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Exploring Marine Energy Potential in the UK Using a Whole Systems Modelling Approach

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  • Anna Stegman

    (Energy Technologies Institute, Loughborough LE11 3UZ, UK
    Institute of Energy Systems, University of Edinburgh, Edinburgh EH9 3DW, UK
    College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn TR10 9EZ, UK)

  • Adrian De Andres

    (Institute of Energy Systems, University of Edinburgh, Edinburgh EH9 3DW, UK)

  • Henry Jeffrey

    (Institute of Energy Systems, University of Edinburgh, Edinburgh EH9 3DW, UK)

  • Lars Johanning

    (College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn TR10 9EZ, UK)

  • Stuart Bradley

    (Energy Technologies Institute, Loughborough LE11 3UZ, UK)

Abstract

The key market drivers for marine energy are to reduce carbon emissions, and improve the security and sustainability of supply. There are other technologies that also meet these requirements, and therefore the marine energy market is dependent on the technology being cost effective, and competitive. The potential UK wave and tidal stream energy market is assessed using ETI’s energy systems modelling environment (ESME) which uses a multi-vector approach including energy generation, demand, heat, transport, and infrastructure. This is used to identify scenarios where wave and tidal energy form part of the least-cost energy system for the UK by 2050, and will assess what Levelised Cost of Energy (LCOE) reductions are required to improve the commercialization rate. The results indicate that an installed capacity of 4.9 GW of wave and 2.5 GW of tidal stream could be deployed by 2050 if the LCOE is within 4.5 and 7 p/kWh for each respective technology. If there is a step reduction to the LCOE of wave energy, however, a similar capacity of 5 GW could be deployed by 2050 at a LCOE of 11 p/kWh.

Suggested Citation

  • Anna Stegman & Adrian De Andres & Henry Jeffrey & Lars Johanning & Stuart Bradley, 2017. "Exploring Marine Energy Potential in the UK Using a Whole Systems Modelling Approach," Energies, MDPI, vol. 10(9), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1251-:d:109421
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    References listed on IDEAS

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    Cited by:

    1. Gimara Rajapakse & Shantha Jayasinghe & Alan Fleming & Michael Negnevitsky, 2017. "A Model Predictive Control-Based Power Converter System for Oscillating Water Column Wave Energy Converters," Energies, MDPI, vol. 10(10), pages 1-17, October.
    2. 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.
    3. Eva Segura & Rafael Morales & José A. Somolinos, 2017. "Cost Assessment Methodology and Economic Viability of Tidal Energy Projects," Energies, MDPI, vol. 10(11), pages 1-27, November.
    4. Eva Segura & Rafael Morales & José A. Somolinos, 2019. "Influence of Automated Maneuvers on the Economic Feasibility of Tidal Energy Farms," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
    5. Chenglong Guo & Wanan Sheng & Dakshina G. De Silva & George Aggidis, 2023. "A Review of the Levelized Cost of Wave Energy Based on a Techno-Economic Model," Energies, MDPI, vol. 16(5), pages 1-30, February.
    6. Bhattacharya, Saptarshi & Pennock, Shona & Robertson, Bryson & Hanif, Sarmad & Alam, Md Jan E. & Bhatnagar, Dhruv & Preziuso, Danielle & O’Neil, Rebecca, 2021. "Timing value of marine renewable energy resources for potential grid applications," Applied Energy, Elsevier, vol. 299(C).

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