In line with the global shift to transition away from fossil fuels to sustainable energy sources, tidal stream energy has emerged as a promising renewable option. This study investigates the tidal stream energy resources along the Dutch coast and focuses on the impact of Mean Sea Level (MSL) rise on the future resource potential. A THETIS high-resolution unstructured model is used. The model is validated against sea surface elevations, and the Dutch tidal stream resource uncertainties are well defined. The validated model is used to evaluate the tidal stream energy potential of the Netherlands, regions in the Wadden Sea and Westerschelde in Zeeland display noteworthy potential, evidenced by maximum average flow velocities of 1.3 m/s and maximum average energy densities of 1600 W/m2 for the Wadden Sea and maximum average flow velocities of 0.75 m/s and maximum average energy densities of 300 W/m2 for the Westerschelde. Forecasting the 2050 tidal stream resource, considering a projected 118 mm MSL rise, results indicate persistent energy characteristics, with minimal fluctuations in average velocities and average energy density when compared to the 2016 model. In the Wadden Sea and Zeeland, respectively, only marginal changes of +25 W/m2, and +8 W/m2 are observed in average energy density for those same locations. Furthermore, the inclusion of long-term constituents has negligible effects on the 2050 results, emphasising the stability of the tidal stream energy source. Tidal stream energy in the Netherlands stands out as a reliable and resilient energy source, demonstrating consistency in the face of projected MSL rise. Such predictability has the potential to contribute significantly to fostering a sustainable and secure energy system in the Netherlands, while aligning with global efforts to combat climate change.

The deployment of marine renewables (MRE) is important for transitioning to a low-carbon energy system. However, their performance is highly dependent on the deployment location, making the selection of feasible sites critical for large-scale implementation. To contribute meaningfully to Europe’s renewable energy strategy and support a carbon-neutral energy system by 2050, the environmental performance of MREs must be taken into account in site selection, beyond the typical economic and technical aspects. Therefore, this study presents a geospatial analysis of the climate change mitigation potential of two wave energy converters, floating offshore photovoltaics, and floating wind turbines in northern European coastal waters. By combining a detailed life cycle assessment model of the four MREs with spatial data, the distribution of their life cycle global warming impact and carbon payback periods is assessed across multiple regions. The results show significantly varying impact levels of the different MREs, with carbon-neutral deployment not guaranteed at every location. Wave energy converters only partially reach carbon neutrality, while floating photovoltaics fail to do so across the entire study area. Floating wind turbines can be considered carbon-neutral nearly across their entire theoretical application area. The findings highlight the importance of taking into account site-specific environmental performance of MREs in order to ensure a positive contribution to climate change mitigation. By providing spatially explicit maps of MREs’ global warming impacts and carbon payback periods, this study enables as the first of its kind the inclusion of climate change mitigation considerations in the site selection process for MREs.

To date the use of the JONSWAP parametric spectrum is still widely accepted in many engineering applications, including the wave energy sector. Nevertheless, in the last 15 years many studies have progressively shown the necessity to implement more detailed and realistic spectral information in order to reduce the errors (or differences) introduced when the JONSWAP spectrum fails to describe more complex sea states. In the present study, the changes in produced power estimations, related to different spectral representations, are analysed. All power production estimates are obtained through 30 years simulations of point-absorber Wave Energy Converter (WEC) arrays, using the HAMS-MREL Boundary Element Method (BEM) solver. To assess the effects of the wave energy distribution on power production, 3 different spectral forcing are considered. Two based on the JONSWAP spectrum, and 1 using spectra time series from the ECHOWAVE hindcast specially developed for wave energy applications. For comparison purposes, the hindcast spectra is used as reference, since it can accurately represent the sea states evolution in time including the occurrence of multimodal conditions, which are not considered by the JONSWAP formulation. Additionally, 3 locations with different wave climates are analysed within European coastal waters. Recent results, focused on the response of a single (point-absorber) WEC, show that the differences in the mean yearly production can be > 12% when compared to reference hindcast data. The generalised analysis presented here, including the hydrodynamic interactions between multiple WECs within an array, is an important step forward in the understanding and quantification of the uncertainties present in power production assessments.

Understanding the effects of arrays of Wave Energy Converters (WEC) on the wave fields is still an ongoing effort. Many publications have proposed different approaches to incorporate WEC farms in wave models to assess sea state changes in the near and far field. In the present study, a practical iterative method is proposed to incorporate the spectral response of a WEC obtained from the HAMS-MREL Boundary Element Model (BEM) in the SWAN spectral wave model. This allows to change the transmission and reflection properties of the WEC, represented in the model as an obstacle, at each time step. Since the response of a WEC simulated in the BEM model is defined in the frequency domain, it is possible to relate the absorbed power, at each discrete frequency, to the transmission coefficient applied at each frequency used to discretize the wave spectrum in SWAN. In this case, the method is applied to a single point-absorber type device since its response is independent of the waves’ directions. Validation of the method is done comparing the omnidirectional spectrum obtained downwave of the WEC in SWAN, with the spectrum reconstructed using the regular wave fields information (for each frequency) obtained in HAMS-MREL.

This study presents a first long term (30 years) assessment to quantify the effects of both, the wave spectrum representation, and occurrences of multi-modal sea states, on power production estimations from a point-absorber Wave Energy Converter (WEC). Analysis in 3 different offshore locations (Portugal, Ireland and The Netherlands) is included to ensure robustness of results. In general, traditional methods based on the use of the JONSWAP spectrum, with an adequate gamma shape value, can lead to mean overestimation in yearly power production >12% when compared to reference hindcast spectral data. This can be partially reduced when capping is applied to power production, but still can be close to 10%. An alternative method is proposed to modulate the JONSWAP spectrum at each time step which helps to reduce differences, but leads to slight yearly underestimations (−2.5 to −5% in average). Although in all analyzed sites the occurrences of multi-modal spectra is >30%, contribution to errors due to misrepresentation of these sea states are estimated to be of about 2.5%. These findings provide valuable insights on the uncertainties introduced in power production estimations, related to wave conditions characterization, that can have important economic impact when planning for large scale deployments.

As the necessity for the decarbonisation of the global electricity market increases, a range of renewable energy technologies will be implemented, one of which is wave energy. A key step in this process is the thorough quantification of both the power resource at locations of interest, and the impacts of these devices on the natural environment. The present work streamlines these 2 processes into one methodology by investigating the long-term impacts of an array of 20 WECs on the nearshore Dutch wave climate, while also calculating the potential power resource at the site considering intra-array wake effects. Simulations of 10 year duration were conducted in the baseline scenario (no farm present) and with 2 array configurations, using the spectral wave model SWAN on an unstructured mesh. It was demonstrated that the power production of the farm during this period, when wake effects are considered, is calculated to be up to 1.8% less than traditional methods. The presence of the farm is shown to reduce significant wave height and wave power in its lee, with the effects being largely attenuated at the coast. It was shown that the magnitude of the change is dependent on both the period and height of the waves at the farm, and notably the magnitude of the reduction does not increase consistently with the wave height, contradicting the sentiment that wave farms are effective protection mechanisms against damaging high-energy conditions. Furthermore, the present work suggests that changes to the nearshore breaker index may impact longshore currents that are essential for nutrient and sediment transport, the effect of which on the ecosystem is not yet well quantified.

The Energy Transition requires meticulous planning, taking into consideration economic, technical, social, and resource constraints. In Europe ambitious targets have been set for system electrification, however, integrating the potential of marine renewables have not been thoroughly investigated. This study extends the framework of PyPSA-Eur into PyPSA-Eur-MREL that for the first time incorporates all marine renewables, using high resolution datasets, that uncover the potential of marine renewables. Marine renewables are modelled in terms of power estimations, deployment strategies and revised packing density, and expected benefits for 2030, and 2050 across all European Countries are quantified. Higher spatio-temporal data have an immediate impact in estimates, and reduction of energy storage by 73%. Wind energy has a reduced installation capacity by 50%, but the higher fidelity of resource matches production to demand and reduces curtailments up to 60%. System costs with high resolution data are 40% reduced to 160 billion € for a 2030 100% renewable reliant system. The benefits of having more marine renewables are not limited to cost and more efficient demand matching, reduced energy storage, but it also with the area required to decarbonise the system. The results are encouraging and outline the importance and further need for marine renewable energies.

The ECHOWAVE hindcast is an open source dataset specially developed for wave climate and energy applications within European Atlantic waters. It provides high resolution (∼2.3 km) fields of wave parameters and spectral data allowing for a detailed characterization of the wave resource within the coastal shelf. This is of importance for depths <200 m, where most deployment projects of wave energy converters (WEC) take place. Model setup and adjustments, leading to parameterization TUD-165, were specially aimed to improve the sea states’ characterization within the North-East Atlantic. The effects on accuracy of these adjustments and extensive validation, were done mainly comparing simulations with significant wave heights (H _s) from the European Space Agency CCI Version 3 altimeter dataset. Verification of other wave parameters and the spectral energy comparing with in situ measurements were also included. Results show that TUD-165 helps to reduce about 5% the H _s bias of the most frequent waves compared to T475 proposed by Alday et al. (2021), and an overall better performance than ERA5 within the North-East Atlantic. Compared to WAVERYS, ECHOWAVE performs better for H _s >9.5 m, with constrained bias between −2 to 5%. The accurate estimation of “extreme” waves is important to avoid WECs survivability over-estimations.

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.

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.

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.

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.

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.

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.

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. 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 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 a point absorber wave energy converter (WEC) related to different wave data sources will be quantified.

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.

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.