Characterising the wave energy resource of Lanzarote, Canary Islands

David Christie, Simon P. Neill and Peter Arnold

Renewable Energy, 2023, vol. 206, issue C, 1198-1211

Abstract: Waves of varying magnitude and frequency, characteristic of all coastal locations throughout the world, could be converted into electricity via wave energy converters. However, one challenge with wave energy conversion is lack of knowledge of the regional distribution of wave properties (e.g. to optimise site selection), and how the wave power varies at inter- and intra-annual timescales. Here, we apply physics- and non-physics-based approaches to accurately simulate the wave climate of the Canary Islands—a region in the eastern North Atlantic that relies heavily on the import of diesel to generate much of its electricity. Over the 11-year time period of the physics-based wave hindcast, the annual mean wave power of Lanzarote, one of the largest of the Canary Islands was approximately 25 kW/m along the exposed north-western coast of the island. We find that intra-annual variability was relatively low (compared with high latitude regions such as the west coast of Scotland), with the coefficient of variation for wave energy resource = 1.1. To reduce levelized cost, it could be advantageous to co-locate wave energy arrays with mature offshore wind energy, and we find that the dominance of swell waves in Lanzarote reduces the coefficient of variation for a 55% wind, 45% wave combination to 0.8. Finally, we demonstrate a simple non-physics based process for extending the output timeseries beyond the hindcast duration, by correlating with parameters from global models.

Keywords: Wave energy; Spectral modelling; Simulating waves nearshore SWAN model; Resource assessment; Wind-wave co-location; Metamodel (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:206:y:2023:i:c:p:1198-1211

DOI: 10.1016/j.renene.2023.02.126

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