -- 5.6.4 Variables -- References -- 6 Financial Risk Assessment and Optimal Planning of Biofuels Supply Chains Under Uncertainty -- 6.1 Introduction -- 6.2 Problem Statement. , 6.3 Mathematical Model Formulation -- 6.4 Objective 1: Expected Profit -- 6.5 Objective 2: Worst Case for the Net Annual Profit -- 6.6 Results and Discussion -- 6.6.1 Distribution of Raw Material Price Without Correlation -- 6.6.2 Case With Correlated Values -- 6.7 Concluding Remarks -- 6.8 Nomenclature -- 6.8.1 Variables -- 6.8.2 Binary Variables -- 6.8.3 Parameters -- 7 Stochastic Design of Biorefinery Supply Chains Considering Economic and Environmental Objectives -- 7.1 Introduction -- 7.2 Problem Statement -- 7.3 Mathematical Formulation -- 7.3.1 Availability of Raw Material -- 7.3.2 Mass Balances in the Suppliers -- 7.3.3 Mass Balances in the Processing Facilities -- 7.3.4 Mass Balances in the Markets -- 7.3.5 Demand Constraint -- 7.3.6 Relationships for the Input-Output of the Distributed Material -- 7.3.7 Transportation Limits and Transportation Costs -- 7.3.8 Processing Stages in the Processing Facilities -- 7.3.9 Processing Constraints for the First Stage -- 7.3.10 Processing Constraints for the Second Stage -- 7.3.11 Storage Modeling -- 7.3.12 Revenue From Selling Products -- 7.3.13 Raw Material Production Cost -- 7.3.14 Economic Objective Function -- 7.3.15 Environmental Objective -- 7.4 Solution Approach -- 7.4.1 Definition of the Superstructure -- 7.4.2 Identification of the Parameters Under Uncertainty -- 7.4.3 Sampling for Uncertain Parameters -- 7.4.4 Solving of the Associated Deterministic Optimization Problem -- 7.4.5 Comparison Between Different Supply Chain Topologies -- 7.4.6 Changing of the Upper Limit for the Environmental Impact -- 7.4.7 Standardized Regression Coefficients -- 7.5 Case Study -- 7.6 Computer-Aided Tools -- 7.7 Results and Discussion -- 7.8 Concluding Remarks -- 7.9 Nomenclature -- 7.9.1 Indexes -- 7.9.2 Variables -- 7.9.3 Parameters -- References. , 8 Mixed-Integer Dynamic Optimization for Planning Distributed Biorefineries -- 8.1 Introduction -- 8.2 Problem Statement -- 8.3 Mixed-Integer Dynamic Mathematical Optimization Model -- 8.3.1 Raw Material Inventory at Suppliers -- 8.3.2 Raw Material Inventory at Processing Facilities -- 8.3.3 Raw Material Inventory at Main Processing Facility -- 8.3.4 Product Inventory at Processing Facilities -- 8.3.5 Product Inventory at Main Processing Facility -- 8.3.6 Product Inventory at Distribution Centers -- 8.3.7 Continuity of the Inventories at the Beginning and End of the Time Horizon -- 8.3.8 Raw Material Orders From General Facilities to Suppliers -- 8.3.9 Raw Material Orders From the Main Facility to Suppliers -- 8.3.10 Product Orders From the Distribution Centers to the Facilities -- 8.3.11 Product Orders From the Distribution Centers to the Main Facility -- 8.3.12 Product Orders From Consumers to the Distribution Centers -- 8.3.13 Continuity of the Inventories at the Beginning and End of the Horizon -- 8.3.14 Availability of Raw Material -- 8.3.15 Constraints for the Demand -- 8.3.16 Constraints to Control the Orders From Consumers to Distribution Centers -- 8.3.17 Constraints for Transported Flow Rate at the Outlet and Inlet Locations -- 8.3.18 Transportation Limits -- 8.3.19 Processing -- 8.3.20 Economies of Scale for Processing Facilities -- 8.3.21 Storage Modeling -- 8.3.22 Operating Cost -- 8.3.23 Total Capital Cost -- 8.3.24 Transportation Cost -- 8.3.25 Storage Cost -- 8.3.26 Net Annual Profit -- 8.3.27 Control Product Demand -- 8.4 Nonlinear Model Predictive Control Approach -- 8.5 Solution Approach for the MIDO Problem -- 8.6 Results -- 8.7 Conclusions -- 8.8 Nomenclature -- 8.8.1 Parameters -- 8.8.2 Binary Variables -- 8.8.3 Variables -- References -- Appendices: Code Used in the Book. , Appendix A GAMS Code for Model of Chapter 2, Environmental Aspects in the Strategic Planning of a Biomass Conversion System.

Language: English

UID:

ISBN: 0-443-13572-X , 0-443-13571-1

Series Statement: Developments in environmental modelling ; volume 32

Language: English

UID:

Format: 1 online resource (XVII, 110 p. 92 illus., 85 illus. in color.)

Edition: 1st ed. 2019.

ISBN: 3-319-91722-6

Content: This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.

Note: Chapter 1- Introduction -- Chapter 2- Process simulators -- Chapter 3- Metaheuristic optimization programs -- Chapter 4- interlinking between process simulators and optimization programs -- Chapter 5- Performance evaluation -- Chapter 6- Optimization of industrial process 1 -- Chapter 7- Optimization of industrial process 2 -- Chapter 8- Bibliography -- Appendix.

Additional Edition: ISBN 3-319-91721-8

Language: English

DOI: 10.1007/978-3-319-91722-1