IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v353y2024ipas0306261923013405.html
   My bibliography  Save this article

Convex optimization of PV-battery system sizing and operation with non-linear loss models

Author

Listed:
  • Despeghel, Jolien
  • Tant, Jeroen
  • Driesen, Johan

Abstract

To mitigate climate change, households are increasingly incentivized to install PV systems in combination with battery energy storage systems to increase their self-sufficiency and flexibility as well as to relieve the stress caused by the high penetration of distributed generation on the grid. This paper aims to assess the need for non-linear loss models as opposed to linear loss models found in the literature when optimizing the sizing and operation of PV-battery systems. Therefore, an optimization model is presented which implements non-linear, convex and linear converter and battery loss model formulations. The relaxed convex formulation is equivalent to the original non-linear formulation and can be solved more efficiently, decreasing the run time by a factor of 4. The impact of non-linear as opposed to linear loss models on the optimal solution is illustrated for a residential DC-coupled PV-battery system. The linear loss model is shown to result in an underestimation of the cost by 14.7% and the battery size by 12.4%. Further, the battery utilization is underestimated by a third. The proposed method is useful to accurately model the losses when optimizing the sizing and operation of a PV-battery system in exchange for a slightly higher computational time compared to linear loss models, though far below that of solving the non-relaxed non-linear problem.

Suggested Citation

  • Despeghel, Jolien & Tant, Jeroen & Driesen, Johan, 2024. "Convex optimization of PV-battery system sizing and operation with non-linear loss models," Applied Energy, Elsevier, vol. 353(PA).
  • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s0306261923013405
    DOI: 10.1016/j.apenergy.2023.121976
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923013405
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.121976?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. 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.
    2. Moshövel, Janina & Kairies, Kai-Philipp & Magnor, Dirk & Leuthold, Matthias & Bost, Mark & Gährs, Swantje & Szczechowicz, Eva & Cramer, Moritz & Sauer, Dirk Uwe, 2015. "Analysis of the maximal possible grid relief from PV-peak-power impacts by using storage systems for increased self-consumption," Applied Energy, Elsevier, vol. 137(C), pages 567-575.
    3. Brusco, Giovanni & Burgio, Alessandro & Menniti, Daniele & Pinnarelli, Anna & Sorrentino, Nicola, 2016. "The economic viability of a feed-in tariff scheme that solely rewards self-consumption to promote the use of integrated photovoltaic battery systems," Applied Energy, Elsevier, vol. 183(C), pages 1075-1085.
    4. Wu, Xiaohua & Hu, Xiaosong & Yin, Xiaofeng & Zhang, Caiping & Qian, Shide, 2017. "Optimal battery sizing of smart home via convex programming," Energy, Elsevier, vol. 140(P1), pages 444-453.
    5. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2016. "Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems," Applied Energy, Elsevier, vol. 173(C), pages 331-342.
    6. Ranaweera, Iromi & Midtgård, Ole-Morten, 2016. "Optimization of operational cost for a grid-supporting PV system with battery storage," Renewable Energy, Elsevier, vol. 88(C), pages 262-272.
    7. Mousavi G., S.M. & Nikdel, M., 2014. "Various battery models for various simulation studies and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 477-485.
    8. Holger C. Hesse & Rodrigo Martins & Petr Musilek & Maik Naumann & Cong Nam Truong & Andreas Jossen, 2017. "Economic Optimization of Component Sizing for Residential Battery Storage Systems," Energies, MDPI, vol. 10(7), pages 1-19, June.
    9. Linssen, Jochen & Stenzel, Peter & Fleer, Johannes, 2017. "Techno-economic analysis of photovoltaic battery systems and the influence of different consumer load profiles," Applied Energy, Elsevier, vol. 185(P2), pages 2019-2025.
    10. Quoilin, Sylvain & Kavvadias, Konstantinos & Mercier, Arnaud & Pappone, Irene & Zucker, Andreas, 2016. "Quantifying self-consumption linked to solar home battery systems: Statistical analysis and economic assessment," Applied Energy, Elsevier, vol. 182(C), pages 58-67.
    11. de Oliveira e Silva, Guilherme & Hendrick, Patrick, 2017. "Photovoltaic self-sufficiency of Belgian households using lithium-ion batteries, and its impact on the grid," Applied Energy, Elsevier, vol. 195(C), pages 786-799.
    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. Azuatalam, Donald & Paridari, Kaveh & Ma, Yiju & Förstl, Markus & Chapman, Archie C. & Verbič, Gregor, 2019. "Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 555-570.
    2. Li, Yanxue & Gao, Weijun & Ruan, Yingjun, 2018. "Performance investigation of grid-connected residential PV-battery system focusing on enhancing self-consumption and peak shaving in Kyushu, Japan," Renewable Energy, Elsevier, vol. 127(C), pages 514-523.
    3. von Appen, J. & Braun, M., 2018. "Interdependencies between self-sufficiency preferences, techno-economic drivers for investment decisions and grid integration of residential PV storage systems," Applied Energy, Elsevier, vol. 229(C), pages 1140-1151.
    4. von Appen, J. & Braun, M., 2018. "Strategic decision making of distribution network operators and investors in residential photovoltaic battery storage systems," Applied Energy, Elsevier, vol. 230(C), pages 540-550.
    5. Luthander, Rasmus & Nilsson, Annica M. & Widén, Joakim & Åberg, Magnus, 2019. "Graphical analysis of photovoltaic generation and load matching in buildings: A novel way of studying self-consumption and self-sufficiency," Applied Energy, Elsevier, vol. 250(C), pages 748-759.
    6. 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.
    7. Hirschburger, Rafael & Weidlich, Anke, 2020. "Profitability of photovoltaic and battery systems on municipal buildings," Renewable Energy, Elsevier, vol. 153(C), pages 1163-1173.
    8. Koskela, Juha & Rautiainen, Antti & Järventausta, Pertti, 2019. "Using electrical energy storage in residential buildings – Sizing of battery and photovoltaic panels based on electricity cost optimization," Applied Energy, Elsevier, vol. 239(C), pages 1175-1189.
    9. 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.
    10. O'Shaughnessy, Eric & Cutler, Dylan & Ardani, Kristen & Margolis, Robert, 2018. "Solar plus: A review of the end-user economics of solar PV integration with storage and load control in residential buildings," Applied Energy, Elsevier, vol. 228(C), pages 2165-2175.
    11. Rômulo de Oliveira Azevêdo & Paulo Rotela Junior & Luiz Célio Souza Rocha & Gianfranco Chicco & Giancarlo Aquila & Rogério Santana Peruchi, 2020. "Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments," Sustainability, MDPI, vol. 12(17), pages 1-40, September.
    12. Villa-Arrieta, Manuel & Sumper, Andreas, 2019. "Economic evaluation of Nearly Zero Energy Cities," Applied Energy, Elsevier, vol. 237(C), pages 404-416.
    13. Francesca Andreolli & Chiara D'Alpaos & Peter Kort, 2023. "Does P2P Trading Favor Investments in PV-Battery Systems?," Working Papers 2023.02, Fondazione Eni Enrico Mattei.
    14. Chatzisideris, Marios D. & Ohms, Pernille K. & Espinosa, Nieves & Krebs, Frederik C. & Laurent, Alexis, 2019. "Economic and environmental performances of organic photovoltaics with battery storage for residential self-consumption," Applied Energy, Elsevier, vol. 256(C).
    15. Tang, Rui & Yildiz, Baran & Leong, Philip H.W. & Vassallo, Anthony & Dore, Jonathon, 2019. "Residential battery sizing model using net meter energy data clustering," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Tervo, Eric & Agbim, Kenechi & DeAngelis, Freddy & Hernandez, Jeffrey & Kim, Hye Kyung & Odukomaiya, Adewale, 2018. "An economic analysis of residential photovoltaic systems with lithium ion battery storage in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1057-1066.
    17. Alejandro Pena-Bello & Edward Barbour & Marta C. Gonzalez & Selin Yilmaz & Martin K. Patel & David Parra, 2020. "How Does the Electricity Demand Profile Impact the Attractiveness of PV-Coupled Battery Systems Combining Applications?," Energies, MDPI, vol. 13(15), pages 1-19, August.
    18. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    19. Gopinath Subramani & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg & Josep M. Guerrero, 2017. "Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving," Energies, MDPI, vol. 10(11), pages 1-17, November.
    20. Marion R. Dam & Marten D. van der Laan, 2024. "Techno-Economic Assessment of Battery Systems for PV-Equipped Households with Dynamic Contracts: A Case Study of The Netherlands," Energies, MDPI, vol. 17(12), pages 1-24, June.

    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:appene:v:353:y:2024:i:pa:s0306261923013405. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.