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- W4322209362 abstract "The Canary Islands in the eastern North Atlantic has an abundant and diverse renewable energy resource but currently generates much of its electricity from imported diesel, at significant financial and environmental cost.  To address this, the government and electricity supplier are investing heavily in infrastructure to transform the islands’ energy mix to incorporate offshore wind and wave power.  Economically and technically feasible offshore wave energy projects rely on understanding the regional distribution of wave properties (e.g. to optimize site selection), and how the wave power varies at inter- and intra-annual timescales.  We have constructed an 11-year wave hindcast model for a potential wave energy site at an energetic location in the north-west coast of Lanzarote, one of the largest of the Canary Islands, to investigate the spatial and temporal distribution of wave power.  Due to a lack of a continental shelf, wave power is homogeneous until a few km from the coastline, and then begins to vary rapidly in space.  Temporal variation is relatively low due to the latitude.  The wave resource is heavily dominated by swell, with uninterrupted fetch across the Atlantic, and largely uncorrelated with local wind.  This makes co-location of wind and wave energy arrays particularly attractive from the perspective of reducing resource variability, as well as the other practical and financial benefits of sharing a grid location with more established offshore wind technology. Finally, we demonstrate and validate a simple non-physics based process for extending the output timeseries beyond the hindcast duration, by correlating with parameters from global datasets.  This method also allows the possibility of power forecasting based on global operational models." @default.
- W4322209362 created "2023-02-27" @default.
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- W4322209362 date "2023-05-15" @default.
- W4322209362 modified "2023-09-29" @default.
- W4322209362 title "Wave Power in Lanzarote: Spatiotemporal Variability, Wind Co-location and Non-Physics based Modelling" @default.
- W4322209362 doi "https://doi.org/10.5194/egusphere-egu23-13905" @default.
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