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Innovation and cost reduction for marine renewable energy: A learning investment sensitivity analysis

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  • MacGillivray, Andrew
  • Jeffrey, Henry
  • Winskel, Mark
  • Bryden, Ian

Abstract

Using learning curves as an analytical tool for technology forecasting involves making assumptions over a range of key uncertainties, often implicitly. In this paper, we present an explicit treatment of the key uncertainties involved in learning rates' analyses of marine energy innovation (wave and tidal stream) — technology fields attracting considerable interest, but whose commercial prospects depends on substantial learning and cost reduction. Taking a simple single factor learning rate model, we describe a range of plausible learning investments required so that marine energy technologies become cost-competitive with their ‘benchmark’ technology: offshore wind. Our analysis highlights the sensitivity of marine energy to three key parameters: the capital cost of first devices, the level of deployment before sustained cost reduction emerges, and the average rate of cost reduction with deployment (learning rate). Figures often quoted within the marine energy sector for the parameters of starting cost, learning rate, and capacity at which sustained cost reduction occurs (metrics conventionally used for learning rate analysis) can be seen to represent very attractive scenarios. The intention of this paper is to display that even small changes to input assumptions can have a dramatic effect on the overall investment required for a sector to reach parity with benchmark technologies. In the short term, reaching cost competitiveness with offshore wind is a necessity if marine energy is to reach commercialisation. Additionally, an assessment of the plausible total investment (and inherent uncertainties) in a global wave and tidal deployment scenario will be presented. The paper also considers the implications of these uncertainties for marine energy innovation management. While the benchmark against offshore wind will generally be used as a performance indicator, in order to achieve similar and sustained cost reductions to other, more mature, renewable energy technologies (and thus achieve a competitive price for marine technologies, securing their place within the energy mix), the marine energy sector needs a targeted innovation focus to fulfil the desired objectives, and a development pathway very different to offshore wind must be used.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:tefoso:v:87:y:2014:i:c:p:108-124
    DOI: 10.1016/j.techfore.2013.11.005
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    Citations

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    Cited by:

    1. Jahanshahi, Akram & Kamali, Mohammadreza & Khalaj, Mohammadreza & Khodaparast, Zahra, 2019. "Delphi-based prioritization of economic criteria for development of wave and tidal energy technologies," Energy, Elsevier, vol. 167(C), pages 819-827.
    2. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2024. "Future costs of key emerging offshore renewable energy technologies," Renewable Energy, Elsevier, vol. 222(C).
    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. Zeyringer, Marianne & Fais, Birgit & Keppo, Ilkka & Price, James, 2018. "The potential of marine energy technologies in the UK – Evaluation from a systems perspective," Renewable Energy, Elsevier, vol. 115(C), pages 1281-1293.
    5. Antunes, Jorge & Tan, Yong & Wanke, Peter & Jabbour, Charbel Jose Chiappetta, 2023. "Impact of R&D and innovation in Chinese road transportation sustainability performance: A novel trigonometric envelopment analysis for ideal solutions (TEA-IS)," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    6. Adrian De Andres & Jéromine Maillet & Jørgen Hals Todalshaug & Patrik Möller & David Bould & Henry Jeffrey, 2016. "Techno-Economic Related Metrics for a Wave Energy Converters Feasibility Assessment," Sustainability, MDPI, vol. 8(11), pages 1-19, October.
    7. Renaldi, Renaldi & Hall, Richard & Jamasb, Tooraj & Roskilly, Anthony P., 2021. "Experience rates of low-carbon domestic heating technologies in the United Kingdom," Energy Policy, Elsevier, vol. 156(C).
    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. 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).
    10. Kërçi, Taulant & Tzounas, Georgios & Milano, Federico, 2022. "A dynamic behavioral model of the long-term development of solar photovoltaic generation driven by feed-in tariffs," Energy, Elsevier, vol. 256(C).
    11. Bi, Kexin & Huang, Ping & Wang, Xiangxiang, 2016. "Innovation performance and influencing factors of low-carbon technological innovation under the global value chain: A case of Chinese manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 275-284.
    12. Lavidas, George, 2019. "Energy and socio-economic benefits from the development of wave energy in Greece," Renewable Energy, Elsevier, vol. 132(C), pages 1290-1300.
    13. MacGillivray, Andrew & Jeffrey, Henry & Wallace, Robin, 2015. "The importance of iteration and deployment in technology development: A study of the impact on wave and tidal stream energy research, development and innovation," Energy Policy, Elsevier, vol. 87(C), pages 542-552.
    14. Guangyue Xu & Lulu Zhang & Zhongzhou Li & Zili Huang & Hongyu Jiang & Kyaw Jaw Sine Marma, 2024. "Exploring the Supporting Role of Finance in the Development of Clean Energy in China Based on the Panel Vector Autoregressive Model," Sustainability, MDPI, vol. 16(14), pages 1-30, July.
    15. Fox, Clive J. & Benjamins, Steven & Masden, Elizabeth A. & Miller, Raeanne, 2018. "Challenges and opportunities in monitoring the impacts of tidal-stream energy devices on marine vertebrates," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1926-1938.
    16. Liu, Yijin & Li, Ye & He, Fenglan & Wang, Haifeng, 2017. "Comparison study of tidal stream and wave energy technology development between China and some Western Countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 701-716.
    17. 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.
    18. Clark, Caitlyn E. & Miller, Annalise & DuPont, Bryony, 2019. "An analytical cost model for co-located floating wind-wave energy arrays," Renewable Energy, Elsevier, vol. 132(C), pages 885-897.
    19. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    20. Huang, Junbing & Luan, Bingjiang & He, Wanrui & Chen, Xiang & Li, Mengfan, 2022. "Energy technology of conservation versus substitution and energy intensity in China," Energy, Elsevier, vol. 244(PA).
    21. 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.
    22. Michail Chronopoulos & Afzal Siddiqui, 2015. "When is it better to wait for a new version? Optimal replacement of an emerging technology under uncertainty," Annals of Operations Research, Springer, vol. 235(1), pages 177-201, December.
    23. Guo, Jianfeng & Pan, Jiaofeng & Guo, Jianxin & Gu, Fu & Kuusisto, Jari, 2019. "Measurement framework for assessing disruptive innovations," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 250-265.
    24. Vazquez, A. & Iglesias, G., 2016. "Grid parity in tidal stream energy projects: An assessment of financial, technological and economic LCOE input parameters," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 89-101.

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