IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v328y2023i2d10.1007_s10479-023-05338-x.html
   My bibliography  Save this article

Production planning under RTP, TOU and PPA considering a redox flow battery storage system

Author

Listed:
  • Markus Hilbert

    (FernUniversität in Hagen)

  • Andreas Dellnitz

    (Leibniz FH School of Business)

  • Andreas Kleine

    (FernUniversität in Hagen)

Abstract

Due to climate change and the increasing scarcity of resources, the sustainability performance of companies is increasingly becoming the focus of science and practice. Consequently, bicriteria energy-efficient production planning under price-dynamic electricity tariffs—e.g., real-time-pricing (RTP) or time-of-use (TOU)—is meanwhile well established, often fathoming the tradeoffs between electricity costs of production and another criterion such as makespan. However, tradeoffs between electricity costs and electricity consumption in general are rarely the focus of such analyses. So-called green power purchase agreements (PPAs), which are becoming increasingly popular in the European business community as a means of improving corporate sustainability performance, are also largely ignored. Thus, for the first time in the scientific literature, we put this type of electricity tariff to the test by analyzing the tradeoffs between electricity costs and electricity consumption in a lot-sizing and scheduling context. Here, we additionally consider a real-world redox flow battery storage system that may be the system of the future, which is also new to the literature on lot-sizing and scheduling. Even more: due to the complex nature of our bicriteria mixed-integer problem, we develop and present suitable heuristics. These include an energy-efficient allocation heuristic in the case of PPA and, among others, a fix-relax-and-optimize heuristic combined with a decomposition approach in the case of RTP and TOU. Ultimately, a scenario analysis demonstrates the performance of these heuristics.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:annopr:v:328:y:2023:i:2:d:10.1007_s10479-023-05338-x
    DOI: 10.1007/s10479-023-05338-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-023-05338-x
    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/s10479-023-05338-x?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. Zhang, Yunchao & Islam, Md Monirul & Sun, Zeyi & Yang, Sijia & Dagli, Cihan & Xiong, Haoyi, 2018. "Optimal sizing and planning of onsite generation system for manufacturing in Critical Peaking Pricing demand response program," International Journal of Production Economics, Elsevier, vol. 206(C), pages 261-267.
    2. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    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. Ruiz Duarte, José Luis & Fan, Neng & Jin, Tongdan, 2020. "Multi-process production scheduling with variable renewable integration and demand response," European Journal of Operational Research, Elsevier, vol. 281(1), pages 186-200.
    5. Xiuli Wu & Xianli Shen & Qi Cui, 2018. "Multi-Objective Flexible Flow Shop Scheduling Problem Considering Variable Processing Time due to Renewable Energy," Sustainability, MDPI, vol. 10(3), pages 1-30, March.
    6. Josef Kallrath, 2021. "Business Optimization Using Mathematical Programming," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-030-73237-0, September.
    7. 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.
    8. Rapine, Christophe & Goisque, Guillaume & Akbalik, Ayse, 2018. "Energy-aware lot sizing problem: Complexity analysis and exact algorithms," International Journal of Production Economics, Elsevier, vol. 203(C), pages 254-263.
    9. 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.
    10. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
    11. 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).
    12. Ciwei Dong & Bin Shen & Pui-Sze Chow & Liu Yang & Chi To Ng, 2016. "Sustainability investment under cap-and-trade regulation," Annals of Operations Research, Springer, vol. 240(2), pages 509-531, May.
    13. Yevgenia Mikhaylidi & Hussein Naseraldin & Liron Yedidsion, 2015. "Operations scheduling under electricity time-varying prices," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7136-7157, December.
    14. Guangchen Wang & Xinyu Li & Liang Gao & Peigen Li, 2022. "An effective multi-objective whale swarm algorithm for energy-efficient scheduling of distributed welding flow shop," Annals of Operations Research, Springer, vol. 310(1), pages 223-255, March.
    15. Cheng-Hsiang Liu, 2016. "Mathematical programming formulations for single-machine scheduling problems while considering renewable energy uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(4), pages 1122-1133, February.
    16. Arda Yenipazarli & Asoo J. Vakharia, 2017. "Green, greener or brown: choosing the right color of the product," Annals of Operations Research, Springer, vol. 250(2), pages 537-567, March.
    17. Söhnke Maecker & Liji Shen, 2020. "Solving parallel machine problems with delivery times and tardiness objectives," Annals of Operations Research, Springer, vol. 285(1), pages 315-334, February.
    18. 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.
    19. Meyr, Herbert & Mann, Matthias, 2013. "A decomposition approach for the General Lotsizing and Scheduling Problem for Parallel production Lines," European Journal of Operational Research, Elsevier, vol. 229(3), pages 718-731.
    20. 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.
    21. Eid, Cherrelle & Koliou, Elta & Valles, Mercedes & Reneses, Javier & Hakvoort, Rudi, 2016. "Time-based pricing and electricity demand response: Existing barriers and next steps," Utilities Policy, Elsevier, vol. 40(C), pages 15-25.
    22. Karina Copil & Martin Wörbelauer & Herbert Meyr & Horst Tempelmeier, 2017. "Simultaneous lotsizing and scheduling problems: a classification and review of models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 1-64, January.
    23. Ronghua Meng & Yunqing Rao & Qiang Luo, 2020. "Modeling and solving for bi-objective cutting parallel machine scheduling problem," Annals of Operations Research, Springer, vol. 285(1), pages 223-245, February.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    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. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    4. Weiwei Cui & Lin Li & Zhiqiang Lu, 2019. "Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(2), pages 154-173, March.
    5. 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.
    6. 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.
    7. 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.
    8. Weiwei Cui & Biao Lu, 2020. "A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    9. Fei Luan & Zongyan Cai & Shuqiang Wu & Shi Qiang Liu & Yixin He, 2019. "Optimizing the Low-Carbon Flexible Job Shop Scheduling Problem with Discrete Whale Optimization Algorithm," Mathematics, MDPI, vol. 7(8), pages 1-17, August.
    10. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    11. 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.
    12. 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.
    13. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    14. Andrzej Bożek, 2020. "Energy Cost-Efficient Task Positioning in Manufacturing Systems," Energies, MDPI, vol. 13(19), pages 1-21, September.
    15. Mac Cawley, Alejandro & Maturana, Sergio & Pascual, Rodrigo & Tortorella, Guilherme Luz, 2022. "Scheduling wine bottling operations with multiple lines and sequence-dependent set-up times: Robust formulation and a decomposition solution approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 819-839.
    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. 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.
    20. K. A. G. Araujo & E. G. Birgin & M. S. Kawamura & D. P. Ronconi, 2023. "Relax-and-Fix Heuristics Applied to a Real-World Lot Sizing and Scheduling Problem in the Personal Care Consumer Goods Industry," SN Operations Research Forum, Springer, vol. 4(2), pages 1-30, June.

    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:annopr:v:328:y:2023:i:2:d:10.1007_s10479-023-05338-x. 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.