Digital industrial furnaces: Challenges for energy efficiency under VULKANO project

Abstract

Under intensive industry, industrial furnaces must cope with new challenges to improve the efficiency, reliability and flexibility of their processes. As they need a great amount of energy to achieve the temperature required for heating and melting processes, many researchers have been focused on the minimization of the energy consumption. This energy optimization implies improvements, not only in the competitiveness, but also in environmental and cost performances of the process. This paper shows briefly the challenges for industrial furnaces under VULKANO project focused on the development of five approaches from the point of view of efficiency, flexibility, reliability and safety: improving refractories, investigating new recovery systems based on PCM, using alternative fuels, integrating advanced monitoring and control devices and, finally, developing a holistic tool to help the operator to make decisions. Besides, this paper describes the creation of a digital industrial furnace, regarding to digital twin term. Therefore, an analytical model comprising the burners system, the isolation structure, an energy recovery system, and the load to be heated is described. Each individual model provides the base for the development of future hybrid models, accurately parametrized through process variables, used to investigate the efficiency optimization and provide precise maintenance operation strategies.

Keywords

• Industrial furnaces,Energy efficiency,Control and monitoring system,Digital twin

References

1. Lo, K. A critical review of China’s rapidly developing renewable energy and energy efficiency policies. Renewable and Sustainable Energy Reviews 2014; 29: 508-516, doi:https://doi.org/10.1016 /j.rser.2013.09.006
2. Chowdhury, J , Hu, Y , Haltas, I , Balta-Ozkan, N , Jr.Matthew, G , Varga, L. Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors. Renewable and Sustainable Energy Reviews 2018; 94: 1153-1178, doi: https://doi.org/ 10.1016/j.rser.2018.06.040
3. Gökgöz, F , Güvercin, M. T. Energy security and renewable energy efficiency in EU. Renewable and Sustainable Energy Reviews 2018; 96: 226-239, doi:https://doi.org/10.1016/j.rser.2018.07.046
4. Sutainable Innovation Forum 2017 Available online: http://www.cop-23.org/ (accessed on Aug 30, 2018)
5. European Union 1995-2018 The Paris agreement: the world unites to fight climate change Available online: https://ec.europa.eu/clima/policies/international/negotiations/paris_en (accessed on Aug 30, 2018)
6. EC (European Commission). Directive 2009/29/EC of the European Parliament and of the Council of 23 April 2009 amending Directive 2003/87/EC so as to improve and extend the greenhouse gas emission allowance trading scheme of the Community Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/? qid=1535624849460&uri=CELEX:32009L0029 (accessed on Aug 3, 2018)
7. EC (European Commission). Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and ammending and subsequently repealing Directives 2001/77/EC and 2003/30/EC Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1535624410027&uri=CELEX:32009L0028 (accessed on Aug 3, 2018)
8. Chu, S , Cui, Y , Liu, N. The path towards sustainable energy. Nature Materials 2016; 16: 16-22, doi: http://dx.doi.org/10.1038/nmat4834

9. Yu, S , Zheng, S , Li, X. The achievement of the carbon emissions peak in China: The role of energy consumption structure optimization. Energy Economics 2018; 74: 693-707, doi: https://doi.org/10.1016/j.eneco.2018.07.017
10. Sun, J , Li, G , Wang, Z. Optimizing China’s energy consumption structure under energy and carbon constraints. Structural Change and Economic Dynamics 2018; doi: https://doi.org/10.1016/ j.strueco.2018.07.007
11. Deng, Z , Zhang, H , Fu, Y , Wan, L , Liu, W. Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption. Journal of Cleaner Production 2017; 166: 1407-1414, doi:https://doi.org/10.1016/j.jclepro.2017.08.022
12. Lucchetta, G , Masato, D , Sorgato, M. Optimization of mold thermal control for minimum energy consumption in injection molding of polypropylene parts. Journal of Cleaner Production 2018; 182: 217-226, doi:https://doi.org/10.1016/j.jclepro.2018.01.258
13. Ma, F , Zhang, H , Hong, K. K. B , Gong, G. An optimization approach of selective laser sintering considering energy consumption and material cost. Journal of Cleaner Production 2018; 199: 529-537, doi:https://doi.org/10.1016/j.jclepro.2018.07.185
14. Zhang, Z , Yu, H , Zhang, Y , Yang, K , Li, W , Chen, Z , Zhang, G. Analysis and optimization of process energy consumption and environmental impact in electrical discharge machining of titanium superalloys. Journal of Cleaner Production 2018; 198: 833-846, doi:https://doi.org/10.1016/j.jclepro.2018.07.053
15. Akan, A. E , Akan, A. P. Potential of reduction in carbon dioxide equivalent emissions via energy efficiency for a textile factory. Journal of Energy Systems 2018; 2: 57-69,
16. Mullinger P, Jenkins B. The Combustion Process. In: Mullinger P, Jenkins B, editors. Industrial and Process Furnaces. Oxford, United Kingdom: Butterworth-Heinemann, 2013. pp. 31-65.
17. Jia, T , Huang, J , Li, R , He, P , Dai, Y. Status and prospect of solar heat for industrial processes in China. Renewable and Sustainable Energy Reviews 2018; 90: 475-489, doi:https://doi.org/10.1016/ j.rser.2018.03.077
18. Lieuwen T, Yang V, Yetter R. Synthesis gas combustion : Fundamentals and Applications. Boca Raton, UNITED STATES: CRC Press, 2009.
19. Liu, H , Saffaripour, M , Mellin, P , Grip, C.E , Yang, W , Blasiak, W. A thermodynamic study of hot syngas impurities in steel reheating furnaces - Corrosion and interaction with oxide scales. Energy 2014; 77: 352-362, doi:https://doi:10.1016/j.energy.2014.08.092
20. Keramiotis, C , Katoufa, M , Vourliotakis, G , Hatziapostolou, A , Founti, M.A. Experimental investigation of a radiant porous burner performance with simulated natural gas, biogas and synthesis gas fuel blends. Fuel 2015; 158: 835-842, doi:https://doi:10.1016/j.fuel.2015.06.041
21. Kim, J.S , Park, J , Bae, D.S , Vu, T.M , Ha, J.S , Kim, T.K. A study on methane-air premixed flames interacting with syngas-air premixed flames. International Journal of Hydrogen Energy 2010; 35: 1390-1400, doi:https:// doi:10.1016/j.ijhydene.2009.11.078
22. Lieuwen T, McDonell V, Peterson E, Santavicca D. Fuel Flexibility Influences on Premixed Combustor Blowout, Flashback, Autoignition and Instability. In: ASME Turbo Expo 2006: Power for Land, Sea, and Air. Volume 1: Combustion and Fuels, Education; 8-1 May 2006: ASME Proceedings, pp. 601-615
23. Riazi, R , Farshchi, M , Shimura, M , Tanahashi, M , Miyauchi, T. An Experimental Study on Combustion Dynamics and NOx Emission of a Swirl Stabilized Combustor with Secondary Fuel Injection. International Journal of Thermal Science and Technology 2010; 5: 266-281, doi:https://doi:10.1299/jtst.5.266
24. Lieuwen, T , McDonell, V , Santavicca D , Sattelmayer, T. Burner Development and Operability Issues Associated with Steady Flowing Syngas Fired Combustors. Combustion Science and Technology 2008; 180: 1169-1192, doi:https://doi:10.1080/00102200801963375
25. García-Armingol, T , Sobrino, Á , Luciano, E , Ballester, J. Impact of fuel staging on stability and pollutant emissions of premixed syngas flames. Fuel 2016; 185: 122-132, doi:https:// doi:10.1016/j.fuel.2016.07.086
26. Engineering ToolBox. Fuels - Higher and Lower Calorific Values Available online: https://www. engineeringtoolbox.com/fuels-higher-calorific-values-d_169.html (accessed on Aug 31, 2018)
27. Ballester, J , García-Armingol, T. Diagnostic techniques for the monitoring and control of practical flames. Progress in Energy and Combustion Science 2010; 36: 375-411, doi:https://doi:10.1016/j.pecs.2009.11.005
28. Nouri-Khezrabad, M , Braulio, M.A.L , Pandolfelli, V.C , Golestani-Fard, F , Rezaie, H.R. Nano-bonded refractory castables. Ceramics International 2013 ; 39 : 3479-3497, doi:https://doi:10.1016/ j.ceramint.2012.11.028
29. Nouri-Khezrabad, M , Luz, A.P , Salvini, V.R , Golestani-Fard, F , Rezaie, H.R , Pandolfelli, V.C. Developing nano-bonded refractory castables with enhanced green mechanical properties. Ceramics International 2015; 41: 3051-3057, doi:https://doi:10.1016/j.ceramint.2014.10.143
30. Nardin, G , Meneghetti, A , Dal Magro, F , Benedetti, N. PCM-based energy recovery from electric arc furnaces. Applied Energy 2014; 136: 947-955, doi:https://doi:10.1016/j.apenergy.2014.07.052
31. Olevano D, Micelli P, Martini U, Di Donato A, Martelli S. Degradation of SiC based refractories in CFB plants under co-combustion conditions. In: ECreS 15th Conference & Exhibition of the European Ceramic Society; 9-13 July 2017, doi:https://doi:10.13140/RG.2.2.30882.32965
32. Haag, S , Anderl, R. Digital twin – Proof of concept. Manufacturing Letters 2018; 15: 64-66, doi:https:// doi.org/10.1016/j.mfglet.2018.02.006
33. Uhlemann, T.H.J , Schock, C , Lehmann, C , Freiberger, S , Steinhilper, R. The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems. Procedia Manufacturing 2017 ; 9 : 113-120, doi:https:// doi:10.1016/j.promfg.2017.04.043
34. Tello P, Weerdmeester R. Suitable Process Industry through Resource and Energy Efficiency. SPIRE Roadmap, European Commission, 2003.
35. Zou, S , Xie, X. Simplified model for coefficient of performance calculation of surface water source heat pump. Applied Thermal Engineering 2017; 112: 201-207, doi:https://doi.org/10.1016/ j.applthermaleng.2016.10.081
36. Chen, X.Y , Vinh-Thang, H , Ramirez, A.A , Rodrigue, D , Kaliaguine, S. Membrane gas separation technologies for biogas upgrading. RSC Advances 2015; 5: 24399-24448, doi:https:// doi:10.1039/C5RA00666J
37. Royo, P , Ferreira, V.J , López-Sabirón, A.M , García-Armingol, T , Ferreira, G. Retrofitting strategies for improving the energy and environmental efficiency in industrial furnaces: A case study in the aluminium sector. Renewable and Sustainable Energy Reviews 2018; 82: 1813-1822, doi:https:// doi:10.1016/j.rser.2017.06.11
38. Jardine, A.K.S , Lin, D , Banjevic, D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing 2006; 20: 1483-1510, doi:https:// doi:10.1016/j.ymssp.2005.09.012
39. Tchakoua, P , Wamkeue, R , Ouhrouche, M , Slaoui-Hasnaoui, F , Tameghe, T , Ekemb, G. Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges. Energies 2014; 7: 2595-2630, doi:https://doi:10.3390/en7042595
40. González-González, A , Cortadi, A. J , Galar, D , Ciani, L. Condition monitoring of wind turbine pitch controller: A maintenance approach. Measurement 2018; 123: 80-93, doi:https:// doi.org/10.1016/ j.measurement.2018.01.047
41. Chan, D , Mo, J. Life Cycle Reliability and Maintenance Analyses of Wind Turbines. Energy Procedia 2017; 110: 328-333, doi:https://doi.org/10.1016/j.egypro.2017.03.148
42. Boschert S, Rosen R. Digital Twin---The Simulation Aspect. In: Hehenberger P, Bradley D, editors. Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and their Designers. Cham, Switzerland: Springer International Publishing, 2016. pp. 59-74.
43. Schleich, B , Anwer, N , Mathieu, L , Wartzack, S. Skin Model Shapes: A new paradigm shift for geometric variations modelling in mechanical engineering. Computer-Aided Design 2014; 50: 1-15, doi:https:// doi.org/10.1016/j.cad.2014.01.001
44. Negri, E , Fumagalli, L , Macchi, M. A Review of the Roles of Digital Twin in CPS-based Production Systems. Procedia Manufacturing 2017; 11: 939-948, doi:https://doi.org/10.1016/j.promfg.2017.07.198
45. Schleich, B , Anwer, N , Mathieu, L , Wartzack, S. Shaping the digital twin for design and production engineering. CIRP Annals 2017; 66: 141-144, doi:https://doi.org/10.1016/j.cirp.2017.04.040
46. Robertson, A.F , Gross, D. An Electrical-Analog Method for Transient Heat-Flow Analysis. Journal of Research of the National Bureau of Standards 1958; 61: 105-115
47. Denev, J.A , Dinkov, I , Bockhorn, H. Burner design for an industrial furnace for thermal post-combustion. Energy Procedia 2017; 120: 484-491, doi:https://doi.org/10.1016/j.egypro.2017.07.171
48. Yin, C , Yan, J. Oxy-fuel combustion of pulverized fuels: Combustion fundamentals and modeling. Applied Energy 2016 ; 162 : 742-762, doi:https://doi.org/10.1016/j.apenergy.2015.10.149
49. Mayr, B , Prieler, R , Demuth, M , Moderer, L , Hochenauer, C. CFD modelling and performance increase of a pusher type reheating furnace using oxy-fuel burners. Energy Procedia 2017; 120: 462-468, doi:https:// doi.org/10.1016/j.egypro.2017.07.222
50. Hu, Y , Tan, C.K , Broughton, J , Roach, P.A. Development of a first-principles hybrid model for large-scale reheating furnaces. Applied Energy 2016; 173: 555-566, doi:https://doi.org/10.1016/ j.apenergy.2016.04.011