IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v38y2010i7p3731-3743.html
   My bibliography  Save this article

Projected costs of a grid-connected domestic PV system under different scenarios in Ireland, using measured data from a trial installation

Author

Listed:
  • Ayompe, L.M.
  • Duffy, A.
  • McCormack, S.J.
  • Conlon, M.

Abstract

This paper presents results of a study of projected costs for a grid-connected PV system for domestic application in Ireland. The study is based on results from a 1.72 kWp PV system installed on a flat rooftop in Dublin, Ireland. During its first year of operation a total of 885.1 kWh/kWp of electricity was generated with a performance ratio of 81.5%. The scenarios employed in this study consider: a range of capital costs; cost dynamics based on a PV module learning rate of 20±5%; projections for global annual installed PV capacity under an advanced and moderate market growth conditions; domestic electricity cost growth of 4.5% based on historic data; and a reduction of 25% or 50% in the CO2 intensity of national electricity production by 2055. These scenarios are used to predict when system life cycle production costs fall to grid prices (grid parity). Average NPV and electricity generation costs ranged from -[euro]14,330 and 0.58 [euro]/kWh and were close to zero and 0.18 [euro]/kWh for a system installed in 2009 and 2030, respectively. However, under optimistic conditions NPVs are positive for systems installed after 2021 and grid parity occurs in 2016. Findings are compared with similar international studies.

Suggested Citation

  • Ayompe, L.M. & Duffy, A. & McCormack, S.J. & Conlon, M., 2010. "Projected costs of a grid-connected domestic PV system under different scenarios in Ireland, using measured data from a trial installation," Energy Policy, Elsevier, vol. 38(7), pages 3731-3743, July.
    • Handle: RePEc:eee:enepol:v:38:y:2010:i:7:p:3731-3743
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(10)00155-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    2. Shum, Kwok L. & Watanabe, Chihiro, 2008. "Towards a local learning (innovation) model of solar photovoltaic deployment," Energy Policy, Elsevier, vol. 36(2), pages 508-521, February.
    3. Ferioli, F. & Schoots, K. & van der Zwaan, B.C.C., 2009. "Use and limitations of learning curves for energy technology policy: A component-learning hypothesis," Energy Policy, Elsevier, vol. 37(7), pages 2525-2535, July.
    4. Ren, Hongbo & Gao, Weijun & Ruan, Yingjun, 2009. "Economic optimization and sensitivity analysis of photovoltaic system in residential buildings," Renewable Energy, Elsevier, vol. 34(3), pages 883-889.
    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. Yuan, Jiahai & Sun, Shenghui & Zhang, Wenhua & Xiong, Minpeng, 2014. "The economy of distributed PV in China," Energy, Elsevier, vol. 78(C), pages 939-949.
    2. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    3. Zou, Hongyang & Du, Huibin & Brown, Marilyn A. & Mao, Guozhu, 2017. "Large-scale PV power generation in China: A grid parity and techno-economic analysis," Energy, Elsevier, vol. 134(C), pages 256-268.
    4. Hernández-Moro, J. & Martínez-Duart, J.M., 2013. "Analytical model for solar PV and CSP electricity costs: Present LCOE values and their future evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 119-132.
    5. Patricia Milanés-Montero & Alberto Arroyo-Farrona & Esteban Pérez-Calderón, 2018. "Assessment of the Influence of Feed-In Tariffs on the Profitability of European Photovoltaic Companies," Sustainability, MDPI, vol. 10(10), pages 1-16, September.
    6. Breyer, Christian & Koskinen, Otto & Blechinger, Philipp, 2015. "Profitable climate change mitigation: The case of greenhouse gas emission reduction benefits enabled by solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 610-628.
    7. Stevanović, Sanja & Pucar, Mila, 2012. "Investment appraisal of a small, grid-connected photovoltaic plant under the Serbian feed-in tariff framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1673-1682.
    8. dos Santos, L.L.C. & Canha, L.N. & Bernardon, D.P., 2018. "Projection of the diffusion of photovoltaic systems in residential low voltage consumers," Renewable Energy, Elsevier, vol. 116(PA), pages 384-401.
    9. Jägemann, Cosima & Hagspiel, Simeon & Lindenberger, Dietmar, 2013. "The Economic Inefficiency of Grid Parity: The Case of German Photovoltaics," EWI Working Papers 2013-19, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).

    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. Hernández-Moro, J. & Martínez-Duart, J.M., 2013. "Analytical model for solar PV and CSP electricity costs: Present LCOE values and their future evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 119-132.
    2. Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
    3. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    4. Strupeit, Lars & Neij, Lena, 2017. "Cost dynamics in the deployment of photovoltaics: Insights from the German market for building-sited systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 948-960.
    5. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    6. Yao, Xilong & Liu, Yang & Qu, Shiyou, 2015. "When will wind energy achieve grid parity in China? – Connecting technological learning and climate finance," Applied Energy, Elsevier, vol. 160(C), pages 697-704.
    7. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
    8. Samantha DeMartino, David Le Blanc, 2010. "Estimating the Amount of a Global Feed-in Tariff for Renewable Electricity," Working Papers 95, United Nations, Department of Economics and Social Affairs.
    9. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    10. Odam, Neil & de Vries, Frans P., 2020. "Innovation modelling and multi-factor learning in wind energy technology," Energy Economics, Elsevier, vol. 85(C).
    11. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    12. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    13. Beliën, Jeroen & De Boeck, Liesje & Colpaert, Jan & Cooman, Gert, 2013. "The best time to invest in photovoltaic panels in Flanders," Renewable Energy, Elsevier, vol. 50(C), pages 348-358.
    14. Nicodemus, Julia Haltiwanger, 2018. "Technological learning and the future of solar H2: A component learning comparison of solar thermochemical cycles and electrolysis with solar PV," Energy Policy, Elsevier, vol. 120(C), pages 100-109.
    15. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    16. Gernaat, David E.H.J. & de Boer, Harmen-Sytze & Dammeier, Louise C. & van Vuuren, Detlef P., 2020. "The role of residential rooftop photovoltaic in long-term energy and climate scenarios," Applied Energy, Elsevier, vol. 279(C).
    17. Audrey Laude & Christian Jonen, 2011. "Biomass and CCS: The influence of the learning effect," Working Papers halshs-00829779, HAL.
    18. Laude, Audrey & Jonen, Christian, 2013. "Biomass and CCS: The influence of technical change," Energy Policy, Elsevier, vol. 60(C), pages 916-924.
    19. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
    20. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.

    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:enepol:v:38:y:2010:i:7:p:3731-3743. 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/locate/enpol .

    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.