IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p4038-d394470.html
   My bibliography  Save this article

How Does the Electricity Demand Profile Impact the Attractiveness of PV-Coupled Battery Systems Combining Applications?

Author

Listed:
  • Alejandro Pena-Bello

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva, Boulevard Carl-Vogt 66, 1205 Genève, Switzerland)

  • Edward Barbour

    (Centre for Renewable Energy Systems Technology, Loughborough University, Loughborough LE11 3TU, UK)

  • Marta C. Gonzalez

    (Department of City and Regional Planning, UC Berkeley, 406 Wurster Hall, Berkeley, CA 94720, USA
    Lawrence Berkeley National Laboratory, Cyclotron Road, Berkeley, CA 94720, USA
    Department of Civil and Environmental Engineering and Engineering Systems, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 1-290, Cambridge, MA 02139, USA)

  • Selin Yilmaz

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva, Boulevard Carl-Vogt 66, 1205 Genève, Switzerland)

  • Martin K. Patel

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva, Boulevard Carl-Vogt 66, 1205 Genève, Switzerland)

  • David Parra

    (Energy Efficiency Group, Institute for Environmental Sciences and Forel Institute, University of Geneva, Boulevard Carl-Vogt 66, 1205 Genève, Switzerland)

Abstract

Energy storage is a key solution to supply renewable electricity on demand and in particular batteries are becoming attractive for consumers who install PV panels. In order to minimize their electricity bill and keep the grid stable, batteries can combine applications. The daily match between PV supply and the electricity load profile is often considered as a determinant for the attractiveness of residential PV-coupled battery systems, however, the previous literature has so far mainly focused on the annual energy balance. In this paper, we analyze the techno-economic impact of adding a battery system to a new PV system that would otherwise be installed on its own, for different residential electricity load profiles in Geneva (Switzerland) and Austin (U.S.) using lithium-ion batteries performing various consumer applications, namely PV self-consumption, demand load-shifting, avoidance of PV curtailment, and demand peak shaving, individually and jointly. We employ clustering of the household’s load profile (with 15-minute resolution) for households with low, medium, and high annual electricity consumption in the two locations using a 1:1:1 sizing ratio. Our results show that with this simple sizing rule-of-thumb, the shape of the load profile has a small impact on the net present value of batteries. Overall, our analysis suggests that the effect of the load profile is small and differs across locations, whereas the combination of applications significantly increases profitability while marginally decreasing the share of self-consumption. Moreover, without the combination of applications, batteries are far from being economically viable.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:4038-:d:394470
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/4038/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/4038/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yilmaz, S. & Chambers, J. & Patel, M.K., 2019. "Comparison of clustering approaches for domestic electricity load profile characterisation - Implications for demand side management," Energy, Elsevier, vol. 180(C), pages 665-677.
    2. Ratnam, Elizabeth L. & Weller, Steven R. & Kellett, Christopher M., 2015. "An optimization-based approach to scheduling residential battery storage with solar PV: Assessing customer benefit," Renewable Energy, Elsevier, vol. 75(C), pages 123-134.
    3. 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.
    4. Litjens, G.B.M.A. & Worrell, E. & van Sark, W.G.J.H.M., 2018. "Assessment of forecasting methods on performance of photovoltaic-battery systems," Applied Energy, Elsevier, vol. 221(C), pages 358-373.
    5. Kavlak, Goksin & McNerney, James & Trancik, Jessika E., 2018. "Evaluating the causes of cost reduction in photovoltaic modules," Energy Policy, Elsevier, vol. 123(C), pages 700-710.
    6. 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.
    7. Al-Wakeel, Ali & Wu, Jianzhong & Jenkins, Nick, 2017. "k-means based load estimation of domestic smart meter measurements," Applied Energy, Elsevier, vol. 194(C), pages 333-342.
    8. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    9. Parra, David & Patel, Martin K., 2019. "The nature of combining energy storage applications for residential battery technology," Applied Energy, Elsevier, vol. 239(C), pages 1343-1355.
    10. Parra, David & Norman, Stuart A. & Walker, Gavin S. & Gillott, Mark, 2016. "Optimum community energy storage system for demand load shifting," Applied Energy, Elsevier, vol. 174(C), pages 130-143.
    11. Alexander Tureczek & Per Sieverts Nielsen & Henrik Madsen, 2018. "Electricity Consumption Clustering Using Smart Meter Data," Energies, MDPI, vol. 11(4), pages 1-18, April.
    12. 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.
    13. William E. Hart & Carl Laird & Jean-Paul Watson & David L. Woodruff, 2012. "Pyomo – Optimization Modeling in Python," Springer Optimization and Its Applications, Springer, edition 127, number 978-1-4614-3226-5, September.
    14. 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.
    15. 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.
    16. 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.
    17. Luthander, Rasmus & Widén, Joakim & Munkhammar, Joakim & Lingfors, David, 2016. "Self-consumption enhancement and peak shaving of residential photovoltaics using storage and curtailment," Energy, Elsevier, vol. 112(C), pages 221-231.
    18. 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.
    19. Barbour, Edward & González, Marta C., 2018. "Projecting battery adoption in the prosumer era," Applied Energy, Elsevier, vol. 215(C), pages 356-370.
    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. Shahin Bayramov & Iurii Prokazov & Sergey Kondrashev & Jan Kowalik, 2021. "Household Electricity Generation as a Way of Energy Independence of States—Social Context of Energy Management," Energies, MDPI, vol. 14(12), pages 1-19, June.
    3. Alfredo Nespoli & Andrea Matteri & Silvia Pretto & Luca De Ciechi & Emanuele Ogliari, 2021. "Battery Sizing for Different Loads and RES Production Scenarios through Unsupervised Clustering Methods," Forecasting, MDPI, vol. 3(4), pages 1-19, September.
    4. Olivella, Jordi & Domenech, Bruno & Calleja, Gema, 2021. "Potential of implementation of residential photovoltaics at city level: The case of London," Renewable Energy, Elsevier, vol. 180(C), pages 577-585.
    5. Seong Won Moon & Tong Seop Kim, 2020. "Advanced Gas Turbine Control Logic Using Black Box Models for Enhancing Operational Flexibility and Stability," Energies, MDPI, vol. 13(21), pages 1-23, October.

    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. 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.
    2. Mulleriyawage, U.G.K. & Shen, W.X., 2020. "Optimally sizing of battery energy storage capacity by operational optimization of residential PV-Battery systems: An Australian household case study," Renewable Energy, Elsevier, vol. 160(C), pages 852-864.
    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. 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).
    5. Mulleriyawage, U.G.K. & Shen, W.X., 2021. "Impact of demand side management on optimal sizing of residential battery energy storage system," Renewable Energy, Elsevier, vol. 172(C), pages 1250-1266.
    6. 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.
    7. Roberts, Mike B. & Bruce, Anna & MacGill, Iain, 2019. "Impact of shared battery energy storage systems on photovoltaic self-consumption and electricity bills in apartment buildings," Applied Energy, Elsevier, vol. 245(C), pages 78-95.
    8. Kalkbrenner, Bernhard J., 2019. "Residential vs. community battery storage systems – Consumer preferences in Germany," Energy Policy, Elsevier, vol. 129(C), pages 1355-1363.
    9. Aniello, Gianmarco & Shamon, Hawal & Kuckshinrichs, Wilhelm, 2021. "Micro-economic assessment of residential PV and battery systems: The underrated role of financial and fiscal aspects," Applied Energy, Elsevier, vol. 281(C).
    10. Aniello, Gianmarco & Bertsch, Valentin, 2023. "Shaping the energy transition in the residential sector: Regulatory incentives for aligning household and system perspectives," Applied Energy, Elsevier, vol. 333(C).
    11. 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.
    12. 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.
    13. DiOrio, Nicholas & Denholm, Paul & Hobbs, William B., 2020. "A model for evaluating the configuration and dispatch of PV plus battery power plants," Applied Energy, Elsevier, vol. 262(C).
    14. Freitas Gomes, Icaro Silvestre & Perez, Yannick & Suomalainen, Emilia, 2020. "Coupling small batteries and PV generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    15. Say, Kelvin & John, Michele & Dargaville, Roger, 2019. "Power to the people: Evolutionary market pressures from residential PV battery investments in Australia," Energy Policy, Elsevier, vol. 134(C).
    16. de Souza Dutra, Michael David & da Conceição Júnior, Gerson & de Paula Ferreira, William & Campos Chaves, Matheus Roberto, 2020. "A customized transition towards smart homes: A fast framework for economic analyses," Applied Energy, Elsevier, vol. 262(C).
    17. 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).
    18. Ma, Tao & Zhang, Yijie & Gu, Wenbo & Xiao, Gang & Yang, Hongxing & Wang, Shuxiao, 2022. "Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system," Renewable Energy, Elsevier, vol. 197(C), pages 1049-1060.
    19. Bruno Domenech & Gema Calleja & Jordi Olivella, 2021. "Residential Photovoltaic Profitability with Storage under the New Spanish Regulation: A Multi-Scenario Analysis," Energies, MDPI, vol. 14(7), pages 1-17, April.
    20. 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.

    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:13:y:2020:i:15:p:4038-:d:394470. 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.