IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2015i1p12-d61318.html
   My bibliography  Save this article

A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs

Author

Listed:
  • Enrico Telaretti

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128, Palermo, Italy)

  • Mariano Ippolito

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128, Palermo, Italy)

  • Luigi Dusonchet

    (Department of Energy, Information Engineering and Mathematical Models, University of Palermo, Viale delle Scienze, 90128, Palermo, Italy)

Abstract

Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, where the customer electricity cost may vary at any hour of day, and power consumption can be managed in a more flexible and economical manner, taking advantage of the price differential. Instead of modifying their energy consumption, customers can install storage systems to reduce their electricity bill, shifting the energy consumption from on-peak to off-peak hours. This paper develops a detailed storage model linking together technical, economic and electricity market parameters. The proposed operating strategy aims to maximize the profit of the storage owner (electricity customer) under simplifying assumptions, by determining the optimal charge/discharge schedule. The model can be applied to several kinds of storages, although the simulations refer to three kinds of batteries: lead-acid, lithium-ion (Li-ion) and sodium-sulfur (NaS) batteries. Unlike literature reviews, often requiring an estimate of the end-user load profile, the proposed operation strategy is able to properly identify the battery-charging schedule, relying only on the hourly price profile, regardless of the specific facility’s consumption, thanks to some simplifying assumptions in the sizing and the operation of the battery. This could be particularly useful when the customer load profile cannot be scheduled with sufficient reliability, because of the uncertainty inherent in load forecasting. The motivation behind this research is that storage devices can help to lower the average electricity prices, increasing flexibility and fostering the integration of renewable sources into the power system.

Suggested Citation

  • Enrico Telaretti & Mariano Ippolito & Luigi Dusonchet, 2015. "A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs," Energies, MDPI, vol. 9(1), pages 1-20, December.
  • Handle: RePEc:gam:jeners:v:9:y:2015:i:1:p:12-:d:61318
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/1/12/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/9/1/12/
    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. Shcherbakova, Anastasia & Kleit, Andrew & Cho, Joohyun, 2014. "The value of energy storage in South Korea’s electricity market: A Hotelling approach," Applied Energy, Elsevier, vol. 125(C), pages 93-102.
    3. Matallanas, E. & Castillo-Cagigal, M. & Gutiérrez, A. & Monasterio-Huelin, F. & Caamaño-Martín, E. & Masa, D. & Jiménez-Leube, J., 2012. "Neural network controller for Active Demand-Side Management with PV energy in the residential sector," Applied Energy, Elsevier, vol. 91(1), pages 90-97.
    4. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    5. Filippo Sgroi & Salvatore Tudisca & Anna Maria Di Trapani & Riccardo Testa & Riccardo Squatrito, 2014. "Efficacy and Efficiency of Italian Energy Policy: The Case of PV Systems in Greenhouse Farms," Energies, MDPI, vol. 7(6), pages 1-17, June.
    6. Eugenia Giannini & Antonia Moropoulou & Zacharias Maroulis & Glykeria Siouti, 2015. "Penetration of Photovoltaics in Greece," Energies, MDPI, vol. 8(7), pages 1-12, June.
    7. Severin Borenstein, 2005. "The Long-Run Efficiency of Real-Time Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 93-116.
    8. 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.
    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. Bordin, Chiara & Anuta, Harold Oghenetejiri & Crossland, Andrew & Gutierrez, Isabel Lascurain & Dent, Chris J. & Vigo, Daniele, 2017. "A linear programming approach for battery degradation analysis and optimization in offgrid power systems with solar energy integration," Renewable Energy, Elsevier, vol. 101(C), pages 417-430.
    2. Lucrezia Manservigi & Mattia Cattozzo & Pier Ruggero Spina & Mauro Venturini & Hilal Bahlawan, 2020. "Optimal Management of the Energy Flows of Interconnected Residential Users," Energies, MDPI, vol. 13(6), pages 1-21, March.
    3. Telaretti, E. & Graditi, G. & Ippolito, M.G. & Zizzo, G., 2016. "Economic feasibility of stationary electrochemical storages for electric bill management applications: The Italian scenario," Energy Policy, Elsevier, vol. 94(C), pages 126-137.
    4. Shabani, Masoume & Wallin, Fredrik & Dahlquist, Erik & Yan, Jinyue, 2023. "The impact of battery operating management strategies on life cycle cost assessment in real power market for a grid-connected residential battery application," Energy, Elsevier, vol. 270(C).
    5. Hong-Chao Gao & Joon-Ho Choi & Sang-Yun Yun & Hak-Ju Lee & Seon-Ju Ahn, 2018. "Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty," Energies, MDPI, vol. 11(6), pages 1-15, May.
    6. Dusonchet, L. & Favuzza, S. & Massaro, F. & Telaretti, E. & Zizzo, G., 2019. "Technological and legislative status point of stationary energy storages in the EU," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 158-167.

    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. Graditi, G. & Ippolito, M.G. & Telaretti, E. & Zizzo, G., 2016. "Technical and economical assessment of distributed electrochemical storages for load shifting applications: An Italian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 515-523.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Meinrenken, Christoph J. & Mehmani, Ali, 2019. "Concurrent optimization of thermal and electric storage in commercial buildings to reduce operating cost and demand peaks under time-of-use tariffs," Applied Energy, Elsevier, vol. 254(C).
    7. Ding, Jie & Xu, Yujie & Chen, Haisheng & Sun, Wenwen & Hu, Shan & Sun, Shuang, 2019. "Value and economic estimation model for grid-scale energy storage in monopoly power markets," Applied Energy, Elsevier, vol. 240(C), pages 986-1002.
    8. Dufo-López, Rodolfo, 2015. "Optimisation of size and control of grid-connected storage under real time electricity pricing conditions," Applied Energy, Elsevier, vol. 140(C), pages 395-408.
    9. Cho, Joohyun & Kleit, Andrew N., 2015. "Energy storage systems in energy and ancillary markets: A backwards induction approach," Applied Energy, Elsevier, vol. 147(C), pages 176-183.
    10. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    11. 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.
    12. Khan, Agha Salman M. & Verzijlbergh, Remco A. & Sakinci, Ozgur Can & De Vries, Laurens J., 2018. "How do demand response and electrical energy storage affect (the need for) a capacity market?," Applied Energy, Elsevier, vol. 214(C), pages 39-62.
    13. Jesús Muñoz-Cruzado-Alba & Christian A. Rojas & Samir Kouro & Eduardo Galván Díez, 2016. "Power Production Losses Study by Frequency Regulation in Weak-Grid-Connected Utility-Scale Photovoltaic Plants," Energies, MDPI, vol. 9(5), pages 1-21, April.
    14. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2015. "Smart households: Dispatch strategies and economic analysis of distributed energy storage for residential peak shaving," Applied Energy, Elsevier, vol. 147(C), pages 246-257.
    15. Colmenar-Santos, Antonio & Molina-Ibáñez, Enrique-Luis & Rosales-Asensio, Enrique & Blanes-Peiró, Jorge-Juan, 2018. "Legislative and economic aspects for the inclusion of energy reserve by a superconducting magnetic energy storage: Application to the case of the Spanish electrical system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2455-2470.
    16. Specht, Jan Martin & Madlener, Reinhard, 2023. "Quantifying value pools for distributed flexible energy assets," Energy, Elsevier, vol. 263(PB).
    17. Kraan, Oscar & Kramer, Gert Jan & Nikolic, Igor & Chappin, Emile & Koning, Vinzenz, 2019. "Why fully liberalised electricity markets will fail to meet deep decarbonisation targets even with strong carbon pricing," Energy Policy, Elsevier, vol. 131(C), pages 99-110.
    18. 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.
    19. Chen, Yang & Hu, Mengqi & Zhou, Zhi, 2017. "A data-driven analytical approach to enable optimal emerging technologies integration in the co-optimized electricity and ancillary service markets," Energy, Elsevier, vol. 122(C), pages 613-626.
    20. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.

    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:9:y:2015:i:1:p:12-:d:61318. 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.