IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v128y2019icp25-35.html
   My bibliography  Save this article

Better estimates of LCOE from audited accounts – A new methodology with examples from United Kingdom offshore wind and CCGT

Author

Listed:
  • Aldersey-Williams, John
  • Broadbent, Ian D.
  • Strachan, Peter A.

Abstract

Around the world, government policies to support new renewable energy technologies rely on accurate estimates of Levelised Cost of Energy (LCOE). This paper reveals that such estimates are based on “public domain” data which may be unreliable. A new approach and methodology has been developed which uses United Kingdom (UK) “audited” data, published in company accounts, that has been obtained from Companies House, to determine more accurate LCOE estimates. The methodology is applicable to projects configured within Special Purpose Vehicle (SPV) companies. The methodology is then applied to a number of UK offshore wind farms and one Combined Cycle Gas Turbine (CCGT) project to develop new cost data which is then compared to that presently in the public domain. The analysis reveals that recent offshore wind projects show a slightly declining LCOE and that public domain cost estimates are unreliable. But of most concern is that offshore wind farm costs are still much higher than those implied by recent bids for UK government financial support via Contracts for Difference (CfDs). The paper concludes by addressing further the question of how offshore wind projects can achieve the degree of LCOE reductions required by recent CfD bids.

Suggested Citation

  • Aldersey-Williams, John & Broadbent, Ian D. & Strachan, Peter A., 2019. "Better estimates of LCOE from audited accounts – A new methodology with examples from United Kingdom offshore wind and CCGT," Energy Policy, Elsevier, vol. 128(C), pages 25-35.
  • Handle: RePEc:eee:enepol:v:128:y:2019:i:c:p:25-35
    DOI: 10.1016/j.enpol.2018.12.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421518308504
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2018.12.044?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. Aldersey-Williams, J. & Rubert, T., 2019. "Levelised cost of energy – A theoretical justification and critical assessment," Energy Policy, Elsevier, vol. 124(C), pages 169-179.
    2. Voormolen, J.A. & Junginger, H.M. & van Sark, W.G.J.H.M., 2016. "Unravelling historical cost developments of offshore wind energy in Europe," Energy Policy, Elsevier, vol. 88(C), pages 435-444.
    3. 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.
    4. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    5. Heptonstall, Philip & Gross, Robert & Greenacre, Philip & Cockerill, Tim, 2012. "The cost of offshore wind: Understanding the past and projecting the future," Energy Policy, Elsevier, vol. 41(C), pages 815-821.
    6. MacGillivray, Andrew & Jeffrey, Henry & Winskel, Mark & Bryden, Ian, 2014. "Innovation and cost reduction for marine renewable energy: A learning investment sensitivity analysis," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 108-124.
    7. Ederer, Nikolaus, 2015. "Evaluating capital and operating cost efficiency of offshore wind farms: A DEA approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1034-1046.
    8. 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.
    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. Cartelle Barros, Juan José & Lara Coira, Manuel & de la Cruz López, María Pilar & del Caño Gochi, Alfredo, 2016. "Probabilistic life-cycle cost analysis for renewable and non-renewable power plants," Energy, Elsevier, vol. 112(C), pages 774-787.
    11. van der Zwaan, Bob & Rivera-Tinoco, Rodrigo & Lensink, Sander & van den Oosterkamp, Paul, 2012. "Cost reductions for offshore wind power: Exploring the balance between scaling, learning and R&D," Renewable Energy, Elsevier, vol. 41(C), pages 389-393.
    12. Staffell, Iain & Green, Richard, 2014. "How does wind farm performance decline with age?," Renewable Energy, Elsevier, vol. 66(C), pages 775-786.
    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. Aquila, Giancarlo & Nakamura, Wilson Toshiro & Junior, Paulo Rotella & Souza Rocha, Luiz Celio & de Oliveira Pamplona, Edson, 2021. "Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    2. Wan, Yong & Zheng, Chongwei & Li, Ligang & Dai, Yongshou & Esteban, M. Dolores & López-Gutiérrez, José-Santos & Qu, Xiaojun & Zhang, Xiaoyu, 2020. "Wave energy assessment related to wave energy convertors in the coastal waters of China," Energy, Elsevier, vol. 202(C).
    3. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    4. Sanghyun Sung & Wooyong Jung, 2019. "Economic Competitiveness Evaluation of the Energy Sources: Comparison between a Financial Model and Levelized Cost of Electricity Analysis," Energies, MDPI, vol. 12(21), pages 1-21, October.
    5. Johnston, Barry & Foley, Aoife & Doran, John & Littler, Timothy, 2020. "Levelised cost of energy, A challenge for offshore wind," Renewable Energy, Elsevier, vol. 160(C), pages 876-885.
    6. Shen, Wei & Chen, Xi & Qiu, Jing & Hayward, Jennifier A & Sayeef, Saad & Osman, Peter & Meng, Ke & Dong, Zhao Yang, 2020. "A comprehensive review of variable renewable energy levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    7. Chankook Park & Minkyu Kim, 2021. "A Study on the Characteristics of Academic Topics Related to Renewable Energy Using the Structural Topic Modeling and the Weak Signal Concept," Energies, MDPI, vol. 14(5), pages 1-24, March.
    8. Santhakumar, Srinivasan & Smart, Gavin & Noonan, Miriam & Meerman, Hans & Faaij, André, 2022. "Technological progress observed for fixed-bottom offshore wind in the EU and UK," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    9. Aldersey-Williams, John & Broadbent, Ian D. & Strachan, Peter A., 2020. "Analysis of United Kingdom offshore wind farm performance using public data: Improving the evidence base for policymaking," Utilities Policy, Elsevier, vol. 62(C).
    10. Vieira, M. & Snyder, B. & Henriques, E. & Reis, L., 2019. "European offshore wind capital cost trends up to 2020," Energy Policy, Elsevier, vol. 129(C), pages 1364-1371.
    11. Izabela Godyń & Anna Dubel, 2021. "Evolution of Hydropower Support Schemes in Poland and Their Assessment Using the LCOE Method," Energies, MDPI, vol. 14(24), pages 1-23, December.
    12. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    13. Benini, Giacomo & Cattani, Gilles, 2022. "Measuring the long run technical efficiency of offshore wind farms," Applied Energy, Elsevier, vol. 308(C).
    14. Emblemsvåg, Jan, 2022. "Wind energy is not sustainable when balanced by fossil energy," Applied Energy, Elsevier, vol. 305(C).
    15. Ding, Xiaoyi & Sun, Wei & Harrison, Gareth P. & Lv, Xiaojing & Weng, Yiwu, 2020. "Multi-objective optimization for an integrated renewable, power-to-gas and solid oxide fuel cell/gas turbine hybrid system in microgrid," Energy, Elsevier, vol. 213(C).

    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. Philipp Beiter & Aubryn Cooperman & Eric Lantz & Tyler Stehly & Matt Shields & Ryan Wiser & Thomas Telsnig & Lena Kitzing & Volker Berkhout & Yuka Kikuchi, 2021. "Wind power costs driven by innovation and experience with further reductions on the horizon," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    2. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    3. 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).
    4. 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.
    5. Duffy, Aidan & Hand, Maureen & Wiser, Ryan & Lantz, Eric & Dalla Riva, Alberto & Berkhout, Volker & Stenkvist, Maria & Weir, David & Lacal-Arántegui, Roberto, 2020. "Land-based wind energy cost trends in Germany, Denmark, Ireland, Norway, Sweden and the United States," Applied Energy, Elsevier, vol. 277(C).
    6. Thomassen, Gwenny & Van Passel, Steven & Dewulf, Jo, 2020. "A review on learning effects in prospective technology assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    7. Alemzero, David & Acheampong, Theophilus & Huaping, Sun, 2021. "Prospects of wind energy deployment in Africa: Technical and economic analysis," Renewable Energy, Elsevier, vol. 179(C), pages 652-666.
    8. Wei, Max & Smith, Sarah J. & Sohn, Michael D., 2017. "Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US," Applied Energy, Elsevier, vol. 191(C), pages 346-357.
    9. Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
    10. Svetlana Revinova & Inna Lazanyuk & Svetlana Ratner & Konstantin Gomonov, 2023. "Forecasting Development of Green Hydrogen Production Technologies Using Component-Based Learning Curves," Energies, MDPI, vol. 16(11), pages 1-19, May.
    11. Hernandez-Negron, Christian G. & Baker, Erin & Goldstein, Anna P., 2023. "A hypothesis for experience curves of related technologies with an application to wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    12. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
    13. Tadeusz Skoczkowski & Sławomir Bielecki & Joanna Wojtyńska, 2019. "Long-Term Projection of Renewable Energy Technology Diffusion," Energies, MDPI, vol. 12(22), pages 1-24, November.
    14. Odam, Neil & de Vries, Frans P., 2020. "Innovation modelling and multi-factor learning in wind energy technology," Energy Economics, Elsevier, vol. 85(C).
    15. Wiser, Ryan & Millstein, Dev, 2020. "Evaluating the economic return to public wind energy research and development in the United States," Applied Energy, Elsevier, vol. 261(C).
    16. Santhakumar, Srinivasan & Smart, Gavin & Noonan, Miriam & Meerman, Hans & Faaij, André, 2022. "Technological progress observed for fixed-bottom offshore wind in the EU and UK," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    17. Gunther Glenk & Rebecca Meier & Stefan Reichelstein, 2021. "Cost Dynamics of Clean Energy Technologies," Schmalenbach Journal of Business Research, Springer, vol. 73(2), pages 179-206, June.
    18. Grafström, Jonas & Poudineh, Rahmat, 2021. "A review of problems associated with learning curves for solar and wind power technologies," Ratio Working Papers 347, The Ratio Institute.
    19. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    20. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).

    More about this item

    Keywords

    LCOE; Offshore wind; Accounts;
    All these keywords.

    Statistics

    Access and download statistics

    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:128:y:2019:i:c:p:25-35. 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.