Genetic Algorithm in Tidal Range Schemes’ Optimisation

Jingjing Xue, Reza Ahmadian and Owen Jones

Energy, 2020, vol. 200, issue C

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.

Keywords: Tidal energy; Tidal lagoon; Genetic algorithm; Optimisation of operational characteristics (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:200:y:2020:i:c:s0360544220306034

DOI: 10.1016/j.energy.2020.117496

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