IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v183y2021icp97-115.html
   My bibliography  Save this article

Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications

Author

Listed:
  • Ayuso, Pablo
  • Beltran, Hector
  • Segarra-Tamarit, Jorge
  • Pérez, Emilio

Abstract

This paper analyses the economic profitability provided by different types of Li-ion batteries when used in residential solar applications under a Model Predictive Control that optimizes the operation of the system. The control methodology takes profit of actually commercial time-of-use rates to minimize the operation costs. Also, the analysis takes into account the progressive degradation of the batteries involved by using state-of-the-art semi-empirical ageing models. The study is performed by means of annual simulations that use actual consumption curves for three different households and real PV production batteries, with extended lifetime warranties and prices below 600 €/kWh, under optimized operation and use even when only energy arbitrage and peak shaving services are considered.

Suggested Citation

  • Ayuso, Pablo & Beltran, Hector & Segarra-Tamarit, Jorge & Pérez, Emilio, 2021. "Optimized profitability of LFP and NMC Li-ion batteries in residential PV applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 183(C), pages 97-115.
  • Handle: RePEc:eee:matcom:v:183:y:2021:i:c:p:97-115
    DOI: 10.1016/j.matcom.2020.02.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475420300501
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2020.02.011?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. O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
    2. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    3. Darcovich, K. & Henquin, E.R. & Kenney, B. & Davidson, I.J. & Saldanha, N. & Beausoleil-Morrison, I., 2013. "Higher-capacity lithium ion battery chemistries for improved residential energy storage with micro-cogeneration," Applied Energy, Elsevier, vol. 111(C), pages 853-861.
    4. Pena-Bello, A. & Barbour, E. & Gonzalez, M.C. & Patel, M.K. & Parra, D., 2019. "Optimized PV-coupled battery systems for combining applications: Impact of battery technology and geography," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 978-990.
    5. Zhang, Chao & Wei, Yi-Li & Cao, Peng-Fei & Lin, Meng-Chang, 2018. "Energy storage system: Current studies on batteries and power condition system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3091-3106.
    6. 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.
    7. Berecibar, M. & Gandiaga, I. & Villarreal, I. & Omar, N. & Van Mierlo, J. & Van den Bossche, P., 2016. "Critical review of state of health estimation methods of Li-ion batteries for real applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 572-587.
    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. Nina Munzke & Felix Büchle & Anna Smith & Marc Hiller, 2021. "Influence of Efficiency, Aging and Charging Strategy on the Economic Viability and Dimensioning of Photovoltaic Home Storage Systems," Energies, MDPI, vol. 14(22), pages 1-46, November.
    2. Al-Wreikat, Yazan & Attfield, Emily Kate & Sodré, José Ricardo, 2022. "Model for payback time of using retired electric vehicle batteries in residential energy storage systems," Energy, Elsevier, vol. 259(C).
    3. Delagnes, T. & Henneron, T. & Clenet, S. & Fratila, M. & Ducreux, J.P., 2023. "Comparison of reduced basis construction methods for Model Order Reduction, with application to non-linear low frequency electromagnetics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 211(C), pages 470-488.
    4. Vasallo, Manuel Jesús & Cojocaru, Emilian Gelu & Gegúndez, Manuel Emilio & Marín, Diego, 2021. "Application of data-based solar field models to optimal generation scheduling in concentrating solar power plants," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1130-1149.

    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. Hector Beltran & Pablo Ayuso & Emilio Pérez, 2020. "Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage," Energies, MDPI, vol. 13(3), pages 1-18, January.
    2. Li, Dacheng & Guo, Songshan & He, Wei & King, Marcus & Wang, Jihong, 2021. "Combined capacity and operation optimisation of lithium-ion battery energy storage working with a combined heat and power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    3. Beuse, Martin & Dirksmeier, Mathias & Steffen, Bjarne & Schmidt, Tobias S., 2020. "Profitability of commercial and industrial photovoltaics and battery projects in South-East-Asia," Applied Energy, Elsevier, vol. 271(C).
    4. Yunlong Han & Conghui Li & Linfeng Zheng & Gang Lei & Li Li, 2023. "Remaining Useful Life Prediction of Lithium-Ion Batteries by Using a Denoising Transformer-Based Neural Network," Energies, MDPI, vol. 16(17), pages 1-16, August.
    5. Martin Henke & Getu Hailu, 2020. "Thermal Management of Stationary Battery Systems: A Literature Review," Energies, MDPI, vol. 13(16), pages 1-16, August.
    6. Gupta, Ruchi & Pena-Bello, Alejandro & Streicher, Kai Nino & Roduner, Cattia & Farhat, Yamshid & Thöni, David & Patel, Martin Kumar & Parra, David, 2021. "Spatial analysis of distribution grid capacity and costs to enable massive deployment of PV, electric mobility and electric heating," Applied Energy, Elsevier, vol. 287(C).
    7. 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).
    8. Lucas Deotti & Wanessa Guedes & Bruno Dias & Tiago Soares, 2020. "Technical and Economic Analysis of Battery Storage for Residential Solar Photovoltaic Systems in the Brazilian Regulatory Context," Energies, MDPI, vol. 13(24), pages 1-30, December.
    9. Shaw-Williams, Damian & Susilawati, Connie, 2020. "A techno-economic evaluation of Virtual Net Metering for the Australian community housing sector," Applied Energy, Elsevier, vol. 261(C).
    10. Arsalis, Alexandros & Papanastasiou, Panos & Georghiou, George E., 2022. "A comparative review of lithium-ion battery and regenerative hydrogen fuel cell technologies for integration with photovoltaic applications," Renewable Energy, Elsevier, vol. 191(C), pages 943-960.
    11. Olabi, A.G. & Wilberforce, Tabbi & Sayed, Enas Taha & Abo-Khalil, Ahmed G. & Maghrabie, Hussein M. & Elsaid, Khaled & Abdelkareem, Mohammad Ali, 2022. "Battery energy storage systems and SWOT (strengths, weakness, opportunities, and threats) analysis of batteries in power transmission," Energy, Elsevier, vol. 254(PA).
    12. Damian Shaw-Williams & Connie Susilawati & Geoffrey Walker, 2018. "Value of Residential Investment in Photovoltaics and Batteries in Networks: A Techno-Economic Analysis," Energies, MDPI, vol. 11(4), pages 1-25, April.
    13. Parra, David & Mauger, Romain, 2022. "A new dawn for energy storage: An interdisciplinary legal and techno-economic analysis of the new EU legal framework," Energy Policy, Elsevier, vol. 171(C).
    14. 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.
    15. 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.
    16. Dong, Siyuan & Kremers, Enrique & Brucoli, Maria & Rothman, Rachael & Brown, Solomon, 2020. "Improving the feasibility of household and community energy storage: A techno-enviro-economic study for the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    17. Hector Beltran & Sam Harrison & Agustí Egea-Àlvarez & Lie Xu, 2020. "Techno-Economic Assessment of Energy Storage Technologies for Inertia Response and Frequency Support from Wind Farms," Energies, MDPI, vol. 13(13), pages 1-21, July.
    18. Schram, Wouter L. & Lampropoulos, Ioannis & van Sark, Wilfried G.J.H.M., 2018. "Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential," Applied Energy, Elsevier, vol. 223(C), pages 69-81.
    19. Thiemo Fetzer & Samuel Marden, 2017. "Take What You Can: Property Rights, Contestability and Conflict," Economic Journal, Royal Economic Society, vol. 0(601), pages 757-783, May.
    20. Daniel Agness & Travis Baseler & Sylvain Chassang & Pascaline Dupas & Erik Snowberg, 2022. "Valuing the Time of the Self-Employed," Working Papers 2022-2, Princeton University. Economics Department..

    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:matcom:v:183:y:2021:i:c:p:97-115. 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.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.