IDEAS home Printed from https://ideas.repec.org/a/spr/jbecon/v90y2020i9d10.1007_s11573-020-01000-1.html
   My bibliography  Save this article

Energy costs vs. carbon dioxide emissions in short-term production planning

Author

Listed:
  • Andreas Dellnitz

    (FernUniversität in Hagen, Chair of Operations Research)

  • Damian Braschczok

    (FernUniversität in Hagen, Chair of Operations Research)

  • Jonas Ostmeyer

    (FernUniversität in Hagen, Chair of Operations Research)

  • Markus Hilbert

    (FernUniversität in Hagen, Chair of Operations Research)

  • Andreas Kleine

    (FernUniversität in Hagen, Chair of Operations Research)

Abstract

In energy-oriented lot-sizing and scheduling research, it is often assumed that minimizing energy costs automatically leads to an improvement of the ecological footprint of a company, i.e., lower carbon dioxide emissions. More precisely, a close to one (positive) correlation between energy costs and carbon dioxide emissions is often supposed. In this contribution, we show that this conjecture does not always hold true due to fluctuating carbon dioxide emissions over the whole day. Therefore, we present a real-world business case study, combining lot-sizing and machine scheduling under time-varying electric energy costs and carbon dioxide emissions in a mixed integer optimization model; in this context, we also consider on-site power generation. The interplay between all these aspects is demonstrated via a numerical analysis.

Suggested Citation

  • Andreas Dellnitz & Damian Braschczok & Jonas Ostmeyer & Markus Hilbert & Andreas Kleine, 2020. "Energy costs vs. carbon dioxide emissions in short-term production planning," Journal of Business Economics, Springer, vol. 90(9), pages 1383-1407, November.
    • Handle: RePEc:spr:jbecon:v:90:y:2020:i:9:d:10.1007_s11573-020-01000-1
    DOI: 10.1007/s11573-020-01000-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11573-020-01000-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11573-020-01000-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Munda, G. & Nijkamp, P. & Rietveld, P., 1994. "Qualitative multicriteria evaluation for environmental management," Ecological Economics, Elsevier, vol. 10(2), pages 97-112, July.
    2. Gahm, Christian & Denz, Florian & Dirr, Martin & Tuma, Axel, 2016. "Energy-efficient scheduling in manufacturing companies: A review and research framework," European Journal of Operational Research, Elsevier, vol. 248(3), pages 744-757.
    3. Matthias Gerhard Wichmann & Christoph Johannes & Thomas Stefan Spengler, 2019. "An extension of the general lot-sizing and scheduling problem (GLSP) with time-dependent energy prices," Journal of Business Economics, Springer, vol. 89(5), pages 481-514, July.
    4. Christoph Johannes & Matthias G. Wichmann & Thomas S. Spengler, 2018. "Flexible Production Scheduling with Volatile Energy Rates," Operations Research Proceedings, in: Andreas Fink & Armin Fügenschuh & Martin Josef Geiger (ed.), Operations Research Proceedings 2016, pages 489-495, Springer.
    5. David Wozabal & Christoph Graf & David Hirschmann, 2016. "The effect of intermittent renewables on the electricity price variance," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 687-709, July.
    6. Jaehn, Florian, 2016. "Sustainable Operations," European Journal of Operational Research, Elsevier, vol. 253(2), pages 243-264.
    7. Biel, K. & Glock, C. H., 2016. "Systematic literature review of decision support models for energy-efficient production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83071, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    9. Matthias Gerhard Wichmann & Christoph Johannes & Thomas Stefan Spengler, 2019. "Correction to: An extension of the general lot-sizing and scheduling problem (GLSP) with time-dependent energy prices," Journal of Business Economics, Springer, vol. 89(6), pages 739-742, August.
    10. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Markus Hilbert & Andreas Dellnitz & Andreas Kleine, 2023. "Production planning under RTP, TOU and PPA considering a redox flow battery storage system," Annals of Operations Research, Springer, vol. 328(2), pages 1409-1436, September.
    2. Rainer Baule & Michael Naumann, 2022. "Flexible Short-Term Electricity Certificates—An Analysis of Trading Strategies on the Continuous Intraday Market," Energies, MDPI, vol. 15(17), pages 1-28, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ghorbanzadeh, Masoumeh & Ranjbar, Mohammad, 2023. "Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints," European Journal of Operational Research, Elsevier, vol. 307(2), pages 519-537.
    2. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    3. Sven Schulz & Udo Buscher & Liji Shen, 2020. "Multi-objective hybrid flow shop scheduling with variable discrete production speed levels and time-of-use energy prices," Journal of Business Economics, Springer, vol. 90(9), pages 1315-1343, November.
    4. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.
    5. Markus Hilbert & Andreas Dellnitz & Andreas Kleine, 2023. "Production planning under RTP, TOU and PPA considering a redox flow battery storage system," Annals of Operations Research, Springer, vol. 328(2), pages 1409-1436, September.
    6. Abbas Hamze & Yassine Ouazene & Nazir Chebbo & Imane Maatouk, 2019. "Multisources of Energy Contracting Strategy with an Ecofriendly Factor and Demand Uncertainties," Energies, MDPI, vol. 12(20), pages 1-24, October.
    7. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    8. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    9. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    10. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    11. Hain, Martin & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2017. "An Electricity Price Modeling Framework for Renewable-Dominant Markets," Working Paper Series in Production and Energy 23, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    12. Andrzej Bożek, 2020. "Energy Cost-Efficient Task Positioning in Manufacturing Systems," Energies, MDPI, vol. 13(19), pages 1-21, September.
    13. Liu, Ying & Dong, Haibo & Lohse, Niels & Petrovic, Sanja, 2016. "A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance," International Journal of Production Economics, Elsevier, vol. 179(C), pages 259-272.
    14. Förster, Robert & Harding, Sebastian & Buhl, Hans Ulrich, 2024. "Unleashing the economic and ecological potential of energy flexibility: Attractiveness of real-time electricity tariffs in energy crises," Energy Policy, Elsevier, vol. 185(C).
    15. Heydar, Mojtaba & Mardaneh, Elham & Loxton, Ryan, 2022. "Approximate dynamic programming for an energy-efficient parallel machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 302(1), pages 363-380.
    16. Zhou, Shengchao & Jin, Mingzhou & Du, Ni, 2020. "Energy-efficient scheduling of a single batch processing machine with dynamic job arrival times," Energy, Elsevier, vol. 209(C).
    17. Shen, Liji & Dauzère-Pérès, Stéphane & Maecker, Söhnke, 2023. "Energy cost efficient scheduling in flexible job-shop manufacturing systems," European Journal of Operational Research, Elsevier, vol. 310(3), pages 992-1016.
    18. Martin Bichler & Hans Ulrich Buhl & Johannes Knörr & Felipe Maldonado & Paul Schott & Stefan Waldherr & Martin Weibelzahl, 2022. "Electricity Markets in a Time of Change: A Call to Arms for Business Research," Schmalenbach Journal of Business Research, Springer, vol. 74(1), pages 77-102, March.
    19. Gunther Glenk & Stefan Reichelstein, 2020. "Synergistic Value in Vertically Integrated Power‐to‐Gas Energy Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(3), pages 526-546, March.
    20. Anghinolfi, Davide & Paolucci, Massimo & Ronco, Roberto, 2021. "A bi-objective heuristic approach for green identical parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 289(2), pages 416-434.

    More about this item

    Keywords

    Energy costs; Carbon dioxide emissions; Multi-objective production planning; Sustainable manufacturing;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jbecon:v:90:y:2020:i:9:d:10.1007_s11573-020-01000-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.