IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v40y2012i1p80-89.html
   My bibliography  Save this article

A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns

Author

Listed:
  • Dalton, G.J.
  • Alcorn, R.
  • Lewis, T.

Abstract

This paper is a case study which examines the finances of a proposed installation schedule of 500MW of a wave energy device type in Ireland. The novel aspects of the analysis were the modelling of the combined influence of learning curves, supply and demand rates as well as future cost of cash on the phased deployment over the 10 years. There are many studies which have examined the economics of renewable energy project installations, including wave energy. However, there is lack of research in the impact and implications of phased installations over time, especially when using a feed-in tariff (FIT) revenue mechanism. The goal of the study was twofold. The first goal was to assess the viability of the current Irish feed-in tariff within the context of a phased installation program for the wave energy device chosen for the study, and measures required to produce a positive rate of return. The second aim was to assess the impact of learning curve, supply/demand curves and future cost of cash on phased project installations. The wave energy device chosen for the study was the Pelamis P1 and the economic model used was NAVITAS, created by HMRC. The assessment was based on net present value and internal rate of return. The wave energy data for the study was 2007 from M4 of the west coast of Ireland, obtained from Marine Institute, Ireland. Results from the case study indicated that the high initial costs for the case study wave energy device had a significant impact on financial returns. Results of the case study indicate that higher tariffs may be required than the current Irish, static, nonindex linked, FIT to foster positive returns for future wave energy projects, especially if phased installations are considered, which are susceptible to future cash and supply/demand factors. The large range of sensitivity factors assessed in the case study demonstrates the vulnerable nature of these large scale projects when estimating financial returns. Further studies will be required to assess multiple device types, update initial costs for wave energy devices, provide reliable power matrices, as well as appropriate learning curve and supply demand rates.

Suggested Citation

  • Dalton, G.J. & Alcorn, R. & Lewis, T., 2012. "A 10 year installation program for wave energy in Ireland: A case study sensitivity analysis on financial returns," Renewable Energy, Elsevier, vol. 40(1), pages 80-89.
    • Handle: RePEc:eee:renene:v:40:y:2012:i:1:p:80-89
    DOI: 10.1016/j.renene.2011.09.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014811100543X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2011.09.025?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. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    2. Snyder, Brian & Kaiser, Mark J., 2009. "Ecological and economic cost-benefit analysis of offshore wind energy," Renewable Energy, Elsevier, vol. 34(6), pages 1567-1578.
    3. Dalton, G.J. & Alcorn, R. & Lewis, T., 2010. "Case study feasibility analysis of the Pelamis wave energy convertor in Ireland, Portugal and North America," Renewable Energy, Elsevier, vol. 35(2), pages 443-455.
    4. Dunnett, David & Wallace, James S., 2009. "Electricity generation from wave power in Canada," Renewable Energy, Elsevier, vol. 34(1), pages 179-195.
    5. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    6. Neij, L, 1999. "Cost dynamics of wind power," Energy, Elsevier, vol. 24(5), pages 375-389.
    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. Thies, Philipp R. & Johanning, Lars & Harnois, Violette & Smith, Helen C.M. & Parish, David N., 2014. "Mooring line fatigue damage evaluation for floating marine energy converters: Field measurements and prediction," Renewable Energy, Elsevier, vol. 63(C), pages 133-144.
    2. Farrell, Niall & Donoghue, Cathal O’ & Morrissey, Karyn, 2015. "Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: An Irish case study," Energy Policy, Elsevier, vol. 78(C), pages 62-77.
    3. Pablo Ruiz-Minguela & Donald R. Noble & Vincenzo Nava & Shona Pennock & Jesus M. Blanco & Henry Jeffrey, 2022. "Estimating Future Costs of Emerging Wave Energy Technologies," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    4. Astariz, S. & Iglesias, G., 2015. "The economics of wave energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 397-408.
    5. Xu, Xinxin & Robertson, Bryson & Buckham, Bradley, 2020. "A techno-economic approach to wave energy resource assessment and development site identification," Applied Energy, Elsevier, vol. 260(C).
    6. Astariz, S. & Iglesias, G., 2016. "Output power smoothing and reduced downtime period by combined wind and wave energy farms," Energy, Elsevier, vol. 97(C), pages 69-81.
    7. Portillo, J.C.C. & Reis, P.F. & Henriques, J.C.C. & Gato, L.M.C. & Falcão, A.F.O., 2019. "Backward bent-duct buoy or frontward bent-duct buoy? Review, assessment and optimisation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 353-368.
    8. Guanche, R. & de Andrés, A.D. & Simal, P.D. & Vidal, C. & Losada, I.J., 2014. "Uncertainty analysis of wave energy farms financial indicators," Renewable Energy, Elsevier, vol. 68(C), pages 570-580.
    9. Sierra, J.P. & González-Marco, D. & Sospedra, J. & Gironella, X. & Mösso, C. & Sánchez-Arcilla, A., 2013. "Wave energy resource assessment in Lanzarote (Spain)," Renewable Energy, Elsevier, vol. 55(C), pages 480-489.
    10. Pasquale Contestabile & Enrico Di Lauro & Mariano Buccino & Diego Vicinanza, 2016. "Economic Assessment of Overtopping BReakwater for Energy Conversion (OBREC): A Case Study in Western Australia," Sustainability, MDPI, vol. 9(1), pages 1-28, December.
    11. Astariz, S. & Iglesias, G., 2017. "The collocation feasibility index – A method for selecting sites for co-located wave and wind farms," Renewable Energy, Elsevier, vol. 103(C), pages 811-824.
    12. Liu, Cengceng & Li, Nan & Zha, Donglan, 2016. "On the impact of FIT policies on renewable energy investment: Based on the solar power support policies in China's power market," Renewable Energy, Elsevier, vol. 94(C), pages 251-267.
    13. Choupin, Ophelie & Henriksen, Michael & Tomlinson, Rodger, 2022. "Interrelationship between variables for wave direction-dependent WEC/site-configuration pairs using the CapEx method," Energy, Elsevier, vol. 248(C).
    14. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    15. Tunde Aderinto & Hua Li, 2019. "Review on Power Performance and Efficiency of Wave Energy Converters," Energies, MDPI, vol. 12(22), pages 1-24, November.
    16. Astariz, S. & Perez-Collazo, C. & Abanades, J. & Iglesias, G., 2015. "Co-located wave-wind farms: Economic assessment as a function of layout," Renewable Energy, Elsevier, vol. 83(C), pages 837-849.
    17. Sharay Astariz & Gregorio Iglesias, 2015. "Enhancing Wave Energy Competitiveness through Co-Located Wind and Wave Energy Farms. A Review on the Shadow Effect," Energies, MDPI, vol. 8(7), pages 1-23, July.
    18. Dalton, Gordon & Allan, Grant & Beaumont, Nicola & Georgakaki, Aliki & Hacking, Nick & Hooper, Tara & Kerr, Sandy & O’Hagan, Anne Marie & Reilly, Kieran & Ricci, Pierpaolo & Sheng, Wanan & Stallard, T, 2015. "Economic and socio-economic assessment methods for ocean renewable energy: Public and private perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 850-878.
    19. Aoun, N.S. & Harajli, H.A. & Queffeulou, P., 2013. "Preliminary appraisal of wave power prospects in Lebanon," Renewable Energy, Elsevier, vol. 53(C), pages 165-173.
    20. Astariz, S. & Perez-Collazo, C. & Abanades, J. & Iglesias, G., 2015. "Towards the optimal design of a co-located wind-wave farm," Energy, Elsevier, vol. 84(C), pages 15-24.
    21. Ophelie Choupin & Michael Henriksen & Amir Etemad-Shahidi & Rodger Tomlinson, 2021. "Breaking-Down and Parameterising Wave Energy Converter Costs Using the CapEx and Similitude Methods," Energies, MDPI, vol. 14(4), pages 1-27, February.
    22. Foley, A.M. & Ó Gallachóir, B.P. & McKeogh, E.J. & Milborrow, D. & Leahy, P.G., 2013. "Addressing the technical and market challenges to high wind power integration in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 692-703.
    23. Niall Farrell & Cathal O'Donoghue & Karyn Morrissey, 2020. "Regional income and wave energy deployment in Ireland," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 509-531, June.

    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. Astariz, S. & Iglesias, G., 2015. "The economics of wave energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 397-408.
    2. Dalton, Gordon & Allan, Grant & Beaumont, Nicola & Georgakaki, Aliki & Hacking, Nick & Hooper, Tara & Kerr, Sandy & O’Hagan, Anne Marie & Reilly, Kieran & Ricci, Pierpaolo & Sheng, Wanan & Stallard, T, 2015. "Economic and socio-economic assessment methods for ocean renewable energy: Public and private perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 850-878.
    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. Kumbaroglu, Gürkan & Madlener, Reinhard & Demirel, Mustafa, 2008. "A real options evaluation model for the diffusion prospects of new renewable power generation technologies," Energy Economics, Elsevier, vol. 30(4), pages 1882-1908, July.
    5. Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.
    6. Allan, Grant & Gilmartin, Michelle & McGregor, Peter & Swales, Kim, 2011. "Levelised costs of Wave and Tidal energy in the UK: Cost competitiveness and the importance of "banded" Renewables Obligation Certificates," Energy Policy, Elsevier, vol. 39(1), pages 23-39, January.
    7. Kahouli-Brahmi, Sondes, 2009. "Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach," Ecological Economics, Elsevier, vol. 68(4), pages 1195-1212, February.
    8. Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
    9. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    10. Kahouli, Sondès, 2011. "Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling," Energy Economics, Elsevier, vol. 33(5), pages 840-852, September.
    11. Reichenbach, Johanna & Requate, Till, 2012. "Subsidies for renewable energies in the presence of learning effects and market power," Resource and Energy Economics, Elsevier, vol. 34(2), pages 236-254.
    12. Clas‐Otto Wene, 2016. "Future energy system development depends on past learning opportunities," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(1), pages 16-32, January.
    13. Farrell, Niall & Donoghue, Cathal O’ & Morrissey, Karyn, 2015. "Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: An Irish case study," Energy Policy, Elsevier, vol. 78(C), pages 62-77.
    14. van Sark, W.G.J.H.M. & Alsema, E.A., 2010. "Potential errors when fitting experience curves by means of spreadsheet software," Energy Policy, Elsevier, vol. 38(11), pages 7508-7511, November.
    15. Wu, X.D. & Yang, Q. & Chen, G.Q. & Hayat, T. & Alsaedi, A., 2016. "Progress and prospect of CCS in China: Using learning curve to assess the cost-viability of a 2×600MW retrofitted oxyfuel power plant as a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1274-1285.
    16. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    17. Nakata, Toshihiko & Sato, Takemi & Wang, Hao & Kusunoki, Tomoya & Furubayashi, Takaaki, 2011. "Modeling technological learning and its application for clean coal technologies in Japan," Applied Energy, Elsevier, vol. 88(1), pages 330-336, January.
    18. Harborne, Paul & Hendry, Chris, 2009. "Pathways to commercial wind power in the US, Europe and Japan: The role of demonstration projects and field trials in the innovation process," Energy Policy, Elsevier, vol. 37(9), pages 3580-3595, September.
    19. Astariz, S. & Iglesias, G., 2016. "Output power smoothing and reduced downtime period by combined wind and wave energy farms," Energy, Elsevier, vol. 97(C), pages 69-81.
    20. Bolinger, Mark & Wiser, Ryan, 2009. "Wind power price trends in the United States: Struggling to remain competitive in the face of strong growth," Energy Policy, Elsevier, vol. 37(3), pages 1061-1071, March.

    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:renene:v:40:y:2012:i:1:p:80-89. 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/renewable-energy .

    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.