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Bidding strategy for battery storage systems in the secondary control reserve market

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  • Merten, Michael
  • Olk, Christopher
  • Schoeneberger, Ilka
  • Sauer, Dirk Uwe

Abstract

In continental Europe, automatic Frequency Restoration Reserve (aFRR) is one of three control reserve services to counteract imbalances in the electrical grid. The market is dominated by a few operators of conventional power plants since the auction design is complex and new players face various entrance barriers. In order to stabilize the electrical grid in the future, renewable generation technologies need to enter the market. To encourage operators (and traders) of renewable generation facilities to enter the market, this paper presents a bidding strategy based on an optimization approach for deriving an optimal bid and for estimating the revenue potential on this market. The focus is on the participation of Battery Energy Storage Systems (BESS) either in standalone mode or in conjunction with a virtual power plant (VPP). An in-depth cost breakdown and battery ageing model support the derivation of earning potentials. With current costs of containerized BESS, an operation is not economically viable. However, with a predicted cost breakdown for the year 2025 and a pooled operation, profits can be generated. But even for the reduced-cost scenario, profits were found to be lower than on the Frequency Control Reserve (FCR) market.

Suggested Citation

  • Merten, Michael & Olk, Christopher & Schoeneberger, Ilka & Sauer, Dirk Uwe, 2020. "Bidding strategy for battery storage systems in the secondary control reserve market," Applied Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:appene:v:268:y:2020:i:c:s0306261920304633
    DOI: 10.1016/j.apenergy.2020.114951
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    References listed on IDEAS

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    Cited by:

    1. Glismann, Samuel, 2021. "Ancillary Services Acquisition Model: Considering market interactions in policy design," Applied Energy, Elsevier, vol. 304(C).
    2. 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).
    3. Zhao, Xinyi & Shen, Xinwei & Guo, Qinglai & Sun, Hongbin & Oren, Shmuel S., 2020. "A stochastic distribution system planning method considering regulation services and energy storage degradation," Applied Energy, Elsevier, vol. 277(C).
    4. Poplavskaya, Ksenia & Lago, Jesus & de Vries, Laurens, 2020. "Effect of market design on strategic bidding behavior: Model-based analysis of European electricity balancing markets," Applied Energy, Elsevier, vol. 270(C).
    5. Ahmed Mohamed & Rémy Rigo-Mariani & Vincent Debusschere & Lionel Pin, 2023. "Stacked Revenues for Energy Storage Participating in Energy and Reserve Markets with an Optimal Frequency Regulation Modeling," Post-Print hal-04182119, HAL.
    6. Yuan, Meng & Sorknæs, Peter & Lund, Henrik & Liang, Yongtu, 2022. "The bidding strategies of large-scale battery storage in 100% renewable smart energy systems," Applied Energy, Elsevier, vol. 326(C).
    7. Wang, Y. & Wang, J. & He, W., 2022. "Development of efficient, flexible and affordable heat pumps for supporting heat and power decarbonisation in the UK and beyond: Review and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    8. Kristina Pandžić & Ivan Pavić & Ivan Andročec & Hrvoje Pandžić, 2020. "Optimal Battery Storage Participation in European Energy and Reserves Markets," Energies, MDPI, vol. 13(24), pages 1-21, December.
    9. Fabian Rücker & Michael Merten & Jingyu Gong & Roberto Villafáfila-Robles & Ilka Schoeneberger & Dirk Uwe Sauer, 2020. "Evaluation of the Effects of Smart Charging Strategies and Frequency Restoration Reserves Market Participation of an Electric Vehicle," Energies, MDPI, vol. 13(12), pages 1-31, June.
    10. Kuttner, Leopold, 2022. "Integrated scheduling and bidding of power and reserve of energy resource aggregators with storage plants," Applied Energy, Elsevier, vol. 321(C).
    11. Nebuloni, Riccardo & Meraldi, Lorenzo & Bovo, Cristian & Ilea, Valentin & Berizzi, Alberto & Sinha, Snigdh & Tamirisakandala, Raviteja Bharadwaj & Raboni, Pietro, 2023. "A hierarchical two-level MILP optimization model for the management of grid-connected BESS considering accurate physical model," Applied Energy, Elsevier, vol. 334(C).

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