Journal of Business Economics

, Volume 87, Issue 1, pp 41–72 | Cite as

Prerequisites of efficient decentralized waste heat recovery and energy storage in production planning

  • Konstantin BielEmail author
  • Christoph H. Glock
Original Paper


Following the scarcity of resources, rising energy prices, and an increasing awareness of the role manufacturing plays in the generation of greenhouse gas emissions, the usage of energy has more and more been considered in research on production planning and scheduling in recent years. Time-varying energy prices, which have been introduced to penalize energy usage during peak-demand periods and which are supposed to smooth energy demand, have added a new aspect to this stream of research. This article studies how the integration of a waste heat recovery system, which can convert industrial waste heat into electrical energy, along with an electrical energy storage system can balance the positive and negative effects of energy peak prices on the production plan in a serial multi-stage production system. After developing an appropriate model, we investigate how the use of the waste heat recovery system and the electrical energy storage system impact production planning. In a numerical analysis, we investigate under which conditions the recovery of waste heat combined with the opportunity to store energy provides practitioners with an efficient tool to lower total energy usage and to better react to time-varying energy prices, and thus to reduce total energy cost.


Energy efficiency Sustainable manufacturing system Energy usage Production planning Waste heat recovery Electrical energy storage system 

JEL Classification

M110 L6 



The authors are grateful to the anonymous referees, whose valuable comments on an earlier version of this paper helped to improve this work significantly. The authors further wish to acknowledge the support of the Carlo and Karin Giersch-Stiftung in funding their research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Ashok S (2006) Peak-load management in steel plants. Appl Energy 83:413–424. doi: 10.1016/j.apenergy.2005.05.002 CrossRefGoogle Scholar
  2. Ashok S, Banerjee R (2001) An optimization mode for industrial load management. IEEE Trans Power Syst 16:879–884. doi: 10.1109/59.962440 CrossRefGoogle Scholar
  3. Balogun VA, Kirkwood ND, Mativenga PT (2014) Direct electrical energy demand in fused deposition modelling. Procedia CIRP 15:38–43CrossRefGoogle Scholar
  4. Bazan E, Jaber MY, Zanoni S (2015) Supply chain models with greenhouse gases emissions, energy usage and different coordination decisions. Appl Math Model 39:5131–5151. doi: 10.1016/j.apm.2015.03.044 CrossRefGoogle Scholar
  5. Bego A, Li L, Sun Z (2014) Identification of reservation capacity in critical peak pricing electricity demand response program for sustainable manufacturing systems. Int J Energy Res 38:728–736. doi: 10.1002/er.3077 CrossRefGoogle Scholar
  6. Biel K, Glock CH (2014) On the use of waste heat in a two-stage production system with controllable production rates. In: 18th International Symposium on Inventories, Budapest, 2014Google Scholar
  7. Bruzzone AAG, Anghinolfi D, Paolucci M, Tonelli F (2012) Energy-aware scheduling for improving manufacturing process sustainability: a mathematical model for flexible flow shops. CIRP Ann Manuf Technol 61:459–462. doi: 10.1016/j.cirp.2012.03.084 CrossRefGoogle Scholar
  8. Castro PM, Harjunkoski I, Grossmann IE (2009) New continuous-time scheduling formulation for continuous plants under variable electricity cost. Ind Eng Chem Res 48:6701–6714CrossRefGoogle Scholar
  9. Chao X, Chen FY (2005) An optimal production and shutdown strategy when a supplier offers an incentive program. Manuf Serv Oper Manag 7:130–143Google Scholar
  10. Chen H, Cong TN, Yang W, Tan C, Li Y, Ding Y (2009) Progress in electrical energy storage system: a critical review. Prog Nat Sci 19:291–312. doi: 10.1016/j.pnsc.2008.07.014 CrossRefGoogle Scholar
  11. Chen H, Goswami DY, Stefanakos EK (2010) A review of thermodynamic cycles and working fluids for the conversion of low-grade heat. Renew Sustain Energy Rev 14:3059–3067CrossRefGoogle Scholar
  12. Dai Y, Wang J, Gao L (2009) Parametric optimization and comparative study of organic Rankine cycle (ORC) for low grade waste heat recovery. Energy Convers Manag 50:576–582CrossRefGoogle Scholar
  13. Denton FT, Jefferies KL, Mountain DC, Robb AL, Spencer BG (1987) The response of an industrial firm to alternative electricity rate structures: an optimization model for simulation applications. Resour Energy 9:327–346. doi: 10.1016/0165-0572(87)90002-8 CrossRefGoogle Scholar
  14. European Parliament and Council (2012) Energy efficiency directive (2012/27/EU). Off J Eur Union.
  15. Fang H, Xia J, Zhu K, Su Y, Jiang Y (2013) Industrial waste heat utilization for low temperature district heating. Energy Policy 62:236–246. doi: 10.1016/j.enpol.2013.06.104 CrossRefGoogle Scholar
  16. Fernandez M, Li L, Sun Z (2013) “Just-for-Peak” buffer inventory for peak electricity demand reduction of manufacturing systems. Int J Prod Econ 146:178–184CrossRefGoogle Scholar
  17. Fraunhofer Institut für Umwelt-, Sicherheits und Energietechnik UMSICHT (2013) Abschlussbericht Entwicklungs-/Demonstrationsprojekt mit Feldversuch “ORC-Prozesse zur Abwärmenutzung an BHKW-Motoren” Feldversuch ORC FKZ-Nr. 0327436CGoogle Scholar
  18. Gahm C, Denz F, Dirr M, Tuma A (2016) Energy-efficient scheduling in manufacturing companies: a review and research framework. Eur J Oper Res 248:744–757. doi: 10.1016/j.ejor.2015.07.017 CrossRefGoogle Scholar
  19. Ghobeity A, Mitsos A (2010) Optimal time-dependent operation of seawater reverse osmosis. Desalination 263:76–88CrossRefGoogle Scholar
  20. Gutowski T, Dahmus J, Thiriez (2006) Electrical energy requirements for manufacturing processes. In: 13th CIRP International Conference on Life Cycle Engineering, 2006Google Scholar
  21. Haddad C, Périlhon C, Danlos A, François M-X, Descombes G (2014) Some efficient solutions to recover low and medium waste heat: competitiveness of the thermoacoustic technology. Energy Procedia 50:1056–1069. doi: 10.1016/j.egypro.2014.06.125 CrossRefGoogle Scholar
  22. Hasanbeigi A, Price L (2012) A review of energy use and energy efficiency technologies for the textile industry. Renew Sustain Energy Rev 16:3648–3665. doi: 10.1016/j.rser.2012.03.029 CrossRefGoogle Scholar
  23. He Y, Liu F, Cao H-J, Li C-B (2005) A bi-objective model for job-shop scheduling problem to minimize both energy consumption and makespan. J Cent South Univ Technol 12:167–171CrossRefGoogle Scholar
  24. Hirzel S, Sontag B, Rhode C (2013) Industrielle Abwärmenutzung. Fraunhofer Institut für System- und Innovationsforschung ISI, KarlsruheGoogle Scholar
  25. Hung T, Wang S, Kuo C, Pei B, Tsai K (2010) A study of organic working fluids on system efficiency of an ORC using low-grade energy sources. Energy 35:1403–1411CrossRefGoogle Scholar
  26. Ibarra M, Rovira A, Alarcón-Padilla D-C, Blanco J (2014) Performance of a 5 kWe Organic Rankine Cycle at part-load operation. Appl Energy 120:147–158. doi: 10.1016/j.apenergy.2014.01.057 CrossRefGoogle Scholar
  27. International Energy Agency (2014) Energy Efficiency Market Report, ParisGoogle Scholar
  28. Invernizzi CM (2013) Closed power cycles: thermodynamic fundamentals and applications, vol 11. Springer Science & Business Media, LondonGoogle Scholar
  29. Li L, Sun Z (2013) Dynamic energy control for energy efficiency improvement of sustainable manufacturing systems using Markov decision process. IEEE Trans Syst Man Cyber Syst 43:1195–1205CrossRefGoogle Scholar
  30. Liu Y, Yang J, Wang J, Cheng Z-L, Wang Q-W (2014) Energy and exergy analysis for waste heat cascade utilization in sinter cooling bed. Energy 67:370–380. doi: 10.1016/ CrossRefGoogle Scholar
  31. Madan J, Mani M, Lee JH, Lyons KW (2015) Energy performance evaluation and improvement of unit-manufacturing processes: injection molding case study. J Clean Prod 105:157–170. doi: 10.1016/j.jclepro.2014.09.060 CrossRefGoogle Scholar
  32. Mitra S, Grossmann IE, Pinto JM, Arora N (2012) Optimal production planning under time-sensitive electricity prices for continuous power-intensive processes. Comput Chem Eng 38:171–184CrossRefGoogle Scholar
  33. Moon J-Y, Park J (2013) Smart production scheduling with time-dependent and machine-dependent electricity cost by considering distributed energy resources and energy storage. Int J Prod Res 52:3922–3939. doi: 10.1080/00207543.2013.860251 CrossRefGoogle Scholar
  34. Mouzon G, Yildirim MB, Twomey J (2007) Operational methods for minimization of energy consumption of manufacturing equipment. Int J Prod Res 45:4247–4271CrossRefGoogle Scholar
  35. Neugebauer R, Wabner M, Rentzsch H, Ihlenfeldt S (2011) Structure principles of energy efficient machine tools. CIRP J Manuf Sci Technol 4:136–147CrossRefGoogle Scholar
  36. Nilsson K (1993) Industrial production planning with optimal electricity cost. Energy Convers Manag 34:153–158CrossRefGoogle Scholar
  37. Nilsson K, Söderström M (1993) Industrial applications of production planning with optimal electricity demand. Appl Energy 46:181–192CrossRefGoogle Scholar
  38. Obernberger I, Thonhofer P, Reisenhofer E (2002) Description and evaluation of the new 1000 kWel Organic Rankine Cycle process integrated in the biomass CHP plant in Lienz, Austria. Euroheat Power 10:1–17Google Scholar
  39. Organe and Rockland Utilities (2012) Service classification No. 20. Retrieved 15 January 2013. Accessed 27 April 2015
  40. Pehnt M, Bödeker J, Arens M, Jochem E, Idrissova F (2010) Die Nutzung industrieller Abwärme–technisch-wirtschaftliche Potenziale und energiepolitische Umsetzung. ifeu-Institut für Energie- und Umweltforschung Heidelberg, Fraunhofer Institut für System- und Innovationsforschung, IREES GmbH, Heidelberg, KarlsruheGoogle Scholar
  41. Pons M, Bikfalvi A, Llach J, Palcic I (2013) Exploring the impact of energy efficiency technologies on manufacturing firm performance. J Clean Prod 52:134–144. doi: 10.1016/j.jclepro.2013.03.011 CrossRefGoogle Scholar
  42. Quader MA, Ahmed S, Ghazilla RAR, Ahmed S, Dahari M (2015) A comprehensive review on energy efficient CO2 breakthrough technologies for sustainable green iron and steel manufacturing. Renew Sustain Energy Rev 50:594–614. doi: 10.1016/j.rser.2015.05.026 CrossRefGoogle Scholar
  43. Quoilin S, Aumann R, Grill A, Schuster A, Lemort V, Spliethoff H (2011a) Dynamic modeling and optimal control strategy of waste heat recovery Organic Rankine Cycles. Appl Energy 88:2183–2190. doi: 10.1016/j.apenergy.2011.01.015 CrossRefGoogle Scholar
  44. Quoilin S, Declaye S, Tchanche BF, Lemort V (2011b) Thermo-economic optimization of waste heat recovery Organic Rankine Cycles. Appl Therm Eng 31:2885–2893CrossRefGoogle Scholar
  45. Schneider M, Biel K, Pfaller S, Schaede H, Rinderknecht S, Glock CH (2015) Optimal Sizing of Electrical Energy Storage Systems using Inventory Models. Energy Procedia 73:48–58. doi: 10.1016/j.egypro.2015.07.559
  46. Shrouf F, Ordieres-Meré J, García-Sánchez A, Ortega-Mier M (2014) Optimizing the production scheduling of a single machine to minimize total energy consumption costs. J Clean Prod 67:197–207. doi: 10.1016/j.jclepro.2013.12.024 CrossRefGoogle Scholar
  47. Sun Z, Li L (2014) Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov decision process. J Clean Prod 65:184–193CrossRefGoogle Scholar
  48. Sun Z, Li L, Fernandez M, Wang J (2014) Inventory control for peak electricity demand reduction of manufacturing systems considering the tradeoff between production loss and energy savings. J Clean Prod 82:84–93. doi: 10.1016/j.jclepro.2014.06.071 CrossRefGoogle Scholar
  49. Tchanche BF, Quoilin S, Declaye S, Papadakis G, Lemort V (2010) Economic feasibility study of a small scale Organic Rankine Cycle system in waste heat recovery application. In: ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, pp 249–256, 2010. American Society of Mechanical EngineersGoogle Scholar
  50. U.S. Bureau of Labor Statistics (2013) International Labor Comparisons. Washington, DC.
  51. U.S. Energy Information Administration (2014) Annual Energy Outlook with projections to 2040. Washington, DC.
  52. U.S. Energy Information Administration (2015) Annual Energy Outlook with projections to 2040. Washington, DC.
  53. Wang Y, Li L (2013) Time-of-use based electricity demand response for sustainable manufacturing systems. Energy 63:233–244CrossRefGoogle Scholar
  54. Wang E, Zhang H, Fan B, Ouyang M, Zhao Y, Mu Q (2011) Study of working fluid selection of organic Rankine cycle (ORC) for engine waste heat recovery. Energy 36:3406–3418CrossRefGoogle Scholar
  55. Wei D, Lu X, Lu Z, Gu J (2007) Performance analysis and optimization of organic Rankine cycle (ORC) for waste heat recovery. Energy Convers Manag 48:1113–1119. doi: 10.1016/j.enconman.2006.10.020 CrossRefGoogle Scholar
  56. Weinert N, Chiotellis S, Seliger G (2011) Methodology for planning and operating energy-efficient production systems. CIRP Ann Manuf Technol 60:41–44. doi: 10.1016/j.cirp.2011.03.015 CrossRefGoogle Scholar
  57. Zakeri B, Syri S (2015) Electrical energy storage systems: a comparative life cycle cost analysis. Renew Sustain Energy Rev 42:569–596. doi: 10.1016/j.rser.2014.10.011 CrossRefGoogle Scholar
  58. Zanoni S, Bettoni L, Glock CH (2014) Energy implications in a two-stage production system with controllable production rates. Int J Prod Econ 149:164–171. doi: 10.1016/j.ijpe.2013.06.025 CrossRefGoogle Scholar
  59. Zhang H, Zhao F, Sutherland JW (2014) Manufacturing scheduling for energy cost reduction in a smart grid scenario. In: ASME 2014 International Manufacturing Science and Engineering Conference collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference, pp 1–10, 2014. American Society of Mechanical EngineersGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Institute of Production and Supply Chain ManagementTechnische Universität DarmstadtDarmstadtGermany

Personalised recommendations