Wave energy has immense potential and can provide at least twice as much electricity as globally produced now due to its high energy density. Apart from the vast accessibility of the resource, waves are more predictable and available throughout the year when compared to other forms of renewable energies. This makes the development and utilization of wave energy tech-nologies immensely important, in order to meet the renewable energy targets, an example of which is the 40GW by 2050 set as the offshore energy strategy of the European Commission. For wave energy to become a commercially viable power source, in-dividual wave energy converters (WECs) need to be deployed in large numbers similar to what can be seen in the wind in-dustry. Therefore, numerical tools simulating multiple inter-acting devices becomes highly relevant. This research utilizes the new open-source Boundary Element Method (BEM) based solver HAMS-MREL to analyse the hydrodynamic interactions of mono-array farms of point absorbers inspired by the state-of-the-art Corpower C4 point absorber device in various configurations subjected to waves in different directions. The obtained responses are used to estimate the power absorbed by the arrays in different configurations to obtain the Array Power Matrices, which can be used to study the variability of the q-factors in different sea states and different directions. Furthermore, the obtained Array Power Matrices are used to estimate the power absorbed by the array configurations in the North Sea. This can be a powerful tool for the analysis of the best wave energy farm configurations as it employs a computationally efficient frequency domain-based solver.@en

Renewable energy project require long term climate information, offshore renewable energies in particular are in need of higher fidelity information as both power production, reliability and survivability rely on them. Existing open source datasets are too coarse, and often do not have the suitable physics based solutions to resolve high fidelity areas. While for power production different datasets may be needed wind speeds, solar radiation, ambient temperature, metocean conditions, the common thread is that all information provided by often open source free dataset carry large deviations that can be catastrophic or under-estimate power production significantly. This deliverable aims to bridge the gap and offer the EU-SCORES project three custom models wind, solar, wave and are then used for ultra high-fidelity assessment (sub 500m). The physical parametrisation are specifically calibrated with the need of EU-SCORES, and the models are intensively validated against in-situ and satellite information. This report describes the different models used for the construction of the open-source databases for wind-wave-solar information, from 1990-2021. All models have been developed, calibrated and validated against in-situ measurements, providing with the uncertainty levels for the hindcasts.@en

Renewable energy project require long term climate information, offshore renewable energies in particular are in need of higher fidelity information as both power production, reliability and survivability rely on them. Existing open source datasets are too coarse, and often do not have the suitable physics based solutions to resolve high fidelity areas. The deliverable offers an in-depth resource assessment for wind-wave-solar renewable energy resources along the European Atlantic region. The duration of information cover 1990-2021 (including 2021), resulting in 32 years. This deliverable uses state of the art high resolution data for wind and solar, and introduces the European Coasts High resolution Ocean WAVEs (ECHOWAVE) hindcast, a new open source database for wave conditions with superior accuracy. ECHOWAVE covers North Atlantic European waters within the coastal shelf, from intermediate to shallow water relative depths and is specially adjusted to improve the representation of sea states within the area of interest. This translates as a reduction of the uncertainties in the estimation of some of the most important wave parameters for wave energy applications.@en

One of the key aspects to consider before large scale de-ployments of wave energy converters (WEC), is to optimize the devices’ characteristics to improve wave power absorption. Typi-cally, devices with passive control are designed to have the highest efficiency in wave power absorption/production in the range of the most frequent wave conditions. In general, there is an intrinsic “trade-off” between the range of wave conditions where a WEC can operate and the operation efficiency which, in the end, is linked to the energy production yield. Outside the most frequent wave conditions, there is still a non-negligible percentage of oc-currences of more energetic sea states carrying high energy flux values. Given the specific design characteristics of a WEC de-vice, lower operation efficiency is expected during these stronger sea states, which is translated as a lower production compared to the available (usable) resource. In the present study, a multi-size point absorber WEC array, using passive internal control, is pro-posed to optimize wave power production at the array level. The main aim of this work is to verify the combined use of devices de-signed to work in the most frequent wave conditions, with WECs which mass and dimensions are defined to improve their response during stronger sea states. A comparison of the mean produced power is performed between a proposed multi-array and a single size one. This is done using 30 years of spectral wave data ob-tained from an implementation of the WAVEWATCH III model, while response of the wave energy converters array is simulated with the boundary element model HAMS-MREL. Preliminary results, using 10-devices arrays, show a promising increase in production from 60 to 140% when larger WECs are included.@en

Numerical wave models have been developed to reproduce the evolution of waves generated in all directions and over a wide range of wavelengths. The amount of wave energy in the different directions and wavelength is the result of a number of physical processes that are not well understood and that may not be represented in parameterizations. Models have generally been tuned to reproduce dominant wave properties: significant wave height, mean direction, dominant wavelengths. A recent update in wave dissipation parameterizations has shown that it can produce realistic energy levels and directional distribution for shorter waves too. Here, we show that this new formulation of the wave energy sink can reproduce the variability of measured infrasound power below a frequency of 2 Hz, associated with a large energy level of waves propagating perpendicular to the wind, for waves with frequencies up to 1 Hz. The details are sensitive to the balance between the non-linear transfer of energy away from the wind direction, and the influence of dominant and relatively long waves on the dissipation of shorter waves in other directions.

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In order to accelerate the transition from carbon fuels to renewable energy sources, it is essential to extend our knowledge of the resources’ availability to further improve or adjust the design of extraction devices. In the present paper, a first characterization of the tidal stream resource along the coast of The Netherlands is performed using a high-resolution unstructured grid implementation of the Thetis model. Extensive validation of the sea surface elevations was done by comparing with existing networks of tide gauges in the North Sea. The simulations from this study show that the highest tidal current intensities are generated mainly at Den Helder and Oost Vlieland, reaching values >1.5 m s−1 and power density estimates that are most frequently close to 300 W m−2 and that can reach values ≥ 900 W m−2. Given the relatively reduced depths where these ‘‘hot spots’’ are found, most existing stream turbines will require further development to operate. Nevertheless, the existence of higher current intensities zones, along a commonly considered ‘‘low energy’’ coast, opens the door to include the tidal stream resource in near future plans to diversify the energy supply in The Netherlands.@en

Climate change is expected to have an impact on wind patterns, and therefore the generation of waves. Phase 6 of the Coupled Model Intercomparison Project (CMIP6), provides various realization of outputs integrated global coupled models for different centuries. Wind quality is a cornerstone for wave energy as it is the primary generation driver in any wave model. Therefore, proper quantification of wind wave interactions are key in the evaluation of future wave energy potential. In this study, a wave hindcast for the North-East Atlantic, using the WaveWatchIII model forced by CMIP6 winds is presented. The model uses a grid of 0.25° of spatial resolution, covering a longitude range of -21.0° to 10° (west to east) and a latitude range of 18° to 80° (south to north). The main objective of this work is to assess the quality of historical winds from all the CMIP6 wind data that are available under the first realization criteria (r1i1p1f1) at the time of this study. This leads to understanding limitations and proposing a selection method to choose the optimal wind dataset to force the wave model within the analyzed area. Thus, the optimal CMIP6 historical winds for the North-East Atlantic are used to create a 10 years hindcast(from 2003 to 2012). To further assess the suitability of the selected winds dataset for wave generation, results are compared with the ERA5 wave product. The available CMIP6 models show region-specific variations depending on the Regional Climate models used for their developments. The results show the impact of zonal and, meridional wind intensities, on wave characteristics in different regions over the domain.@en

To date there is a wide range of wave reanalysis and hindcasts available to the scientific and engineering community which are commonly used for different applications, including downscaling or the estimation of the wave energy resource (Morim et al., 2022). These long datasets have been created using different combinations of forcing fields, physical parameterizations, and numerical choices (like spatial and spectral resolution). All these elements have a direct effect on the accuracy of the wave models’ output (e.g., Alday et al., 2021) and thus, they are one of the main reasons for the differences between these products. In the present study we analyze the significant wave heights and peak periods characteristics from a selection of global datasets. We additionally include results from a hindcast created using the WAVEWATCH III model, with adjustments specially aimed to reduce uncertainties of the wave energy resource along the Atlantic coasts of Europe. Models’ output is compared with buoys and altimeter data from the latest ESA (European Space Agency) CCI Sea State V3 product. Preliminary validation of the hindcast we have generated for the North Atlantic already show an important bias reduction for wave heights in the 2.5 to 11.5 range compared to ERA5 wave product. Using the relevant wave parameters, we estimate the power density and quantify the differences between databases. Then, based on scatter diagrams obtained from the joint distributions of significant wave height and peak period, the differences in the power captured by wave energy converters (WEC) related to different wave data sources will be quantified (e.g., Babarit et al., 2011; Henriques et al., 2016).@en

This Deliverable, 6.2 Renewable Coarse Resource Assessment for the European Region, aims to offer a preliminary overview of the available wind, wave and solar resources across the European Continent. The coarse assessment aims to analyse and assess the current levels of these renewable resources, analysing and discussing the expected variations per regions. The resource assessment, even at coarse level, can indicate regions for further high resolution analysis, with better suited wind-wave-solar models. The estimated energy densities of wind, wave and solar, are partially the main indicators, we also discuss the impacts of variability, as this is expected to alter the performance of power production, when each resource is utilised by specific technologies. This report also introduces some of the main statistical approaches and ways to estimate the resource potentials. They will be used and expanded upon in forthcoming Deliverables that will also look into power production, via coupling of high fidelity wind-wave-solar models with specific renewable converters. Finally, in this Deliverable we discuss the role of open source coarse data and underline their limitations for operational renewable energy projects.@en

This Deliverable, 6.1 Renewable Correlation of offshore resources, aims to investigate the potential for correlation between parameters of different renewable energies. The analysis is based on a first layer on coarse data, and will allow us to identify which resources have more “connectivity”. The resource assessment, even at coarse level, will indicate regions for further high resolution analysis, with better suited wind-wave-solar models. The correlation analysis is expected to showcase the potential of temporal overlaps by the different resources. The Deliverable examines the overlap of stochastic conditions, the analysis will consider different “time windows” for the base resource, and assess its complementarity with other stochastic renewables. The aim of this deliverable is the estimation of overlap and production of mean maps that indicate to which extend each resource is connected. It is expected that the wind and wave resources will produce higher interest, due to their temporal variability. However, peak solar performance will also be analysed in terms of overlap with wind and/or wave.@en