Different numerical modeling methods have been developed and applied to evaluate a variety of performance indicators of wave energy converters (WECs), including the power performance, structural loads, levelized cost of energy, etc. Based on the modeling fidelity, the commonly used numerical modeling approaches can be classified as linear modeling, weakly nonlinear modeling and fully nonlinear modeling approaches. Each method differs in accuracy and computational efficiency, making them suitable for different stages of WEC design. However, the selection of modeling approach could significantly impact evaluation outcomes. For instance, simplified linear models may underestimate structural loads or overestimate energy production in some operational conditions, potentially leading to less cost-effective designs. Given the widespread utilization of these models, it is essential to understand the uncertainties brought by them in performance evaluations. This work is dedicated to benchmarking different linear-potential-flow-based numerical models for evaluating the systematic performance of WECs. Three representative numerical modeling approaches are considered in this work, including linear frequency-domain modeling, statistically linearized spectral-domain modeling and Cummins equation-based nonlinear time-domain modeling. A generic point absorber WEC is considered as the research reference in this work, and different sea sites are taken into account. The numerical models are utilized to predict critical performance indicators, including power performance, the annual energy production, the capacity factor, the levelized cost of energy and the PTO fatigue loads. By comparing the results, this work identifies the uncertainties associated with different modeling approaches in evaluating WEC performance.

This study examines the potential contribution of marine renewable generators in Greece, in order to achieve a 100% renewable energy system by 2050. Using PyPSA-Eur, a cost-optimization model of the European energy system, possible energy transition pathways are explored, across five-year intervals from 2030 to 2050. For each five-year target, a new cost assumption dataset is used, one that follows estimated cost reduction learning rates. This version of the model is called PyPSA-Eur-MREL, and is modified to include marine power generators, i.e. floating wind, wave, tidal and floating solar, but also high fidelity climate data, in the scale of 5.5 km ² for wind and 4 km ² for wave resources. Three different approaches were employed in this investigation: greenfield, generator constrained, and a high-load scenario inspired by Greece's National Energy and Climate Plan (NECP). The analysis focused on generator capacity and performance, the levels of utilization and availability of each energy carrier and the land-use impact of onshore and offshore generators. While the first two scenarios exhibit similar overall system capacities, they differ in land-use requirements, with the constrained case installing more bottom-fixed wind turbines (1.2 GW), thereby reducing land occupation. The high-load scenario introduces floating wind turbines (4.5 GW), however, the scale of onshore installations remains substantial, covering nearly one-third of Greece's total land area.

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 proper design of wave energy converters (WECs) is crucial for ensuring robustness in harsh wave climates without incurring the additional expense of unnecessary overdesign. The power take-off (PTO) mechanism, serving as a vital link between the moving body and the electric generator, is a key component in the design load analysis of WECs. However, the setting of PTO system parameters significantly impacts the dynamic behavior of the entire WEC system, leading to alterations in estimated loads. This work is dedicated to studying the influence of PTO control strategies on the identification of extreme loads of a heaving point absorber WEC. A nonlinear time-domain model is established to estimate the dynamic responses and loads of the WEC. Both PTO loads and end-stop loads under extreme conditions are examined, considering the wave climate of a realistic sea site. The results suggest that the PTO setting strategies significantly impact the extreme load exerted on both the PTO system and the end-stop system. Varying the PTO damping within a certain range could lead to a difference of 57% and 63% in short-term extreme loads for the PTO system and the end-stop system, respectively. Furthermore, the impacts of the PTO control strategy appear to be specific to each WEC component. The PTO parameters selected for reducing the extreme PTO loads might increase the extreme end-stop loads. A holistic examination is therefore recommended for estimating the extreme loads of WECs.

Wave energy holds substantial promise as a renewable resource, but its commercial deployment remains limited. Research primarily focuses on individual wave energy converter (WEC) devices, while the interactions within WEC arrays have received less attention. Optimizing these interactions is essential for maximizing energy capture and minimizing operational costs. However, due to the variability of wave conditions, it is unlikely that a single WEC configuration will be effective across all scenarios. Therefore, to optimize performance, a large number of simulations are required, which is computationally expensive with traditional high-fidelity numerical methods. This paper addresses this challenge by utilizing a surrogate model based on polynomial chaos expansion (PCE), which efficiently captures the behavior of a WEC array over a 30-year probabilistic based on a high-fidelity wave dataset. The surrogate model is compared to a frequency domain model, demonstrating a high efficiency. The surrogate model is used to simulate the performance of an array of five point absorber WECs under varying wave conditions. The study highlights the following requirements for optimal array performance: the spatial configuration of WECs must consistently produce optimal power throughout the operational period and must adapt to the high variability of wave parameters. The results reveal that the fixed array configuration under study, produces power that is inconsistent over varying sea conditions, showing suboptimal energy production under most wave conditions, and higher power output only under less probable wave scenarios. These findings provide insights into the physical interactions influencing WEC array performance and can inform future design methodologies for wave energy farms. The proposed surrogate modeling framework offers a highly efficient tool for conducting large-scale probabilistic analyses of WEC arrays, significantly reducing computational effort while enabling more accurate performance predictions.

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.

The increasing global demand for wind power underscores the importance of understanding and characterizing extreme ramp events, which are significant fluctuations in wind power generation over short periods that pose challenges for grid integration. This study focuses on modeling frontal low-level jets (FLLJs) and associated extreme ramp-down events, particularly their impact on wind power production at Belgium offshore wind farms. Using the Weather Research and Forecasting (WRF) model, we analyzed five cases of extreme wind power ramp-down events, including in-depth analysis of two cases and generalization of three additional cases. We assessed the sensitivity of various model configurations, including initial and boundary condition (IC/BC) datasets (ERA5 and CERRA), the activation of Fitch wind farm parameterization (WFP), planetary boundary layer (PBL) schemes, and single- versus nested-domain configuration. Our findings indicate that CERRA IC/BCs provide a superior representation of atmospheric flow compared to ERA5, resulting in more accurate predictions of ramp timing, intensity, and FLLJ characteristics. The WFP significantly impacts wind power output by modeling turbine interactions and wake effects, leading to slightly lower wind speeds. The scale-aware Shin and Hong PBL scheme yielded a stronger FLLJ core at higher altitudes with a more pronounced jet nose, although wind speeds below 200 m were lower compared to the Mellor–Yamada–Nakanishi–Niino 2.5 scheme. Single-domain configuration proved more effective in simulating wind power ramps but had higher core heights and higher wind speeds below 200 m, resulting in a diffused jet profile. Our analysis highlights that reliable simulation of extreme ramps associated with FLLJs using a single-domain configuration could reduce computational costs. Further, the FLLJs and associated extreme ramps can be predicted 1 d in advance, offering substantial benefits for operational efficiency in wind energy management.

This article investigates the methodology and applicability of the statistical linearization (SL) method to incorporating multi-variate non-differentiable nonlinearities, with a focus on floating renewable energy devices. The SL method serves as a highly competitive approach for analyzing floating renewable energy structures, such as wave energy converters (WECs) and floating wind energy turbines, because it inherently combines adequate accuracy and high computational efficiency. The origin of high accuracy comes from its incorporation of nonlinear effects through statistically linearized representations. Yet, the statistically linearized solutions have only been derived and verified for a limited number of nonlinearities of floating renewable energy devices, mostly simply-formed and differentiable in their mathematical expressions. However, floating renewable energy devices usually exhibit a complex dynamic mechanism, in which the relevant nonlinear effects could appear to be highly complex for linearization process to describe. These nonlinear effects could make a significant impact on the system dynamics, exemplified by external machinery force saturation and nonlinear hydrostatics of floaters with a non-uniform geometry. To push forward the boundary of the SL method, it is crucial to demonstrate how it applies to nonlinearities of different features. In this paper, the existing SL method is extended to address the nonlinear effects expressed as multi-variate non-differentiable functions. Several case studies are carried out to exemplify the application of the extended SL approach to the concerned nonlinearities in floating renewable energy devices. The accuracy and computational efficiency of the extended SL approach are evaluated by verifying against the corresponding nonlinear time-domain (TD) and linear frequency-domain (FD) models. Despite the complexity of the given nonlinearities, the relative errors of the SL approach are no more than 6 % while its computational time is comparable to the FD model, being thousands of times faster than the TD model. Comparatively, the FD model leads to a relative error of over 70% in some cases.

Harnessing wave energy from the oceans using wave energy converters (WECs) offers a huge opportunity to diversify Europe’s future renewable energy system. Although the energy conversion of this pre-commercial technology is not directly linked to greenhouse gas emissions, environmental sustainability over the full life cycle needs to be ensured for a future-proof large-scale application of WECs. Therefore, we present a cradle-to-grave full life cycle assessment (LCA) study for a generic point absorber WEC based on a fully transparent and adaptable life cycle inventory. Within the study we assess the environmental impacts of a single point absorber device, the influence of different hull materials, hotspots in the impacts of WEC components, and variations induced by different deployment locations. For a WEC deployed in the North Sea, we found a global warming impact of 300-325gCO2eq./kWh with periphery and 52-77gCO2eq./kWh without periphery, depending on the hull material. Using an alternative fibre-reinforced concrete material for the hull can reduce the impact across all categories by between 10% (marine eutrophication) and 78% (human toxicity, carcinogenic). In addition to the WEC itself we found that the electrical cable and vessel operations, particularly for maintenance, are significant contributors. These two elements will also be relevant to other marine renewables such as offshore wind and floating solar. Overall, this study shows potential for improving environmental impacts from WECs and identifies possible levers to achieve such a reduction.

Nowadays, numerous governments have instituted diverse regulatory frameworks aimed at fostering the assimilation of sustainable energy sources characterized by reduced environmental footprints. Solar, wind, geothermal, and ocean energies were subject to extensive scrutiny, owing to their ecological merits. However, these sources exhibit pronounced temporal fluctuations. Notably, ocean dynamics offer vast energy reservoirs, with oceanic waves containing significant amounts of energy. In the Central American Pacific context, the exploration of wave energy resources is currently underway. Accurate numerical wave models are required for applied studies such as those focused on the estimation of exploitable wave power; and even more so in Central American region of the Pacific Ocean where existing numerical models simulations have so far relied on coarse resolution and limited validation field data. This work presents a high-resolution unstructured wave hindcast over the Central American Pacific region, implemented using the third-generation spectral wave model WAVEWATCH III over the period between 1979 and 2021. The results of the significant wave height have been bias-corrected on the basis of satellite information spanning 2005 to 2015, and further validation was performed using wave buoy and acoustic Doppler current profiler (ADCP) records located in the nearshore region of the Central America Pacific coast. After correction and validation of the wave hindcast, we employed the dataset for the evaluation and assessment of wave energy and its possible exploitation using different wave energy converters (WECs). This evaluation addressed the need to diverse the energy portfolio within the exclusive economic zones of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, Panama, Colombia, and Ecuador in a sustainable manner. Moreover, a comprehensive analysis was carried out on the advantages of harnessing wave energy, juxtaposed with the imperative of regulatory frameworks and the current dearth of economic and environmental guidelines requisite for development within the region.

The Boundary Element Method (BEM) based on the linear potential flow theory has shown to produce accurate results at low computational costs in numerical modelling of the hydrodynamics of Wave Energy Converters (WECs). WAMIT, Nemoh and Capytaine are some of the most popular frequency domain BEM solvers used in the response analysis of various WECs. Hydrodynamic Analysis of Marine Structures (HAMS), another open-source BEM solver gaining traction, has been applied to the analysis of single WECs considering rigid body motions providing highly accurate solutions at lower computational costs as compared to other solvers. This research extends its current capabilities to model structures with constraints by applying the generalized modes approach. Results presented include of a cross-model validation with commercial solver WAMIT, of the hydrodynamic coefficients and exciting forces considering flap converter. Furthermore, a comparison is shown with popular open-source solver Capytaine for the same case, since it has parallelization.

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.

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.

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.

The economic profitability of future wave energy production along the Galician coast is assessed by analyzing the Levelized Cost of Energy (LCoE) under different Capital Expenditure (CapEx) scenarios and two discounts rates (5% and 10%). Wave resources for the near future under the RCP8.5 scenario are downscaled using SWAN, providing up to 75 m spatial resolution in coastal areas. The study's goal is to enhance the cost-effectiveness by selecting the most suitable wave energy converter (WEC) for each location. Fourteen WECs operating at different depths are considered. This analysis reveals that the Atargis device boasts the lowest LCoE for 64.2% of the coastal area, mainly in deep waters, with an LCoE of 77 €/MWh. In addition, the Oyster and Wave Dragon devices exhibit the lowest LCoE for 12.4% and 15.0% of the coastal area, respectively, excelling in shallow waters and near the coast, with values of 50 €/MWh and 97 €/MWh. These findings demonstrate the profitability of wave energy production along the Galician coast, even when considering a more conservative CapEx of 3 M€/MW, resulting in a cost of 140 €/MWh. This conclusion takes into account the evolving electricity prices in Spain, which reached 0.2068 €/kWh in the second half of 2023.

Ocean wave energy has immense potential and can provide at least twice as much electricity as globally produced now due to its high energy density. In order to efficiently extract this energy and make this commercially viable, Wave Energy Converters (WECs) need to interact with the resource in an optimized way for the expanse of sea states. This interaction is critical to power production by these devices and hence an accurate modelling of this is paramount. The Boundary element method (BEM) based on the linear potential flow theory has yielded accurate results at low computational costs when compared to complex Computational Fluid Dynamics methods. Hydrodynamic Analysis of Marine Structures (HAMS) and Capytaine are recently developed open-source BEM frequency domain solvers, originally created for large marine structures. These solvers have since been utilized for studying wave energy converters, though, for very few converter geometries. Owing to the implementation of parallelization in both HAMS and Capytaine, both these solvers could be capable for significantly lower computational costs as compared to the traditional BEM solvers such as Nemoh. This research aims to compare hydrodynamic coefficients and computational costs in Nemoh, HAMS and Capytaine for various WEC geometries.

The Oscillating Water Column (OWC) wave energy converter has been shown to have high potential, thus rendering extensive development in recent years. In order to further accelerate its development, highly accurate yet computationally efficient tools are necessary particularly when studying the interaction of multiple OWC devices. This paper proposes a new framework for fixed OWC devices with an orifice, that uses the input from a high fidelity non-linear numerical model to improve the accuracy of a low fidelity linear numerical model keeping computational costs low. This is done by accounting for the non-linearities in the pressure-flow of an orifice in the input to the linear numerical model. Experimental data is used to validate the framework, thus providing an accurate and computationally efficient linear numerical model, that can be used for the preliminary analysis of fixed OWC devices.

A modified spectral-domain (SD) model is introduced in this study to address the nonlinear hydrostatic restoring force for heaving wave energy converters (WECs) with non-uniform cross-sectional areas. Distinguished from previous SD models, the modified SD model collectively includes the effects of incident wave elevation and buoy displacement, through the utilization of the multi-variate stochastic linearization method. The proposed SD model is verified against results obtained from a corresponding nonlinear time-domain (TD) model. Subsequently, a comprehensive comparison is carried out between the modified SD model, the other two existing SD models and the linear frequency-domain (FD) model. The nonlinear TD model is considered as the accuracy reference in this comparison. Various environmental and operational inputs, such as sea states, Power Take-Off (PTO) parameters, and buoy drafts, are systematically taken into account in the comparison. Additionally, the computational efficiency of each model is evaluated.

The results suggest that the modified SD model demonstrates significantly enhanced accuracy in cases where hydrostatic force nonlinearity intensifies, compared to the existing SD models and the FD model. Throughout the entire domain of the simulation cases, the maximum relative error of the modified SD model to the nonlinear TD model is below 5 %, while it is 20 % for the FD model and approximately 15 % for the two existing SD models. Moreover, the modeling accuracy of the FD model and existing SD models could be strongly disturbed by the variation of the environmental and operational inputs. Comparatively, the modified SD model is associated with much more stable accuracy. Nevertheless, the modified SD model only requires a modest increase in computational load compared to the FD model and existing SD models and it is still thousands of times faster than the nonlinear TD model.