Future role of wave power in Seychelles

A structured sensitivity analysis empowered by a novel EnergyPLAN-based optimisation tool

Journal Article (2024)
Author(s)

Dominik Keiner (Lappeenranta-Lahti University of Technology (LUT))

Ashish Gulagi (Lappeenranta-Lahti University of Technology (LUT))

Rasul Satymov (Lappeenranta-Lahti University of Technology (LUT))

Daniel Etongo (University of Seychelles)

G. Lavidas (TU Delft - Offshore Engineering)

Ayobami S. Oyewo (Lappeenranta-Lahti University of Technology (LUT))

Siavash Khalili (Lappeenranta-Lahti University of Technology (LUT))

Christian Breyer (Lappeenranta-Lahti University of Technology (LUT))

Research Group
Offshore Engineering
DOI related publication
https://doi.org/10.1016/j.energy.2024.131905
More Info
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Publication Year
2024
Language
English
Research Group
Offshore Engineering
Volume number
303
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Abstract

Mitigating climate change requires a variety of energy technologies and energy simulation approaches to evaluate the best possible system structures. Screening whether novel technologies are a viable solution for a particular country within a cost-optimised system setup is usually simulation- and time-intensive. This study introduces the novel add-on optimisation tool EP-ALISON-LUT for use in combination with EnergyPLAN applied to the test case of wave power in the case of Seychelles in 2030 and 2050 within a structured sensitivity analysis. The tool enables a high number of possible system setups and scenarios, including the import and domestic production of electricity-based fuels, to be modelled, allowing for an in-depth view of the system impacts of integrating wave power. The results indicate a limited role for wave power due to its relatively low yield, especially in 2030. However, in 2050, up to 500 MW of wave power capacity is possible with a lower or similar levelised cost of final energy compared to the reference scenario in 2019, which can benefit the diversification of the power generation portfolio. Thus, this novel tool is fast and effective in technology screening studies requiring a fast optimisation algorithm.