HAL Id: tel-02951293
https://tel.archives-ouvertes.fr/tel-02951293
Submitted on 28 Sep 2020
HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
Performances on Iron and Steel plants through System Dynamics
Raphaël Norbert
To cite this version:
Raphaël Norbert. Evaluation of Industrial Symbiosis Scenario Performances on Iron and Steel plants through System Dynamics. Environmental Engineering. Université de Technologie de Troyes, 2018.
English. �NNT : 2018TROY0054�. �tel-02951293�
THESE
pour l’obtention du grade de
DOCTEUR de l’UNIVERSITE DE TECHNOLOGIE DE TROYES
Spécialité : SYSTEMES SOCIOTECHNIQUES
présentée et soutenue par
Raphaël NORBERT
le 20 décembre 2018
Evaluation of Industrial Symbiosis Scenario Performances on Iron and Steel Plants through System Dynamics
JURY
M. B. REMY PROFESSEUR DES UNIVERSITES Président Mme. C. AZZARO-PANTEL PROFESSEUR DES UNIVERSITES Rapporteur M. J. KIM PROFESSEUR ASSOCIE UTT Directeur de thèse
M. G. GRIFFAY DOCTEUR Examinateur
M. H.-S. PARK PROFESSOR Rapporteur
To my wife, Elsa, my mother, Isabelle, my father, Vincent, and my brother, Alexandre, thank you for everything.
All along this research work, I felt so privileged to work on industrial symbiosis within the challenging and very interesting framework of the iron and steel industry. I have been able to learn a lot from both an academic and an industrial research point of view; especially by dealing with the real word issues while leading research developments that relies on the interesting field of system dynamics. I also feel very lucky to have benefited from this research experience from a personal development perspective. For that purpose, I take here the opportunity to sincerely thank every persons who have broadly contributed to the success of this PhD thesis work.
I would like first to thank my academic advisor, Dr Junbeum Kim, for the unlimited and essential support he gave me throughout this research work. His total commitment as well as his significant scientific and technical expertise in the field of industrial ecology and industrial symbiosis (including all related methodologies and tools), combined with his valuable advices, were inspiring to me; and definitely helped me over the past three years performing these research developments. I feel so fortunate to have had the possibility to develop my ideas through our numerous insightful discussions. I also want to sincerely thank Dr Junbeum Kim for all what he continuously brought to me with regards to my personal development area.
I would like then to thank my industrial supervisor, Dr Gérard Griffay, for the infinite and crucial support he gave me as well as for giving me the possibility to carry out this PhD thesis work within the energy team of ArcelorMittal Global R&D during the last three years. He openly shared with me his significant scientific and technical expertise in the field of energy systems applied to the iron and steel industry. He also pushed me in developing my ideas thanks to his creative and innovative mind which was inspiring to me. I feel very lucky to have had the possibility to perform these research developments under his supervision and I want to sincerely thank Dr Gérard Griffay for everything he made me benefited from, including the personal development aspects.
both agrees to be the Rapporteurs of this PhD thesis work and who agrees to be part of the thesis examiners. I also want to thank Professor Benjamin Rémy who has accepted to be part of the thesis examiners.
I also take here the opportunity to thank Marianne Viart who extensively and greatly handled the role of my industrial supervisor during the first year of this research work. She initiated and participated to give the very first orientations of these research developments that have particularly launched the following major steps of the PhD thesis work. She was also at the initiative of a steering committee which she settled up in order to have regularly follow-up meetings to discuss the progress and orientations of the industrial outcomes of this research work. I sincerely thank Marianne Viart for her relevant advices and for sharing with me her valuable experience from both a scientific and a technical perspective as well as from a personal development side.
I would like then to thank Dr Valentine Weber-Zollinger as well as Dr José Barros Lorenzo for their help during the whole duration of this research work. Both of them brought me at a high level of understanding of the energy aspects and the physicochemical phenomena related to the entire iron and steel production system thanks to their significant expertise. I also sincerely thank them for the insightful discussions we had, within a professional context on one hand and from a personal perspective on the other hand. I also would like to thank Dr Sarah Salamé and Dr Akshay Bansal for their support and friendship as my teammates within the energy team of ArcelorMittal Global R&D. I sincerely thank them for our numerous scientific, technical and personal discussions. Both of them have contributed to the success of this PhD thesis as well as to my personal development. For that purpose, I want to thank Dr Vladislav Janecek who left the energy team of ArcelorMittal Global R&D during the first year of this research work and who has also contributed to the success of it.
I also take the opportunity to sincerely thank Dr Joël Leroy, Dr Gilles Franceschini as well as Dr Mauro Chiappini for their valuable help and participation to the steering committee follow-up meetings as a regular support of this PhD thesis work. I sincerely thank Dr Pascal Gardin for his valuable advices and for his availability all along these three years. I also
discussions we had from both a professional and a personal perspective. I finally sincerely thank all colleagues from every department in ArcelorMittal Global R&D and ArcelorMittal Group who have contributed to the success of these research developments.
I would like then to thank Professor Nadège Troussier for giving me the possibility to perform this PhD thesis work within the CREIDD research team she is head of within the University of Technology of Troyes. I sincerely thank her for all her valuable advices and punctual follow-ups all along this research work. I also would like to sincerely thank all colleagues from every department within the University of Technology of Troyes and within the CREIDD research team who have contributed to the success of these research developments.
I would like to further thank all the partners from each company involved within the European H2020 EPOS Project. I sincerely thank all of them for our numerous insightful discussions and for the research work we led together towards the facilitation of the implementation of more industrial symbiosis within large and complex industries.
I would like finally to sincerely thank every person who would have been forgotten within the previous lines and who would have contributed to the success of this research work.
Last but not least, I sincerely thank my family and all my friends for their essential support throughout this PhD thesis work. Thanks for their encouragement and for everything that contributed to the success of this research work.
Iron and steel industry is known as one of the most energy-intensive sectors which contribute to worldwide energy and resource consumptions as well as carbon dioxide emissions. Many efforts have been made to increase the efficiency of internal processes but the potential of improvement tends to be more and more limited. This research work is thus focused on industrial symbiosis as a mean to face these environmental stakes on a common industrial territory and for which iron and steel plants have a major role to play. A new methodology and a new tool aiming at evaluating over time economic and environmental impacts of industrial symbiosis scenarios on this kind of industrial sites have been therefore developed.
Based on the system dynamics concepts, they further yearn to enhance the deployment of industrial symbioses in the context of iron and steel industry by providing a systematic approach for assessing their performances.
The developed method is described after investigating its theoretical foundations. It is then applied to a typically integrated iron and steel plant. A dynamic model is thus built and validated over a two year simulation period enabling to run industrial symbiosis scenarios involving energy and material flows implied throughout iron and steel production activities.
An application case of a concrete industrial symbiosis in real operational conditions is finally proposed and simulated. It allows showing the significant added value of this research work in the support of decisions-making processes towards industrial symbiosis in the framework of iron and steel industry.
Keywords: industrial symbiosis - industrial ecology - system dynamics - iron and steel - steel - energy - resources
L’industrie sidérurgique est l’un des secteurs les plus énergivores contribuant à la consommation mondiale d’énergie et de ressources ainsi qu’aux émissions de dioxyde de carbone. Des efforts ont été réalisés pour augmenter l’efficacité des procédés en interne mais le potentiel d’amélioration est de plus en plus limité. Ce travail de recherche porte donc sur la symbiose industrielle comme solution pour faire face aux enjeux environnementaux sur un territoire industriel et pour laquelle les usines sidérurgiques ont un rôle majeur à jouer. Une nouvelle méthodologie et un nouvel outil évaluant dans le temps les impacts économiques et environnementaux de scénarios de symbiose industrielle sur ces sites ont été développés.
Basés sur la dynamique des systèmes, ils visent à favoriser l’emploi des symbioses industrielles dans ce contexte industriel en proposant une approche systématique pour évaluer leurs performances.
La méthode développée est décrite après l’étude de ses fondements théoriques. Elle est ensuite appliquée à une usine sidérurgique intégrée typique. Un modèle dynamique est ainsi construit et validé sur une période de simulation de deux ans afin de simuler tout scénario de symbiose industrielle impliquant des flux d'énergie et de matières relatifs aux activités sidérurgiques. Un cas concret d'application de symbiose industrielle dans des conditions opérationnelles réelles est enfin proposé et simulé. Il montre la valeur ajoutée de ce travail de recherche qui vient en support des processus de prise de décisions en matière de symbiose industrielle dans le contexte de l’industrie sidérurgique.
Mots-clés : symbiose industrielle - écologie industrielle - dynamique des systèmes - sidérurgie - acier - énergie - ressources
For confidentiality reasons, neither the name nor the location or any other information inherent to the typically integrated iron and steel plant on that is focused this research work is disclosed within this whole PhD thesis report. The gathered and provided data as well as the collected feedbacks for the developments presented and detailed herein are obviously not disclosed either with respect to the previous enounced statement. Whenever it is necessary, the related data and the related results are normalized if they could be used in order to identify this typically integrated iron and steel plant or any related information that would be specific to its operation or identity. It should be noted that the preservation of this confidentiality does not prevent this research work from keeping its scientific relevance and interest and it does not prevent the corresponding developments from aiming at advancing and contributing to the realm of science.
The research work described in the present PhD thesis report has been carried out under the supervision of the Research Centre for Environmental Studies and Sustainability (CREIDD) at the University of Technology of Troyes as well as ArcelorMittal Global Research and Development. It has received funding from the European Union’s Horizon 2020 research and innovation programme within the project entitled "Enhanced energy and resource Efficiency and Performance in process industry Operations via onsite and cross-sectorial Symbiosis - EPOS" under grant agreement No 679386. This research work has also received funding from the Conventions Industrielles de Formation par la REcherche (CIFRE) fully funded by the ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation in France which entrusted the implementation to the Association Nationale de la Recherche et de la Technologie (ANRT).
The sole responsibility of the issues treated within the present PhD thesis report completely lies with the author.
List of abbreviations List of figures
List of tables List of equations Nomenclature
... 1
Introduction ... 1
1.1 Global energy context ... 2
1.2 Energy efficiency in the Iron and Steel industry ... 3
1.3 Towards more Industrial Ecology and Industrial Symbiosis ... 4
1.4 Outlines of the research work ... 7
... 9
Theoretical Background ... 9
2.1 Evaluation of Industrial Symbiosis performances ... 10
2.1.1 Related concepts and definitions ... 10
2.1.2 Theoretical framework ... 12
2.1.3 Quantifying performances of Industrial Symbiosis ... 15
2.2 System Dynamics modelling ... 17
2.2.1 Related concepts and definitions ... 17
2.2.2 Overview of the modelling concepts ... 19
2.2.3 Comparison with other methods ... 22
... 29
Problem Statement ... 29
3.1 Global scope and research interests ... 30
3.2 Main research question and scientific relevance ... 33
3.3 Objectives of the research work ... 34
... 36
Methodological Framework ... 36
4.1 Methodology overview ... 37
4.2 Data and hypothesis description ... 39
... 43
5.1 Definition of the system structure ... 44
5.2 Causal Loop Diagram ... 46
5.3 Stock and Flow Diagram ... 47
5.3.1 Typical model for a given process ... 47
5.3.2 Focus on a given storage ... 55
5.3.3 Integration of physicochemical calculations ... 57
5.4 Physical module overview ... 70
5.4.1 Input and output data ... 70
5.4.2 Main assumptions ... 81
... 83
System Dynamics Model Validation ... 83
6.1 Validation of the system structure ... 84
6.1.1 Structure verification ... 84
6.1.2 Parameter verification ... 85
6.1.3 Dimensional consistency test ... 86
6.1.4 Boundary adequacy test ... 86
6.2 Validation of the system behaviour ... 87
6.2.1 Reproduction test ... 87
6.2.2 Family member test ... 92
6.2.3 Boundary adequacy test ... 92
6.3 Comparison with a static approach ... 93
... 101
Application Case Study ... 101
7.1 Valorisation of steel slags ... 102
7.2 Industrial Symbiosis evaluation ... 106
7.3 Comparison with a static approach ... 116
7.4 Conclusions ... 123
... 125
Conclusion ... 125
8.1 Short summary ... 126
8.2 Major features and findings ... 127
8.3 Recommendations for future work ... 131
... 133
Extended Abstract (in French)... 133
9.1 Introduction ... 134
9.2.2 Modélisation par la dynamique des systèmes ... 140
9.3 Enoncé du problème ... 144
9.3.1 Périmètre du travail de recherche ... 144
9.3.2 Question de recherche et objectifs ... 146
9.4 Cadre méthodologique ... 147
9.5 Description du modèle dynamique ... 150
9.5.1 Modélisation par la dynamique des systèmes ... 150
9.5.2 Module de calculs physiques ... 156
9.6 Validation du modèle dynamique ... 158
9.7 Etude de cas d’application ... 160
9.8 Conclusion ... 167 References
Appendices
Symbol Designation
IS Industrial Symbiosis
IEA International Energy Agency IE Industrial Ecology
CE Circular Economy
ADEME French Environment and Energy Management Agency ("Agence de l’Environnement et de la Maîtrise de l’Energie" in French)
ST System Thinking
IMSA Amsterdam Sustainability and Innovation WSA World Steel Association
LCA Life Cycle Assessment MFA Material Flow Analysis IOA Input and Output Analysis SFA Substance Flow Analysis GIS Geographic Information System EMF Ellen MacArthur Foundation
LE Linear Economy
CIRAIG International Reference Centre for the Life Cycle of Products, Processes and Services ("Centre International de Référence sur le Cycle de Vie des Produits, Procédés et Services" in French)
GDRC Global Development Research Center
NISP National Industrial Symbiosis Programme TBL Triple Bottom Line
ABM Agent-Based Modelling
SD System Dynamics
MIT Massachusetts Institute of Technology
CLD Causal Loop Diagram
SFD Stock and Flow Diagram
DS Dynamic Systems
DES Discrete-Event-Simulation OHF Open Hearth Furnace
BF Blast Furnace
BOF Basic Oxygen Furnace / Converter EAF Electric Arc Furnace
COG Coke Oven Gas
BFG Blast Furnace Gas
BOFG Basic Oxygen Furnace Gas
LHV Low Heating Value
PCI Pulverized Coal Injected
GHG Greenhouse Gas
HRM Hot Rolling Mill
CC Continuous Casting
DRI Direct Reduced Iron LCI Life Cycle Inventory
ANOVA Analysis of variance Std Standard deviation NSA Nippon Slag Association BAU Business as Usual
TS Time Series
ML Machine Learning
Figure 1.1. Worldwide CO2 emissions from fossil fuel combustion (1870 - 2014) [3] ... 2
Figure 1.2. Worldwide total final energy distribution by sector (2016) [1] ... 2
Figure 1.3. Worldwide blast furnace iron production (2003 - 2016) [7] ... 3
Figure 1.4. Worldwide crude steel production (2003 - 2016) [8] ... 3
Figure 1.5. CO2 emissions from crude steel production (2003 - 2016) [12] ... 4
Figure 1.6. Energy intensity of crude steel production (2003 - 2016) [12] ... 4
Figure 2.1. Three level operations of IE (IS operates at the inter-firm level) [28] ... 11
Figure 2.2. Kalundborg symbiosis and new biomass power plants circled (2012) [27] ... 12
Figure 2.3. Theoretical bases of IS-related research works [27] ... 13
Figure 2.4. System modelling of the real world [127] ... 18
Figure 2.5. SD top-down approach [128] ... 18
Figure 2.6. CLD of the adoption of a new product [140] ... 20
Figure 2.7. SFD of the adoption of a new product [136] ... 22
Figure 2.8. System modelling methods [122] ... 22
Figure 3.1. Overview of the different steel making routes (including BF-BOF) [155] ... 30
Figure 3.2. Overview of a typically integrated iron and steel plant [159] ... 31
Figure 4.1. Overview of the methodology of this research work ... 38
Figure 5.1. Iron and steel production steps implemented within the SD model ... 45
Figure 5.2. Developed generic CLD for a typical production step ... 46
Figure 5.3. Developed generic SD model for a typical production step ... 48
Figure 5.4. Link between developed generic SD models within the global SD model ... 54
Figure 5.5. Developed generic SD model for a typical stock ... 55
Figure 5.6. Integration of the physical module within the SD model ... 70
Figure 6.1. Coke production within the coking process ... 88
Figure 6.2. Sinter production within the sintering process ... 88
Figure 6.3. Hot metal production within the ironmaking process ... 88
Figure 6.4. Raw steel production within the converter unit ... 88
Figure 6.5. Liquid steel production within the ladle treatment unit ... 88
Figure 6.6. Steel coils production within the hot rolling process ... 88
Figure 6.8. Limestone consumption within the sintering process ... 89
Figure 6.9. Coal consumption within the coking process ... 89
Figure 6.10. Blast furnace gas production within the ironmaking process ... 89
Figure 6.11. Basic oxygen furnace gas production within the converter unit ... 89
Figure 6.12. Oxygen consumption within the converter unit ... 89
Figure 6.13. Description of the target diagram template ... 96
Figure 6.14. Target point, rings and axes of the target diagram (fictive example) ... 96
Figure 6.15. Focus on month 1 (fictive example) ... 96
Figure 6.16. Focus on month 2 (fictive example) ... 96
Figure 6.17. Full target diagram (fictive example) ... 96
Figure 6.18. Coke production within the coking process (target) ... 97
Figure 6.19. Sinter production within the sintering process (target) ... 97
Figure 6.20. Hot metal production within the ironmaking process (target) ... 97
Figure 6.21. Raw steel production within the converter unit (target) ... 97
Figure 6.22. Liquid steel production within the ladle treatment unit (target) ... 97
Figure 6.23. Steel coils production within the hot rolling process (target) ... 97
Figure 6.24. Iron ore consumption within the sintering process (target) ... 98
Figure 6.25. Limestone consumption within the sintering process (target) ... 98
Figure 6.26. Coal consumption within the coking process (target) ... 98
Figure 6.27. Blast furnace gas production within the ironmaking process (target) ... 98
Figure 6.28. Basic oxygen furnace gas production within the converter unit (target) ... 98
Figure 6.29. Oxygen consumption within the converter unit (target) ... 98
Figure 7.1. Main solid by-products from ironmaking and steelmaking processes [157] ... 103
Figure 7.2. Current configuration of the typically integrated iron and steel plant ... 106
Figure 7.3. Configuration of the typically integrated iron and steel plant in the IS scenario 107 Figure 7.4. Iron ore consumed within the sintering process ... 109
Figure 7.5. Limestone consumed within the sintering process ... 109
Figure 7.6. Anthracite consumed within the sintering process ... 109
Figure 7.7. Olivine consumed within the sintering process ... 109
Figure 7.8. Sinter’s basicity 1 produced within the sintering process ... 109
Figure 7.9. Sinter’s basicity 2 produced within the sintering process ... 109
Figure 7.11. Fumes production within the sintering process ... 110 Figure 7.12. CO2 content of the fumes produced within the sintering process ... 110 Figure 7.13. Blast furnace gas production within the ironmaking process ... 110 Figure 7.14. CO2 content of the BFG produced within the ironmaking process ... 110 Figure 7.15. LHV of the BFG produced within the ironmaking process ... 110 Figure 7.16. Blast furnace slag production within the ironmaking process ... 111 Figure 7.17. BF slag’s basicity 1 produced within the ironmaking process ... 111 Figure 7.18. BF slag’s basicity 2 produced within the ironmaking process ... 111 Figure 7.19. BF slag’s basicity 3 produced within the ironmaking process ... 111 Figure 7.20. Iron ore consumed within the ironmaking process ... 111 Figure 7.21. External coke consumed within the ironmaking process ... 111 Figure 7.22. Calcium carbide consumed within the hot metal treatment unit ... 112 Figure 7.23. Magnesium consumed within the hot metal treatment unit ... 112 Figure 7.24. Basic oxygen furnace slag production within the converter unit ... 112 Figure 7.25. Basic oxygen furnace gas production within the converter unit ... 112 Figure 7.26. LHV of the BOFG produced within the converter unit ... 112 Figure 7.27. Oxygen consumed within the converter unit ... 112 Figure 7.28. Basic oxygen furnace slag consumed within the sintering process ... 113 Figure 7.29. Basic oxygen furnace slag consumed within the ironmaking process ... 113 Figure 7.30. Total variable costs of the whole industrial site ... 113 Figure 7.31. Total direct CO2 emissions of the whole industrial site ... 113 Figure 7.32. Total indirect CO2 emissions of the whole industrial site ... 113 Figure 7.33. Basic oxygen furnace slag price ... 113 Figure 7.34. Iron ore consumed within the sintering process (target) ... 117 Figure 7.35. Limestone consumed within the sintering process (target) ... 117 Figure 7.36. Anthracite consumed within the sintering process (target) ... 118 Figure 7.37. Olivine consumed within the sintering process (target) ... 118 Figure 7.38. Sinter’s basicity 1 produced within the sintering process (target) ... 118 Figure 7.39. Sinter’s basicity 2 produced within the sintering process (target) ... 118 Figure 7.40. Sinter’s basicity 3 produced within the sintering process (target) ... 118 Figure 7.41. Fumes production within the sintering process (target) ... 118
Figure 7.43. Blast furnace gas production within the ironmaking process (target) ... 119 Figure 7.44. CO2 content of the BFG produced in the ironmaking process (target) ... 119 Figure 7.45. LHV of the BFG produced within the ironmaking process (target) ... 119 Figure 7.46. Blast furnace slag production within the ironmaking process (target) ... 119 Figure 7.47. BF slag’s basicity 1 produced within the ironmaking process (target) ... 119 Figure 7.48. BF slag’s basicity 2 produced within the ironmaking process (target) ... 120 Figure 7.49. BF slag’s basicity 3 produced within the ironmaking process (target) ... 120 Figure 7.50. Iron ore consumed within the ironmaking process (target) ... 120 Figure 7.51. External coke consumed within the ironmaking process (target) ... 120 Figure 7.52. Calcium carbide consumed within the hot metal treatment unit (target) ... 120 Figure 7.53. Magnesium consumed within the hot metal treatment unit (target) ... 120 Figure 7.54. Basic oxygen furnace slag production within the converter unit (target) ... 121 Figure 7.55. Basic oxygen furnace gas production within the converter unit (target) ... 121 Figure 7.56. LHV of the BOFG produced within the converter (target) ... 121 Figure 7.57. Total variable costs of the whole industrial site (target) ... 121 Figure 7.58. Total direct CO2 emissions of the whole industrial site (target) ... 121 Figure 7.59. Total indirect CO2 emissions of the whole industrial site (target) ... 121 Figure 9.1. CLD de l’adoption d’un nouveau produit [136] ... 142 Figure 9.2. SFD de l’adoption d’un nouveau produit [140] ... 142 Figure 9.3. Aperçu global d’une usine sidérurgique intégrée typique [159] ... 146 Figure 9.4. Aperçu global de la méthodologie de recherche ... 149 Figure 9.5. CLD générique développé pour une étape de production ... 151 Figure 9.6. Etapes de production implémentées dans le modèle dynamique ... 152 Figure 9.7. SFD générique développé pour une étape de production ... 155 Figure 9.8. Couplage du module de calculs physiques au modèle dynamique ... 156
Table 1.1. General outlines of this research work ... 7 Table 1.2. General outlines of this research work (continued) ... 8 Table 2.1. Core of the literature in the field of IS [27] ... 14 Table 2.2. Core of the literature in the field of IS (continued) [27] ... 15 Table 2.3. The SD method vs. the ABM method [122] ... 25 Table 2.4. The SD method vs. the DS method ... 27 Table 2.5. The SD method vs. the DES method [154] ... 28 Table 4.1. Dynamic data gathered and used within this research work ... 41 Table 5.1. Iron and steel production steps implemented within the SD model ... 44 Table 5.2. Iron and steel production steps implemented within the SD model (continued) .... 45 Table 5.3. Type of variables implemented in the developed generic SD model ... 49 Table 5.4. Type of variables implemented in the developed generic stock-based SD model .. 55 Table 5.5. Colour legend used within the SD model input and output data tables ... 59 Table 5.6. Input data related to the sintering process within the SD model ... 60 Table 5.7. Input data related to the coking process within the SD model ... 61 Table 5.8. Input data related to the PCI preparation unit within the SD model ... 62 Table 5.9. Input data related to the hot blast production unit within the SD model ... 63 Table 5.10. Input data related to the ironmaking process within the SD model ... 64 Table 5.11. Input data related to the hot metal treatment unit within the SD model ... 65 Table 5.12. Input data related to the basic oxygen furnace unit within the SD model ... 66 Table 5.13. Input data related to the ladle treatment unit within the SD model ... 67 Table 5.14. Input data related to the continuous casting unit within the SD model ... 68 Table 5.15. Input data related to the hot rolling process within the SD model ... 69 Table 5.16. Input data and output data related to the sintering process ... 71 Table 5.17. Input data and output data related to the coking process ... 72 Table 5.18. Input data and output data related to the PCI preparation unit ... 73 Table 5.19. Input data and output data related to the hot blast production unit ... 74 Table 5.20. Input data and output data related to the ironmaking process ... 75 Table 5.21. Input data and output data related to the hot metal treatment unit ... 76
Table 5.23. Input data and output data related to the ladle treatment unit ... 78 Table 5.24. Input data and output data related to the continuous casting unit ... 79 Table 5.25. Input data and output data related to the hot rolling process ... 80 Table 5.26. Assumptions of the physical module in the SD model [164] [166] ... 81 Table 5.27. Assumptions of the physical module in the SD model (continued) [164] [166] .. 82 Table 6.1. Main statistical analysis outcomes from the reproduction test ... 91 Table 6.2. Main analysis outcomes from the reproduction test (target diagrams) ... 99 Table 6.3. Main analysis outcomes from the reproduction test (target diagrams - continued) ... 100 Table 7.1. Typical composition of iron and steel slags [173] ... 104 Table 7.2. Primary characteristics and applications of iron and steel slags [174] ... 105 Table 7.3. Results of the dynamic simulation of the IS scenario ... 114 Table 7.4. Results of the dynamic simulation of the IS scenario (continued 1) ... 115 Table 7.5. Results of the dynamic simulation of the IS scenario (continued 2) ... 116 Table 7.6. Main analysis outcomes from the comparison (target diagrams) ... 122 Table 9.1. La méthode de la SD vs. la méthode de ABM [122] ... 143 Table 9.2. La méthode de la SD vs. la méthode de la DS ... 143 Table 9.3. La méthode de la SD vs. la méthode de la DS (suite) ... 144 Table 9.4. La méthode de la SD vs. la méthode de DES [154] ... 144 Table 9.5. Données dynamiques recueillies et utilisées dans ce travail de recherche ... 150 Table 9.6. Etapes de production sidérurgique implémentées dans le modèle dynamique ... 153 Table 9.7. Principaux résultats du test de reproduction ... 159 Table 9.8. Principaux résultats du test de reproduction (suite) ... 160 Table 9.9. Caractéristiques primaires et applications des laitiers de convertisseur [174] ... 161 Table 9.10. Résultats des simulations dynamiques du scenario de IS ... 163 Table 9.11. Résultats des simulations dynamiques du scenario de IS (suite 1) ... 164 Table 9.12. Résultats des simulations dynamiques du scenario de IS (suite 2) ... 165
Eq 5.1 ... 50 Eq 5.2 ... 50 Eq 5.3 ... 51 Eq 5.4 ... 51 Eq 5.5 ... 51 Eq 5.6 ... 51 Eq 5.7 ... 51 Eq 5.8 ... 52 Eq 5.9 ... 52 Eq 5.10 ... 52 Eq 5.11 ... 52 Eq 5.12 ... 52 Eq 5.13 ... 52 Eq 5.14 ... 52 Eq 5.15 ... 52 Eq 5.16 ... 53 Eq 5.17 ... 53 Eq 5.18 ... 53 Eq 5.19 ... 53 Eq 5.20 ... 53 Eq 5.21 ... 53 Eq 5.22 ... 53 Eq 5.23 ... 53 Eq 5.24 ... 53 Eq 5.25 ... 54 Eq 5.26 ... 54 Eq 5.27 ... 56 Eq 5.28 ... 56 Eq 5.29 ... 56
Eq 5.31 ... 56 Eq 5.32 ... 56 Eq 5.33 ... 56 Eq 5.34 ... 56 Eq 5.35 ... 57 Eq 5.36 ... 57 Eq 5.37 ... 57 Eq 5.38 ... 57 Eq 7.1 ... 108 Eq 7.2 ... 108 Eq 7.3 ... 108
Symbol Designation [unit]
CO2 Carbon dioxide [/]
𝑆𝑡𝑜𝑐𝑘𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of main product in process i [t]
𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Flow rate of main product produced in process i [t/month]
𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of main product produced in process i consumed in process i+1 [t/month]
𝑅𝐴𝑇𝐸 𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Constant rate of flow of main product produced in process i on flow of main product consumed in process i+1 [/]
𝑟𝑎𝑡𝑒 𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable rate of flow of main product produced in process i consumed in process i+1 on flow of main product produced in process i+1 [/]
𝑆𝑡𝑜𝑐𝑘𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of main product in process i at time t [t]
𝑆𝑡𝑜𝑐𝑘 𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of raw materials in process i [t]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Flow rate of raw materials purchased in process i [t/month]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of raw materials consumed in process i [t/month]
𝑆𝑡𝑜𝑐𝑘 𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of raw materials in process i at time t [t]
𝑅𝐴𝑇𝐸 𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Constant rate of flow of raw materials purchased in process i on flow of raw materials consumed in process i [/]
𝑟𝑎𝑡𝑒 𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠 in process i on flow of main product produced in process i [/]
𝑆𝑡𝑜𝑐𝑘 𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of by-products in process i [t; Nm3; GJ]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Flow rate of by-products produced in process i [t/month; Nm3/month; GJ/month]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of by-products consumed in process i [t/month; Nm3/month; GJ/month]
𝑆𝑡𝑜𝑐𝑘 𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of by-products in process i at time t [t;
Nm3; GJ]
𝑟𝑎𝑡𝑒 𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Variable rate of flow of by-products produced in process i on flow of by-products consumed in process i [/]
𝑟𝑎𝑡𝑒 𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable rate of flow of by-products consumed in process i on flow of main product produced in process i [/]
𝑆𝑡𝑜𝑐𝑘 𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of intermediate products in process i [t]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Flow rate of intermediate products produced in process i [t/month]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of intermediate products consumed in process i [t/month]
𝑆𝑡𝑜𝑐𝑘 𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of intermediate products in process i at time t [t]
𝑟𝑎𝑡𝑒 𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Variable rate of flow of intermediate products produced in process i on flow of intermediate products consumed in process i [/]
𝑟𝑎𝑡𝑒 𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠 Variable rate of flow of intermediate products
produced in process i [/]
𝑆𝑡𝑜𝑐𝑘 𝐺𝑎𝑠𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of gases in process i [Nm3; GJ]
𝑔𝑎𝑠𝑒𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Flow rate of gases purchased in process i [Nm3/month; GJ/month]
𝑔𝑎𝑠𝑒𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of gases consumed in process i [Nm3/month; GJ/month]
𝑆𝑡𝑜𝑐𝑘 𝐺𝑎𝑠𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of gases in process i at time t [Nm3; GJ]
𝑅𝐴𝑇𝐸 𝑔𝑎𝑠𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Constant rate of flow of gases purchased in process i on flow of gases consumed in process i [/]
𝑟𝑎𝑡𝑒 𝑔𝑎𝑠𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable rate of flow of gases consumed in process i on flow of main product produced in process i [/]
𝑆𝑡𝑜𝑐𝑘 𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Stock of utilities in process i [t; Nm3; GJ; MWh]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Flow rate of utilities purchased in process i [t/month; Nm3/month; GJ/month; MWh/month]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Flow rate of utilities consumed in process i [t/month; Nm3/month; GJ/month; MWh/month]
𝑆𝑡𝑜𝑐𝑘 𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Stock of utilities in process i at time t [t; Nm3; GJ; MWh]
𝑅𝐴𝑇𝐸 𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑢𝑟𝑐ℎ
Constant rate of flow of utilities purchased in process i on flow of gases consumed in process i [/]
𝑟𝑎𝑡𝑒 𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable rate of flow of utilities consumed in process i on flow of main product produced in process i [/]
𝑆𝑡𝑜𝑐𝑘 𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 Stock of raw materials in the whole plant [t]
whole plant [t/month]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙̇ 𝑐𝑜𝑛𝑠 Flow rate of raw materials consumed in the whole plant [t/month]
𝑆𝑡𝑜𝑐𝑘 𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 Stock of by-products in the whole plant [t; Nm3; GJ]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑝𝑟𝑜𝑑 Flow rate of by-products produced in the whole plant [t/month; Nm3/month; GJ/month]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑐𝑜𝑛𝑠 Flow rate of by-products consumed in the whole plant [t/month; Nm3/month; GJ/month]
𝑆𝑡𝑜𝑐𝑘 𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 Stock of intermediate products in the whole plant [t]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑝𝑟𝑜𝑑 Flow rate of intermediate produced in the whole plant [t/month]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠̇ 𝑐𝑜𝑛𝑠 Flow rate of intermediate consumed in the whole plant [t/month]
CO Carbon monoxide [/]
H2 Hydrogen [/]
CH4 Methane [/]
C2H6 Ethane [/]
C3H8 Propane [/]
C4H10 Butane [/]
FeO Iron oxide II [/]
Fe Iron [/]
Fe2O3 Iron oxide III [/]
NH3 Ammonia [/]
H2S Hydrogen sulphide [/]
Si Silicon [/]
Mn Manganese [/]
P Phosphorous [/]
Ti Titanium [/]
Cr Chromium [/]
SO2 Sulphur dioxide [/]
CaS Calcium sulphide [/]
𝑀𝑎𝑖𝑛 𝑃𝑟𝑜𝑑𝑢𝑐𝑡 𝑇𝑜𝑡𝑎𝑙 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total variable costs of main product in process i [€]
𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Variable costs of main product produced in process i [€/month]
𝑀𝑎𝑖𝑛 𝑃𝑟𝑜𝑑𝑢𝑐𝑡 𝑇𝑜𝑡𝑎𝑙 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total variable costs of main product in process i at time t [€]
𝑟𝑎𝑡𝑒 𝑚𝑎𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑣𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝑐𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑝𝑟𝑜𝑑
Variable costs of main product produced in process I [€/t] (e.g. other costs related to the good operation of process i and attached to main product)
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total costs of raw materials in process i [€]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable costs of raw materials consumed in process i [€/month]
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total costs of raw materials in process i at time t [€]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑝𝑟𝑖𝑐𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠 Variable prices of raw materials consumed in
𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total costs of by-products in process i [€]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable costs of by-products consumed in process i [€/month]
𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total costs of by-products in process i at time t [€]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑝𝑟𝑖𝑐𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable prices of by-products consumed in process i [€/t; €/Nm3; €/GJ]
𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total costs of intermediate products in process i [€]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable costs of intermediate products consumed in process i [€/month]
𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total costs of intermediate products in process i at time t [€]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑝𝑟𝑖𝑐𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable prices of intermediate products consumed in process i [€/t]
𝐺𝑎𝑠𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total costs of gases in process i [€]
𝑔𝑎𝑠𝑒𝑠 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable costs of gases consumed in process i [€/month]
𝐺𝑎𝑠𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total costs of gases in process i at time t [€]
𝑔𝑎𝑠𝑒𝑠 𝑝𝑟𝑖𝑐𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable prices of gases consumed in process i [€/Nm3; €/GJ]
𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total costs of utilities in process i [€]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑐𝑜𝑠𝑡𝑠̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable costs of utilities consumed in process i [€/month]
𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total costs of utilities in process i at time t [€]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑝𝑟𝑖𝑐𝑒𝑠𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠 Variable prices of utilities consumed in process i
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total direct CO2 emissions due to raw materials consumed in process i [tCO2]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝐷 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable direct CO2 emissions due to raw materials consumed in process i [tCO2/month]
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total direct CO2 emissions due to raw materials consumed in process i at time t [tCO2]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Carbon content of raw materials consumed in process i [tCO2/t]
𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total direct CO2 emissions due to by-products consumed in process i [tCO2]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝐷 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable direct CO2 emissions due to by- products consumed in process i [tCO2/month]
𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total direct CO2 emissions due to by-products consumed in process i at time t [tCO2]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Carbon content of by-products consumed in process i [tCO2/t; tCO2/Nm3; tCO2/GJ]
𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total direct CO2 emissions due to intermediate products consumed in process i [tCO2]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝐷 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable direct CO2 emissions due to intermediate products consumed in process i [tCO2/month]
𝐼𝑛𝑡𝑒𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total direct CO2 emissions due to intermediate products consumed in process i at time t [tCO2]
𝑖𝑛𝑡𝑒𝑟𝑚 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Carbon content of intermediate products consumed in process i [tCO2/t]
𝐺𝑎𝑠𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total direct CO2 emissions due to gases consumed in process i [tCO2]
consumed in process i [tCO2/month]
𝐺𝑎𝑠𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total direct CO2 emissions due to gases consumed in process i at time t [tCO2]
𝑔𝑎𝑠𝑒𝑠 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Carbon content of gases consumed in process i [tCO2/Nm3; tCO2/GJ]
𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total direct CO2 emissions due to utilities consumed in process i [tCO2]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐷 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable direct CO2 emissions due to utilities consumed in process i [tCO2/month]
𝑈𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑇𝑜𝑡𝑎𝑙 𝐷 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total direct CO2 emissions due to utilities consumed in process i at time t [tCO2]
𝑢𝑡𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝐶 𝑐𝑜𝑛𝑡𝑒𝑛𝑡𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Carbon content of utilities consumed in process i [tCO2/t; tCO2/Nm3; tCO2/GJ; tCO2/MWh]
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝑈 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖
Total indirect CO2 emissions due to raw materials consumed in process i [tCO2]
𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑈 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable indirect CO2 emissions due to raw materials consumed in process i [tCO2/month]
𝑅𝑎𝑤 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑇𝑜𝑡𝑎𝑙 𝑈 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖𝑡 Total indirect CO2 emissions due to raw materials consumed in process i at time t [tCO2]
𝑟𝑎𝑡𝑒 𝑟𝑎𝑤 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑠 𝑈 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Upstream CO2 content of raw materials consumed in process i [tCO2/t]
𝐵𝑦𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑇𝑜𝑡𝑎𝑙 𝑈 𝐶𝑂2𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 Total indirect CO2 emissions due to by-products consumed in process i [tCO2]
𝑏𝑦𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 𝑈 𝐶𝑂2̇ 𝑃𝑟𝑜𝑐𝑒𝑠𝑠 𝑖 𝑐𝑜𝑛𝑠
Variable indirect CO2 emissions due to by- products consumed in process i [tCO2/month]
