IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v352y2023ics0306261923010310.html
   My bibliography  Save this article

Optimizing the marketing of flexibility for a virtual battery in day-ahead and balancing markets: A rolling horizon case study

Author

Listed:
  • Finhold, E.
  • Gärtner, C.
  • Grindel, R.
  • Heller, T.
  • Leithäuser, N.
  • Röger, E.
  • Schirra, F.

Abstract

Industrial electricity consumers with flexible demand can profit from adjusting their load to short-term prices or by providing balancing services to the grid. Markets which support this kind of short-term position adjustment are the day-ahead market and balancing markets. We propose a formulation for a combined optimization model that computes an optimal distribution of flexibility between the balancing and day-ahead markets. The optimal solution also includes the specific bids for the day-ahead and balancing markets. Besides the expected profits of each market and their different rules for bidding, our model also takes their different roles in a continuous marketing of flexibility into account. To prevent overrating short-term profits we introduce a variable penalty term that adds a cost to unfavorable load schedules. We evaluate the optimization model in a rolling horizon case study based on the setting of a virtual battery at TRIMET Aluminum SE, which is derived from a flexible aluminum electrolysis process. For such a battery we compute a daily optimal split of flexibility and trading decisions based on data in the period 04/2021–03/2022. We show that the optimal split is more profitable than using only one market or a fixed split between the markets.

Suggested Citation

  • Finhold, E. & Gärtner, C. & Grindel, R. & Heller, T. & Leithäuser, N. & Röger, E. & Schirra, F., 2023. "Optimizing the marketing of flexibility for a virtual battery in day-ahead and balancing markets: A rolling horizon case study," Applied Energy, Elsevier, vol. 352(C).
  • Handle: RePEc:eee:appene:v:352:y:2023:i:c:s0306261923010310
    DOI: 10.1016/j.apenergy.2023.121667
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923010310
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.121667?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. Kraft, Emil & Russo, Marianna & Keles, Dogan & Bertsch, Valentin, 2023. "Stochastic optimization of trading strategies in sequential electricity markets," European Journal of Operational Research, Elsevier, vol. 308(1), pages 400-421.
    2. Eduardo Faria & Stein-Erik Fleten, 2011. "Day-ahead market bidding for a Nordic hydropower producer: taking the Elbas market into account," Computational Management Science, Springer, vol. 8(1), pages 75-101, April.
    3. Xiaolin Ayón & María Ángeles Moreno & Julio Usaola, 2017. "Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets," Energies, MDPI, vol. 10(4), pages 1-20, April.
    4. Wagner, Andreas & Ramentol, Enislay & Schirra, Florian & Michaeli, Hendrik, 2022. "Short- and long-term forecasting of electricity prices using embedding of calendar information in neural networks," Journal of Commodity Markets, Elsevier, vol. 28(C).
    5. Boomsma, Trine Krogh & Juul, Nina & Fleten, Stein-Erik, 2014. "Bidding in sequential electricity markets: The Nordic case," European Journal of Operational Research, Elsevier, vol. 238(3), pages 797-809.
    6. Fabian Ocker & Karl‐Martin Ehrhart & Marion Ott, 2018. "Bidding strategies in Austrian and German balancing power auctions," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(6), November.
    7. Xenos, Dionysios P. & Mohd Noor, Izzati & Matloubi, Mitra & Cicciotti, Matteo & Haugen, Trond & Thornhill, Nina F., 2016. "Demand-side management and optimal operation of industrial electricity consumers: An example of an energy-intensive chemical plant," Applied Energy, Elsevier, vol. 182(C), pages 418-433.
    8. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    9. Ottesen, Stig Ødegaard & Tomasgard, Asgeir & Fleten, Stein-Erik, 2018. "Multi market bidding strategies for demand side flexibility aggregators in electricity markets," Energy, Elsevier, vol. 149(C), pages 120-134.
    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. Bohlayer, Markus & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2020. "Energy-intense production-inventory planning with participation in sequential energy markets," Applied Energy, Elsevier, vol. 258(C).
    2. Lopez, A. & Ogayar, B. & Hernández, J.C. & Sutil, F.S., 2020. "Survey and assessment of technical and economic features for the provision of frequency control services by household-prosumers," Energy Policy, Elsevier, vol. 146(C).
    3. Gro Klæboe & Jørgen Braathen & Anders Lund Eriksrud & Stein-Erik Fleten, 2022. "Day-ahead market bidding taking the balancing power market into account," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 683-703, October.
    4. Kraft, Emil & Russo, Marianna & Keles, Dogan & Bertsch, Valentin, 2023. "Stochastic optimization of trading strategies in sequential electricity markets," European Journal of Operational Research, Elsevier, vol. 308(1), pages 400-421.
    5. Nitsch, Felix & Deissenroth-Uhrig, Marc & Schimeczek, Christoph & Bertsch, Valentin, 2021. "Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets," Applied Energy, Elsevier, vol. 298(C).
    6. Kuttner, Leopold, 2022. "Integrated scheduling and bidding of power and reserve of energy resource aggregators with storage plants," Applied Energy, Elsevier, vol. 321(C).
    7. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    8. Klyve, Øyvind Sommer & Klæboe, Gro & Nygård, Magnus Moe & Marstein, Erik Stensrud, 2023. "Limiting imbalance settlement costs from variable renewable energy sources in the Nordics: Internal balancing vs. balancing market participation," Applied Energy, Elsevier, vol. 350(C).
    9. Spodniak, Petr & Ollikka, Kimmo & Honkapuro, Samuli, 2019. "The Relevance of Wholesale Electricity Market Places: The Nordic Case," Working Papers 126, VATT Institute for Economic Research.
    10. Spodniak, Petr & Ollikka, Kimmo & Honkapuro, Samuli, 2021. "The impact of wind power and electricity demand on the relevance of different short-term electricity markets: The Nordic case," Applied Energy, Elsevier, vol. 283(C).
    11. Narajewski, Michał & Ziel, Florian, 2022. "Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs," Energy Economics, Elsevier, vol. 110(C).
    12. Fatras, Nicolas & Ma, Zheng & Duan, Hongbo & Jørgensen, Bo Nørregaard, 2022. "A systematic review of electricity market liberalisation and its alignment with industrial consumer participation: A comparison between the Nordics and China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    13. Bohlayer, Markus & Bürger, Adrian & Fleschutz, Markus & Braun, Marco & Zöttl, Gregor, 2021. "Multi-period investment pathways - Modeling approaches to design distributed energy systems under uncertainty," Applied Energy, Elsevier, vol. 285(C).
    14. Marte Fodstad & Mats Mathisen Aarlott & Kjetil Trovik Midthun, 2017. "Value-Creation Potential from Multi-Market Trading for a Hydropower Producer," Energies, MDPI, vol. 11(1), pages 1-15, December.
    15. Herding, Robert & Ross, Emma & Jones, Wayne R. & Charitopoulos, Vassilis M. & Papageorgiou, Lazaros G., 2023. "Stochastic programming approach for optimal day-ahead market bidding curves of a microgrid," Applied Energy, Elsevier, vol. 336(C).
    16. Wanapinit, Natapon & Thomsen, Jessica & Weidlich, Anke, 2022. "Integrating flexibility provision into operation planning: A generic framework to assess potentials and bid prices of end-users," Energy, Elsevier, vol. 261(PB).
    17. Karim L. Anaya & Michael G. Pollitt, 2021. "How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects," Energies, MDPI, vol. 14(15), pages 1-26, July.
    18. Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
    19. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    20. Che, Gelegen & Zhang, Yanyan & Tang, Lixin & Zhao, Shengnan, 2023. "A deep reinforcement learning based multi-objective optimization for the scheduling of oxygen production system in integrated iron and steel plants," Applied Energy, Elsevier, vol. 345(C).

    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:eee:appene:v:352:y:2023:i:c:s0306261923010310. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.