IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i6p999-d213970.html
   My bibliography  Save this article

Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †

Author

Listed:
  • Holger C. Hesse

    (Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 Munich, Germany
    These authors contributed equally to this work.)

  • Volkan Kumtepeli

    (Energy Research Institute @ NTU, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore 637371, Singapore
    These authors contributed equally to this work.)

  • Michael Schimpe

    (Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 Munich, Germany)

  • Jorn Reniers

    (Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
    Energy Technology Unit, Vlaamse Instelling voor Technologisch Onderzoek (VITO), Boeretang 200, 2400 Mol, Belgium)

  • David A. Howey

    (Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK)

  • Anshuman Tripathi

    (Energy Research Institute @ NTU, Nanyang Technological University, Singapore 637141, Singapore)

  • Youyi Wang

    (School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Andreas Jossen

    (Department of Electrical and Computer Engineering, Technical University of Munich (TUM), 80333 Munich, Germany)

Abstract

To achieve maximum profit by dispatching a battery storage system in an arbitrage operation, multiple factors must be considered. While revenue from the application is determined by the time variability of the electricity cost, the profit will be lowered by costs resulting from energy efficiency losses, as well as by battery degradation. In this paper, an optimal dispatch strategy is proposed for storage systems trading on energy arbitrage markets. The dispatch is based on a computationally-efficient implementation of a mixed-integer linear programming method, with a cost function that includes variable-energy conversion losses and a cycle-induced battery capacity fade. The parametrisation of these non-linear functions is backed by in-house laboratory tests. A detailed analysis of the proposed methods is given through case studies of different cost-inclusion scenarios, as well as battery investment-cost scenarios. An evaluation with a sample intraday market data set, collected throughout 2017 in Germany, offers a potential monthly revenue of up to 8762 EUR/MWh cap installed capacity, without accounting for the costs attributed to energy losses and battery degradation. While this is slightly above the revenue attainable in a reference application—namely, primary frequency regulation for the same sample month (7716 EUR/MWh cap installed capacity)—the situation changes if costs are considered: The optimisation reveals that losses in battery ageing and efficiency reduce the attainable profit by up to 36% for the most profitable arbitrage use case considered herein. The findings underline the significance of considering both ageing and efficiency in battery system dispatch optimisation.

Suggested Citation

  • Holger C. Hesse & Volkan Kumtepeli & Michael Schimpe & Jorn Reniers & David A. Howey & Anshuman Tripathi & Youyi Wang & Andreas Jossen, 2019. "Ageing and Efficiency Aware Battery Dispatch for Arbitrage Markets Using Mixed Integer Linear Programming †," Energies, MDPI, vol. 12(6), pages 1-28, March.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:999-:d:213970
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/6/999/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/6/999/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Graves, Frank & Jenkin, Thomas & Murphy, Dean, 1999. "Opportunities for Electricity Storage in Deregulating Markets," The Electricity Journal, Elsevier, vol. 12(8), pages 46-56, October.
    2. Hirth, Lion & Ueckerdt, Falko & Edenhofer, Ottmar, 2015. "Integration costs revisited – An economic framework for wind and solar variability," Renewable Energy, Elsevier, vol. 74(C), pages 925-939.
    3. Rodrigo Martins & Holger C. Hesse & Johanna Jungbauer & Thomas Vorbuchner & Petr Musilek, 2018. "Optimal Component Sizing for Peak Shaving in Battery Energy Storage System for Industrial Applications," Energies, MDPI, vol. 11(8), pages 1-22, August.
    4. Greenwood, D.M. & Lim, K.Y. & Patsios, C. & Lyons, P.F. & Lim, Y.S. & Taylor, P.C., 2017. "Frequency response services designed for energy storage," Applied Energy, Elsevier, vol. 203(C), pages 115-127.
    5. Björn Nykvist & Måns Nilsson, 2015. "Rapidly falling costs of battery packs for electric vehicles," Nature Climate Change, Nature, vol. 5(4), pages 329-332, April.
    6. A. Stephan & B. Battke & M. D. Beuse & J. H. Clausdeinken & T. S. Schmidt, 2016. "Limiting the public cost of stationary battery deployment by combining applications," Nature Energy, Nature, vol. 1(7), pages 1-9, July.
    7. Schimpe, Michael & Naumann, Maik & Truong, Nam & Hesse, Holger C. & Santhanagopalan, Shriram & Saxon, Aron & Jossen, Andreas, 2018. "Energy efficiency evaluation of a stationary lithium-ion battery container storage system via electro-thermal modeling and detailed component analysis," Applied Energy, Elsevier, vol. 210(C), pages 211-229.
    8. Moreno, Rodrigo & Moreira, Roberto & Strbac, Goran, 2015. "A MILP model for optimising multi-service portfolios of distributed energy storage," Applied Energy, Elsevier, vol. 137(C), pages 554-566.
    9. Bradbury, Kyle & Pratson, Lincoln & Patiño-Echeverri, Dalia, 2014. "Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity markets," Applied Energy, Elsevier, vol. 114(C), pages 512-519.
    10. Michael Schimpe & Christian Piesch & Holger C. Hesse & Julian Paß & Stefan Ritter & Andreas Jossen, 2018. "Power Flow Distribution Strategy for Improved Power Electronics Energy Efficiency in Battery Storage Systems: Development and Implementation in a Utility-Scale System," Energies, MDPI, vol. 11(3), pages 1-17, March.
    11. Holger C. Hesse & Michael Schimpe & Daniel Kucevic & Andreas Jossen, 2017. "Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids," Energies, MDPI, vol. 10(12), pages 1-42, December.
    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. Robert Małkowski & Marcin Jaskólski & Wojciech Pawlicki, 2020. "Operation of the Hybrid Photovoltaic-Battery System on the Electricity Market—Simulation, Real-Time Tests and Cost Analysis," Energies, MDPI, vol. 13(6), pages 1-21, March.
    2. Carlos García-Santacruz & Luis Galván & Juan M. Carrasco & Eduardo Galván, 2021. "Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence," Energies, MDPI, vol. 14(11), pages 1-17, June.
    3. Iris, Çağatay & Lam, Jasmine Siu Lee, 2021. "Optimal energy management and operations planning in seaports with smart grid while harnessing renewable energy under uncertainty," Omega, Elsevier, vol. 103(C).
    4. Specht, Jan Martin & Madlener, Reinhard, 2023. "Quantifying value pools for distributed flexible energy assets," Energy, Elsevier, vol. 263(PB).
    5. Murat Ceylan & Abdulkadir Balikci, 2023. "An Intermodular Active Balancing Topology for Efficient Operation of High Voltage Battery Packs in Li-Ion Based Energy Storage Systems: Switched (Flying) DC/DC Converter," Energies, MDPI, vol. 16(15), pages 1-22, July.
    6. Kanbur, Baris Burak & Kumtepeli, Volkan & Duan, Fei, 2020. "Thermal performance prediction of the battery surface via dynamic mode decomposition," Energy, Elsevier, vol. 201(C).
    7. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    8. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    9. Walmsley, Timothy Gordon & Philipp, Matthias & Picón-Núñez, Martín & Meschede, Henning & Taylor, Matthew Thomas & Schlosser, Florian & Atkins, Martin John, 2023. "Hybrid renewable energy utility systems for industrial sites: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    10. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).

    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. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
    2. Holger C. Hesse & Michael Schimpe & Daniel Kucevic & Andreas Jossen, 2017. "Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids," Energies, MDPI, vol. 10(12), pages 1-42, December.
    3. Jürgen Marchgraber & Wolfgang Gawlik, 2021. "Dynamic Prioritization of Functions during Real-Time Multi-Use Operation of Battery Energy Storage Systems," Energies, MDPI, vol. 14(3), pages 1-36, January.
    4. Bernhard Faessler, 2021. "Stationary, Second Use Battery Energy Storage Systems and Their Applications: A Research Review," Energies, MDPI, vol. 14(8), pages 1-19, April.
    5. Rangarajan, Arvind & Foley, Sean & Trück, Stefan, 2023. "Assessing the impact of battery storage on Australian electricity markets," Energy Economics, Elsevier, vol. 120(C).
    6. Stefan Englberger & Holger Hesse & Daniel Kucevic & Andreas Jossen, 2019. "A Techno-Economic Analysis of Vehicle-to-Building: Battery Degradation and Efficiency Analysis in the Context of Coordinated Electric Vehicle Charging," Energies, MDPI, vol. 12(5), pages 1-17, March.
    7. Walmsley, Timothy Gordon & Philipp, Matthias & Picón-Núñez, Martín & Meschede, Henning & Taylor, Matthew Thomas & Schlosser, Florian & Atkins, Martin John, 2023. "Hybrid renewable energy utility systems for industrial sites: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    8. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    9. Rodrigo Martins & Holger C. Hesse & Johanna Jungbauer & Thomas Vorbuchner & Petr Musilek, 2018. "Optimal Component Sizing for Peak Shaving in Battery Energy Storage System for Industrial Applications," Energies, MDPI, vol. 11(8), pages 1-22, August.
    10. Ziad Ragab & Ehsan Pashajavid & Sumedha Rajakaruna, 2024. "Optimal Sizing and Economic Analysis of Community Battery Systems Considering Sensitivity and Uncertainty Factors," Energies, MDPI, vol. 17(18), pages 1-20, September.
    11. Chen, Yang & Odukomaiya, Adewale & Kassaee, Saiid & O’Connor, Patrick & Momen, Ayyoub M. & Liu, Xiaobing & Smith, Brennan T., 2019. "Preliminary analysis of market potential for a hydropneumatic ground-level integrated diverse energy storage system," Applied Energy, Elsevier, vol. 242(C), pages 1237-1247.
    12. McConnell, Dylan & Forcey, Tim & Sandiford, Mike, 2015. "Estimating the value of electricity storage in an energy-only wholesale market," Applied Energy, Elsevier, vol. 159(C), pages 422-432.
    13. Parlikar, Anupam & Truong, Cong Nam & Jossen, Andreas & Hesse, Holger, 2021. "The carbon footprint of island grids with lithium-ion battery systems: An analysis based on levelized emissions of energy supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    14. Parlikar, Anupam & Schott, Maximilian & Godse, Ketaki & Kucevic, Daniel & Jossen, Andreas & Hesse, Holger, 2023. "High-power electric vehicle charging: Low-carbon grid integration pathways with stationary lithium-ion battery systems and renewable generation," Applied Energy, Elsevier, vol. 333(C).
    15. Pusceddu, Elian & Zakeri, Behnam & Castagneto Gissey, Giorgio, 2021. "Synergies between energy arbitrage and fast frequency response for battery energy storage systems," Applied Energy, Elsevier, vol. 283(C).
    16. de Sisternes, Fernando J. & Jenkins, Jesse D. & Botterud, Audun, 2016. "The value of energy storage in decarbonizing the electricity sector," Applied Energy, Elsevier, vol. 175(C), pages 368-379.
    17. Li, Yang & Vilathgamuwa, Mahinda & Choi, San Shing & Farrell, Troy W. & Tran, Ngoc Tham & Teague, Joseph, 2019. "Development of a degradation-conscious physics-based lithium-ion battery model for use in power system planning studies," Applied Energy, Elsevier, vol. 248(C), pages 512-525.
    18. Giuliano Rancilio & Alexandre Lucas & Evangelos Kotsakis & Gianluca Fulli & Marco Merlo & Maurizio Delfanti & Marcelo Masera, 2019. "Modeling a Large-Scale Battery Energy Storage System for Power Grid Application Analysis," Energies, MDPI, vol. 12(17), pages 1-26, August.
    19. Schopfer, S. & Tiefenbeck, V. & Staake, T., 2018. "Economic assessment of photovoltaic battery systems based on household load profiles," Applied Energy, Elsevier, vol. 223(C), pages 229-248.
    20. Wu, Wei & Lin, Boqiang, 2018. "Application value of energy storage in power grid: A special case of China electricity market," Energy, Elsevier, vol. 165(PB), pages 1191-1199.

    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:gam:jeners:v:12:y:2019:i:6:p:999-:d:213970. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.