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

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  • 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.

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  • 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
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    References listed on IDEAS

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    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.
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    Cited by:

    1. 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).
    2. 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).
    3. 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.
    4. Emblemsvåg, Jan, 2022. "Wind energy is not sustainable when balanced by fossil energy," Applied Energy, Elsevier, vol. 305(C).
    5. 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).
    6. 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.
    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. 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).
    9. Benini, Giacomo & Cattani, Gilles, 2022. "Measuring the long run technical efficiency of offshore wind farms," Applied Energy, Elsevier, vol. 308(C).
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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).
    15. 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.

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    Keywords

    LCOE; Offshore wind; Accounts;
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