IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2504.06932.html
   My bibliography  Save this paper

Maximizing Battery Storage Profits via High-Frequency Intraday Trading

Author

Listed:
  • David Schaurecker
  • David Wozabal
  • Nils Lohndorf
  • Thorsten Staake

Abstract

Maximizing revenue for grid-scale battery energy storage systems in continuous intraday electricity markets requires strategies that are able to seize trading opportunities as soon as new information arrives. This paper introduces and evaluates an automated high-frequency trading strategy for battery energy storage systems trading on the intraday market for power while explicitly considering the dynamics of the limit order book, market rules, and technical parameters. The standard rolling intrinsic strategy is adapted for continuous intraday electricity markets and solved using a dynamic programming approximation that is two to three orders of magnitude faster than an exact mixed-integer linear programming solution. A detailed backtest over a full year of German order book data demonstrates that the proposed dynamic programming formulation does not reduce trading profits and enables the policy to react to every relevant order book update, enabling realistic rapid backtesting. Our results show the significant revenue potential of high-frequency trading: our policy earns 58% more than when re-optimizing only once every hour and 14% more than when re-optimizing once per minute, highlighting that profits critically depend on trading speed. Furthermore, we leverage the speed of our algorithm to train a parametric extension of the rolling intrinsic, increasing yearly revenue by 8.4% out of sample.

Suggested Citation

  • David Schaurecker & David Wozabal & Nils Lohndorf & Thorsten Staake, 2025. "Maximizing Battery Storage Profits via High-Frequency Intraday Trading," Papers 2504.06932, arXiv.org, revised Apr 2025.
    • Handle: RePEc:arx:papers:2504.06932
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2504.06932
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alessandro Saldarini & Michela Longo & Morris Brenna & Dario Zaninelli, 2023. "Battery Electric Storage Systems: Advances, Challenges, and Market Trends," Energies, MDPI, vol. 16(22), pages 1-30, November.
    2. Nils Löhndorf & David Wozabal & Stefan Minner, 2013. "Optimizing Trading Decisions for Hydro Storage Systems Using Approximate Dual Dynamic Programming," Operations Research, INFORMS, vol. 61(4), pages 810-823, August.
    3. Christoph Graf & Thomas Kuppelwieser & David Wozabal, 2024. "Frequent Auctions for Intraday Electricity Markets," The Energy Journal, , vol. 45(1), pages 231-256, January.
    4. René Aïd & P. Gruet & H. Pham, 2016. "An optimal trading problem in intraday electricity markets," Post-Print hal-01609481, HAL.
    5. Thomas Kuppelwieser & David Wozabal, 2023. "Intraday power trading: toward an arms race in weather forecasting?," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 57-83, March.
    6. 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.
    7. Daniel R. Jiang & Warren B. Powell, 2015. "Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 525-543, August.
    8. Bertrand, Gilles & Papavasiliou, Anthony, 2020. "Adaptive Trading in Continuous Intraday Electricity Markets for a Storage Unit," LIDAM Reprints CORE 3104, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Guoming Lai & Mulan X. Wang & Sunder Kekre & Alan Scheller-Wolf & Nicola Secomandi, 2011. "Valuation of Storage at a Liquefied Natural Gas Terminal," Operations Research, INFORMS, vol. 59(3), pages 602-616, June.
    10. 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.
    11. Wozabal, David & Rameseder, Gunther, 2020. "Optimal bidding of a virtual power plant on the Spanish day-ahead and intraday market for electricity," European Journal of Operational Research, Elsevier, vol. 280(2), pages 639-655.
    12. Guoming Lai & François Margot & Nicola Secomandi, 2010. "An Approximate Dynamic Programming Approach to Benchmark Practice-Based Heuristics for Natural Gas Storage Valuation," Operations Research, INFORMS, vol. 58(3), pages 564-582, June.
    13. Löhndorf, Nils & Wozabal, David, 2021. "Gas storage valuation in incomplete markets," European Journal of Operational Research, Elsevier, vol. 288(1), pages 318-330.
    14. Braeuer, Fritz & Rominger, Julian & McKenna, Russell & Fichtner, Wolf, 2019. "Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry," Applied Energy, Elsevier, vol. 239(C), pages 1424-1440.
    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. 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.
    2. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.
    3. Yangfang (Helen) Zhou & Alan Scheller‐Wolf & Nicola Secomandi & Stephen Smith, 2019. "Managing Wind‐Based Electricity Generation in the Presence of Storage and Transmission Capacity," Production and Operations Management, Production and Operations Management Society, vol. 28(4), pages 970-989, April.
    4. Jochen Gönsch & Michael Hassler, 2016. "Sell or store? An ADP approach to marketing renewable energy," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 633-660, July.
    5. Anna Maria Gambaro & Nicola Secomandi, 2021. "A Discussion of Non‐Gaussian Price Processes for Energy and Commodity Operations," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 47-67, January.
    6. 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).
    7. John R. Birge, 2015. "OM Forum—Operations and Finance Interactions," Manufacturing & Service Operations Management, INFORMS, vol. 17(1), pages 4-15, February.
    8. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    9. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    10. Fraunholz, Christoph & Miskiw, Kim K. & Kraft, Emil & Fichtner, Wolf & Weber, Christoph, 2021. "On the role of risk aversion and market design in capacity expansion planning," Working Paper Series in Production and Energy 62, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    11. 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).
    12. Daniel R. Jiang & Warren B. Powell, 2018. "Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures," Mathematics of Operations Research, INFORMS, vol. 43(2), pages 554-579, May.
    13. Löhndorf, Nils & Wozabal, David, 2021. "Gas storage valuation in incomplete markets," European Journal of Operational Research, Elsevier, vol. 288(1), pages 318-330.
    14. Daniel R. Jiang & Warren B. Powell, 2015. "Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage Using Approximate Dynamic Programming," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 525-543, August.
    15. Nicola Secomandi & Guoming Lai & François Margot & Alan Scheller-Wolf & Duane J. Seppi, 2015. "Merchant Commodity Storage and Term-Structure Model Error," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 302-320, July.
    16. Alessio Trivella & Danial Mohseni-Taheri & Selvaprabu Nadarajah, 2023. "Meeting Corporate Renewable Power Targets," Management Science, INFORMS, vol. 69(1), pages 491-512, January.
    17. Enzo Cogn'eville & Thomas Deschatre & Xavier Warin, 2024. "Battery valuation on electricity intraday markets with liquidity costs," Papers 2412.15959, arXiv.org.
    18. Nicola Secomandi, 2015. "Merchant Commodity Storage Practice Revisited," Operations Research, INFORMS, vol. 63(5), pages 1131-1143, October.
    19. Demir, Sumeyra & Stappers, Bart & Kok, Koen & Paterakis, Nikolaos G., 2022. "Statistical arbitrage trading on the intraday market using the asynchronous advantage actor–critic method," Applied Energy, Elsevier, vol. 314(C).
    20. Thomas Hubner & Gabriela Hug, 2025. "Package Bids in Combinatorial Electricity Auctions: Selection, Welfare Losses, and Alternatives," Papers 2502.09420, arXiv.org, revised Apr 2025.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2504.06932. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.