Optimal strategies of deployment of far offshore co-located wind-wave energy farms

[EN] The most profitable offshore energy resources are usually found away from the coast. Nevertheless, the accessibility and grid integration in those areas are more complicated. To avoid this problematic, large scale hydrogen production is being promoted for far offshore applications. The main objective of this paper is to analyze the ability of wave energy converters to maximize hydrogen production in hybrid wind and wave far offshore farms. To that end, wind and wave resource data are obtained from ERA5 for different locations in the Atlantic ocean and a Maximum Covariance Analysis is proposed for the selection of the most representative locations. Furthermore, the suitability of different sized wave energy converters for auxiliary hydrogen production in the far offshore wind farms is also analysed. On that account, the hydrodynamic parameters of the oscillating bodies are obtained via simulations with a Boundary Element Method based code and their operation is modelled using the software tool Matlab. The combination of both methodologies enables to perform a realistic assessment of the contribution of the wave energy converters to the hydrogen generation of an hybrid energy farm, especially during those periods when the wind turbines would be stopped due to the variability of the wind. The obtained results show a considerable hydrogen generation capacity of the wave energy converters, up to 6.28% of the wind based generation, which could remarkably improve the efficiency of the far offshore farm and bring important economical profit. Wave energy converters are observed to be most profitable in those farms with low covariance between wind and waves, where the disconnection times of the wind turbines are prone to be more prolonged but the wave energy is still usable. In such cases, a maximum of 101.12 h of equivalent rated production of the wind turbine has been calculated to be recovered by the wave energy converters.This paper is part of project PID2020-116153RB-I00 funded by MCIN/AEI/ 10.13039/501100011033. Authors also acknowledge financial support by the University of the Basque Country under the contract (UPV/EHU, GIU20/008)