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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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    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).

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    Keywords

    LCOE; Offshore wind; Accounts;
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