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Genetic Algorithm in Tidal Range Schemes’ Optimisation

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  • Xue, Jingjing
  • Ahmadian, Reza
  • Jones, Owen

Abstract

Tidal energy has a significant advantage over many other forms of renewable energy because of the predictability of tides. Tidal Range Structures (TRSs) are one of the main forms of tidal renewable energy. Designing the operation of TRSs is one of the challenging aspects in early stages due to the large variety of scenarios. Traditionally this has been done using a grid search. However, grid search can be very elaborate and time consuming during the design of TRSs. This paper proposes a novel and more efficient method to optimise the design of the operation of TRSs by maximising their electricity generation using a Genetic Algorithm. This GA model is coupled with a 0-D model which breaks the tides into small units and considers flexible operation. This approach delivered more than a 10% increase in electricity generation when compared to non-flexible operation, i.e. using fixed heads for all tides, just by optimising the operation. The GA model was able to achieve the same amount of electricity compared to the best grid search method with flexible operation more efficiently, i.e. with about a 50% reduction in simulation time. The feasibility of the elite operational scheme is validated through a developed 2-D model.

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  • Xue, Jingjing & Ahmadian, Reza & Jones, Owen, 2020. "Genetic Algorithm in Tidal Range Schemes’ Optimisation," Energy, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:energy:v:200:y:2020:i:c:s0360544220306034
    DOI: 10.1016/j.energy.2020.117496
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    References listed on IDEAS

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    Cited by:

    1. Moreira, Túlio Marcondes & de Faria, Jackson Geraldo & Vaz-de-Melo, Pedro O.S. & Medeiros-Ribeiro, Gilberto, 2023. "Development and validation of an AI-Driven model for the La Rance tidal barrage: A generalisable case study," Applied Energy, Elsevier, vol. 332(C).
    2. Pappas, Konstantinos & Mackie, Lucas & Zilakos, Ilias & van der Weijde, Adriaan Hendrik & Angeloudis, Athanasios, 2023. "Sensitivity of tidal range assessments to harmonic constituents and analysis timeframe," Renewable Energy, Elsevier, vol. 205(C), pages 125-141.
    3. Qi, Haijie & Yue, Hong & Zhang, Jiangfeng & Lo, Kwok L., 2021. "Optimisation of a smart energy hub with integration of combined heat and power, demand side response and energy storage," Energy, Elsevier, vol. 234(C).
    4. Xue, Jingjing & Ahmadian, Reza & Jones, Owen & Falconer, Roger A., 2021. "Design of tidal range energy generation schemes using a Genetic Algorithm model," Applied Energy, Elsevier, vol. 286(C).

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