1   Introduction

Ocean wave energy, because of its predictability and reliability, offers a promising opportunity to help reduce reliance on fossil fuels and support the transition to a more sustainable, diverse, and resilient energy mix. Moreover, the energy carried by ocean waves is dense and consistent compared with other renewable energy sources, and energy losses are small for long propagation distances.

Wave energy can be understood as a transformed form of solar energy. The differential heat gradient of the earth's surface promotes the generation of winds that, when blown over large widths of water, transfer part of the energy into waves. The magnitude of the energy transferred from the wind to the water surface (and hence the wave height and period) depends on the wind speed, the duration, and the distance over which it blows (fetch). The waves created locally close to the wind-blow generation area constitute the "wind sea" and exhibit a very irregular pattern. As these waves travel, they grow and progressively become regular and smoother waves characterized by greater wavelengths called "swell". As swell waves approach the shoreline travelling in waters of decreasing depth, the effect of the seabed, local currents, the geometry of the coastline, or shelter due to the presence of islands may provoke significant changes in wave direction and meaningful power losses.

Early attempts to convert wave energy date back a few hundred years, when France's first WEC patent was born in 1799 (Don Ross, 1995). Much later, Yoshio Masuda built the first floating oscillating water column attached to a navigation buoy in 1940 (Masuda, 1986). Since then, the geographical variability of wave patterns has resulted in various device types. Today, over a hundred different WEC concepts have been developed worldwide, with different maturity, working principles, directional alignment to waves, set-up locations, and PTO systems.

A review of the WECs deployed and demonstrated information about global technology developers, existing and forthcoming projects at open sea test sites is given in references (Magagna and Uihlein, 2015; Magagna et al., 2018; Ahamed et al., 2020; Bertram et al., 2020; OES-IEA, 2021; IEA-OES, 2023), and a library including photographic documentation of WEC concepts that reached the highest levels of development can be found in Tethys Engineering (2023). Details about the classification methods of WEC technologies are given in Guedes Soares et al. (2013), Bertram et al. (2020), and IRENA (2020). On the other hand, the most popular mechanisms for transforming wave energy into electrical energy and WEC control systems are given in Gallutia et al. (2022), Barua and Salauddin Rasel (2024). Most of the concepts are in the R & D stage, although some of them have reached full-scale prototypes and have been tested in the open sea. The most promising ideas for commercialisation include oscillating water columns (OWC), oscillating water surge converters (OWSC) and point absorbers (IRENA 2020).

Despite the wide range of WEC prototypes tested, convergence into commercial applications has not been reached yet, and the integration into the global energy market has been slow due to complex associated challenges, namely long-term survivability at sea, lack of consensus about the optimum design and PTO, lack of technological maturity, difficult storage, inland grid integration and high economic uncertainty (Kamranzad and Hadadpour 2020, Clemente et al., 2021). The LCOE of the wave energy (estimated at 0.27‒0.54 €/kWh (IRENA 2021)) is still not competitive against that of other commercial renewables (0.027‒0.11 €/kWh) (IRENA 2023) and fossil energy sources (0.045‒0.16 €/kWh) (Our World in Data 2023). However, it is expected to stabilize and decrease as the learning curve progresses.

A detailed compilation of advantages and challenges that researchers and industry developers must overcome before large-scale wave energy conversion installations can be fully realized is given in (Gallutia et al., 2022). Nonetheless, despite its elevated cost, the exploitation of wave energy can still substantially increase energetic independence, especially in marine regions with high costs of imported energy, such as island territories. Some socioeconomic benefits linked to wave energy exploitation, among other MREs, are provided in (Bhuiyan et al., 2022). Furthermore, wave energy can efficiently supply flexible and low-cost power assurances for offshore projects with signi ficant power grid development requirements, such as marine farms, surveillance equipment, and drilling platforms (Chen et al., 2022).

Recently, the International Energy Association made efforts to set up common areas and parameters to evaluate the performance of wave energy exploitation (IEA-OES 2021). No international consensus has yet been reached on which metrics to use for a standardised evaluation of the wave energy resource at each of its exploitation levels. Thus, various diverse metrics have been estimated historically to characterize the wave resource and its potential at a given place or using a specific technology. The most popular ones have been compiled in (Guillou et al., 2020). However, a more exhaustive collection of the various parameters estimated in the literature is still missing.

This paper contributes to facilitating the understanding of wave energy evaluation parameters by providing a compilation and classification of the metrics most often estimated for the characterization of the wave resource at different levels of exploitation. Moreover, an overview of the global wave energy resource is given, and existing prospective wave resource assessments at different exploitation levels worldwide have been collated and classified by area of study. Finally, information about thirty-four existing worldwide wave energy test centres and their characteristics has been depicted and displayed into a newly created global wave test-sites map.

The paper is organised as follows: Section 2 classifies the estimators and metrics commonly used for wave energy assessment by exploitation levels. Section 3 presents an overview of global and continental wave energy resource assessment studies. Section 4 compiles details about existing wave energy test sites around the world. Finally, Section 5 includes the main conclusions retrieved from this review.

2   Estimators and metrics for wave resource characterisation

Different levels characterize the wave energy conversion process using WECs, from the net available resource to delivering power to the grid to reach the final user (Figure 1), somehow inspired by the classification used in previous references (ESBI, 2005; ABP MER, 2008; Dalton et al., 2010; Mørk et al., 2010). This review classifies the resource levels as theoretical, practicable, technical, and socio-economic.

Figure  1  Levels characterizing the wave energy conversion process, from the net available resource to delivering power to the grid

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Level 1, referred to as theoretical potential, is related to the raw wave resource available and its climate. Wave climate, extreme analysis, and energy resource statistics are commonly performed to assess the resources at this level. The met-ocean metrics associated with this level have also been referred to as pre-production metrics (Guillou et al., 2020) and include the significant wave height, peak and energy periods, mean direction, the available power density, the long-term statistics of those parameters or bivariate scatter diagrams, among others.

Level 2, referred to here as practicable potential, accounts for the energy potential of the areas where its extraction is feasible and accessible. Its assessment includes rejecting areas constrained due to impracticable water depths or distances to shore, environmental or safety constraints, other marine uses and existing activities, or other spatial criteria that would make deploying a wave farm inappropriate. Evaluating the resource at this level requires marine spatial planning metrics and techniques.

Level 3, referred to as technical potential, is related to the WEC performance and the transmission system of the energy to shore. Not all WEC technologies are equally appropriate for every wave environment. The extent to which a WEC can convert the locally available power into output power is given by its power matrix (PM_{i, j}) and rated power (Rp), which depend on the symphony between the sea state and the WEC's dimensions, working principle and PTO. Generally, device developers provide their power matrixes in terms of power output (kW) or efficiency (%) for the different sea states. The most popular metric to characterise the resource at this stage is the Power Output (Po), which measures the energy the WEC can capture and convert given a specific sea state. If the WEC power rating is too high to a magnitude that is rarely available, it will end in significant investment costs in relation to the generated electricity. The wave power output increases with the available power and when its variability is lower. The power transferred from the WEC to the onshore grid for energy consumption is represented by the Delivered Power (P_d). The transport of the ocean power to the onshore grid is usually done through array and subsea electrical systems, substations, and a submarine cable connection to the shore in a process associated with energetic and economic challenges. The energy loss coefficient (η_loss) accommodates transmission losses, wake effects, downtime losses due to maintenance, and technical failures. It has been estimated that these losses can range between 6% to 10% of the power outputting the WEC (Henfridsson et al., 2007). Metrics used in the literature to characterize the wave resource at this technical level have also been referred to as "post-production metrics" (Guillou et al., 2020).

Level 4, or socio-economic potential, goes beyond pure energy potential and considers other social, economic, and environmental criteria influencing the return of a wave farm. Social impacts address various issues ranging from well-being and quality of life to employment and local income. Economic criteria include, for example, water depth and remoteness, which can highly impact life cycle costs by affecting the installation and maintenance cost of a wave energy exploration facility. Environmental criteria address potential impacts associated with a project's activities (manufacture, installation, O & M and decommission) and can be evaluated through techniques such as the Life-Cycle Assessment. Various studies have proposed indicators, including socio-economic criteria, to support the decision-making process, seeking to determine the optimal location to minimize the environmental impact and maximize the socio-economic return. However, it is important to highlight that several uncertainties are still linked to quantifying social and economic parameters of wave energy generation due to the lack of demonstration technologies and real data. Uihlein & Magagna (2016) gave a good classification and review of different criteria at the practicable and socio-economic levels to be considered when performing a complete resource assessment for exploitation.

Various metrics, depicted in Table 1, have been used in the literature to characterise the wave energy resource at each of these levels. A detailed description and reference for each of these metrics are further included in Supplementary Material 1. Although output metrics were often found to be referred to differently in different publications, the same nomenclature has been used to classify them in this review as homogeneously as possible. As inputs to those metrics, raw wave resource parameters able to describe the sea state conditions and its variations in the local of interest are needed (such as the wave spectra or the integrated values of the significant wave height and periods). Historically, different data sources have been exploited, and diverse approaches have been followed to retrieve those intrinsic wave parameters, such as observation and measurements, physics-based numerical simulation, and statistic-based analytical models. An extended overview of those methods can be found in (Ramos-Marin and Guedes Soares, 2024).

Conversely to the main trend (which evaluate wave resource metrics in terms of historical wave conditions), some studies have evaluated the wave resource metrics for the near future by projecting the expected wave parameters in different climate-change scenarios, which better represent the conditions that those devices will encounter when put into operation (Ribeiro et el., 2020, Simonetti and Cappietti 2023).

3   Review on wave energy characterization studies

Existing prospective global and regional assessments of the wave energy resource up to date have been collated. Details about the methodologies used, input data, simulation period, analysed resource level, output metrics and spatial and temporal resolution have been included in this review.

3.1   Global wave resource characterization

One of the first assessments of the global wave energy resource was presented by Kinsman (1965). Based on experimental observations and openly admitted not rigorous guesses, he estimated the global power potential to be around 2 TW, which is still the most popular value in the literature (Reguero et al., 2015). Between 1973 and 2000, several authors performed improved global wave power assessments and came up with values ranging from 0.8 to 3 TW (Inman and Brush, 1973; Isaacs and Seymour, 1973; Panicker, 1976; Quayle and Changery, 1981; Hogben and Dacunha, 1986; World Energy Council, 1993; Pontes, et al., 1998; Krogstad and Barstow, 1999). Most of these global wave energy studies estimated the available power based on visual observations, satellite data, simplified formulations or first and second-generation numerical models and suggested potential locations for energy extraction based on the energy hotspots. From the early 2000 s up to date, most of the research on global resource assessment was based on reanalysis data products outcoming from existing deep and shallow water third-generation simulation models, often validated against available in-situ or remote observations (Ahn et al., 2022; Arinaga & Cheung, 2012; Barstow et al., 2003, 2009; Caires et al., 2004; Caires & Sterl, 2005; Chawla et al., 2013; Chen et al., 2013; Cornett, 2009; Folley et al., 2012; Gunn & Stock-Williams, 2012; Lavidas & Kamranzad, 2021; Law-Chune et al., 2021; Martinez & Iglesias, 2020; Mørk et al., 2010; Reguero et al., 2011, 2015; Ringwood & Brandle, 2015; Rusu & Rusu, 2021; Sasaki, 2017; Sterl & Caires, 2005; Stopa et al., 2013). Results from Gunn and Stock-Williams (2012) estimated that out of the total wave power incident on the ocean-facing coastlines worldwide (≈2.11 TW), the effective extractable power could be about 97 GW considering a state-of-the-art WEC, representing an efficiency of approximately 4.6%. Table S2.1 (Supplementary Material 2) shows detailed specifications of existing global wave energy assessments.

Generally, the main objective of existing research has been to assess the theoretical wave energy potential in terms of traditional parameters, such as average annual significant wave height (Hs), energy period (Te), mean direction (θ_m), and wave power density (Pw). Moreover, there has been a particular focus on generating longer and higher resolution models by hindcasting ocean and atmospheric models or downscaling the updated available data (Sterl et al., 1998; Reguero et al., 2012; Hemer et al., 2013; Rascle and Ardhuin, 2013; Alday et al., 2021).

An idea of the global distribution of Hs, Tp and Pw, resulting from one of the latest worldwide assessments (Kamranzad et al., 2022) is given in Figure 2.

Figure  2  Significant wave height (Hs), energy period (Te) and power density (Pw) estimations from one of the most recent global wave resource assessments (Kamranzad et al., 2022)

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Resource variability has often been evaluated to assess the effects of climate change (Morim et al., 2019). The CoV has been one of the most used metrics to evaluate resource variability. Figure 3 compares the global results of this parameter as given in (Martinez and Iglesias, 2020; Rusu and Rusu, 2021).

Figure  3  Global CoV distribution from most recent global resource assessments

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For the assessment of the future viability of marine energy projects, the extreme events have often been evaluated as well through metrics such as exceedance probabilities, extreme wave heights for a determined return period of years (H₅, H₅₀, H₁₀₀), and Relative Risk ratios (Rr) (Bhaskaran et al., 2023; Neary and Ahn, 2023).

Besides the traditional parameters, several authors proposed the estimation of other less popular or novel metrics to assess the adequacy of the wave resource for exploitation. Examples are Goda's peakedness parameter (Qp), a risk parameter, and the wave directional width (WDW), given in Fairley et al. (2020); the Wave Exploitability Index (WEI) given in Martinez and Iglesias (2020); the Wave Energy Development Index (WEDI), and rate of change (RC), given in Lavidas and Kamranzad (2021); and the frequency-constrained wave power (FP) and the frequency-directionally constrained wave power (FDP) proposed in Ahn et al. (2022).

Using one or a combination of single parameters, Fairley et al. (2020), Martinez and Iglesias (2020) and Ahn et al. (2022) developed a classification system to split the global wave resource into different suitability classes for wave energy exploitation. With the same purpose, Farley et al. (2020) used a K-means clustering method using two sets of input data: a simple set (based on Hs and Tp) and a comprehensive set including a wide range of other relevant wave climate parameters (Qp, extreme events, risk parameter, WDW); Martinez & Iglesias (2020) based their classification on the mean wave power; while Ahn et al. (2022) consider the combination the total wave power density, the FP and the FDP. Kamranzad et al. (2022) re-defined the suitability of global hotspots for wave energy extraction. They are represented by employing the Sustainability Index (SIp), which defines the suitability of the sea conditions for wave farm deployments by relating the mean annual power density, the long-term rate of change, and the variation in the monthly variability index. Figure 4 provides the global suitability distribution for the exploitation of wave energy. Higher values represent better conditions.

Figure  4  Sustainability Index (SIp) estimations from the most recent global wave resource assessment (Kamranzad et al., 2022)

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Although slight differences in wave power estimations exist in publications due to the use of different simulation methods and input data sets, an almost consensual distribution of the overall wave power resource has been observed. The highest wave energy resource is found to be concentrated in latitudes between 40° and 60° in both hemispheres. Thus, latitude is one main factor affecting the spatial variability of the wave power resource (Guo and Ringwood, 2021).

The South Hemisphere is characterized by higher mean annual wave power than the North Hemisphere due to higher seasonal variations and larger continental masses in the latter (which provokes the development of shorter fetches) (Martinez and Iglesias, 2020). Figure 2 shows that the areas with the most significant wave power density are in the temperate zone of the South Hemisphere and cover the offshore regions of southern Australia, New Zealand, South Africa, and Chile. The maximum simulated values occurred in the Southern Indian Ocean, between the Kerguelen Island and the southern coasts of Australia, where Hs rounds 4.5 – 5 m, Te exceeds 9 s and Pw rises over 120 kW/m. The lowest energy resource in this hemisphere is found between the Northern Coast of Australia and southern Indonesia and Papua New Guinea, where the mean power density does not exceed 5 kW/m (Rusu and Rusu, 2021). In most areas of this hemisphere (Southern coasts of Australia, Tasmania, New Zealand and Chile), the predominant contributor to the mean annual wave power density is the primary swell, while in regions such as southern South Africa, the wind waves have a more substantial impact (Arinaga and Cheung, 2012). Regarding the Antarctic continent, even though wave power is a possible energy source for the coastal stations in the future (Mckenzie et al., 2010), there has been barely any interest in evaluating its potential for exploitation due to the great ice-covered extent of the surrounding ocean, and the technical limitations of current exploitation technologies (West et al., 2016).

In the Northern Hemisphere, the highest wave height power density values are found in the North-Atlantic zone, offshore the British Isles, Iceland, and Greenland coasts. Up to 4 m and 90 kW/m of Hs and Pw have been estimated near the Azores archipelago, respectively (Lavidas and Kamranzad, 2021). However, up in the Arctic waters, the substantial diminishing of sea ice has been found to induce local and regional changes in both mean and extreme wave conditions (Christakos et al. 2024). Interestingly, the European Northeast Atlantic region stands out in relation to the Pacific because of the two centres of action that govern the atmospheric circulation in this region: the Iceland Low and the Azores High (Martinez and Iglesias 2020). The Pacific waters surrounding the west coast of Canada, Washington and Oregon also have significant values of Hs (apx. 3 m), Te (apx. 9 s) and wave energy (ranging from 20 to 60 kW/m as latitude increases). Lower levels of Hs and wave power (apx. 2 m and 15–20 kW/m) are found in the Pacific equatorial waters (see Figure 2), with the highest energetic potential in Northern Peru and Ecuador. In the Equatorial waters, mean energy periods reach up to 10 seconds, indicating that some swell waves propagate eastwards through the Pacific and reach the equatorial coasts. The Western Pacific side, covering the coast of Japan and the Russian Bering Sea, is characterized by the highest power resource in the Asian Pacific (with average power values of 20‒40 kW/m). Smaller annual mean values are found at the surrounding waters of south-eastern China, north-eastern Indonesia, and the Philippines (average power densities of 2‒20 kW/m) (Martinez and Iglesias 2020, Rusu and Rusu 2021).

The lowest global values were estimated in the enclosed or semi-enclosed basins (Black Sea, Mediterranean Sea, Baltic Sea, Red Sea, Persian Gulf, etc.), with average power density values rounding between 2 and 13 kW/m (Bozzi et al., 2018, Guillou et al., 2020b), or in sheltered coastal regions like the Gulf of Mexico (mean Pw ≤ 13 kW/m (Guillou and Chapalain 2020)), the Caribbean Sea (mean Pw < 8 kW/m (Guillou and Chapalain 2020)), or the Indonesian inner seas (mean 6 kW/m (Ribal et al., 2020)).

Resource assessments in island territories received special attention due to their isolated nature and their need for energy independence and sustainable development (Rusu and Onea 2019, Ramos et al., 2020). The minimum wave power value among global islands (2.28 kW/m) was estimated close to the island of Sulawesi (Indonesia), compared to a maximum of 68.8 kW/m encountered close to Tasmania (Australia) (Rusu and Onea 2019).

However, some areas characterized by significant power density levels, such as the Western Coasts of Europe, are also characterized by the most significant seasonal wave power variability. This phenomenon makes other regions with lower mean power density, such as the coast of Chile, more reliable for exploitation when considering variability factors (Martinez and Iglesias 2020). Temporal variability is lower around the Equator in the Atlantic, Pacific and Indian Oceans, except for the Arabian Sea, the Bay of Bengal and northern Australia, Indonesia, Malaysia, and the Philippines (Cornett 2009). The highest variability occurs at greater latitudes of both hemispheres, in seasonally ice-covered sites, such as the Beaufort Sea, Sea of Okhotsk, the northern Bering Sea and the waters around Greenland and Australia. However, influenced by the "El-Niño" phenomena, the resource is also unsteady in Central America, the Gulf of Mexico, and the Caribbean Sea (López et al., 2013).

Although offshore regions are more energetic overall than nearshore areas (due to the increase in wave energy dissipation shoreward), offshore locations are often improper for any wave energy project because of the unfeasible considerable distance to shore and small survivability chances. Under the current state of the art, the mean depth of wave energy exploitation using WECs is around 50–60 m (Barstow et al., 2008). Results of the adequacy ranking for wave energy exploitation by Farley et al. and Ahn et al. (Fairley et al., 2020, Ahn et al., 2022) are shown in Figure 5. Figure 5a represents a scale of increasing adequacy from 1 to 22, meaning that locations assigned with one present the highest interest for the wave energy exploitation, and those attributed with 22 the lowest. Figure 5b is given on a scale of 5 classes that decrease in adequacy (class 5 for highest adequacy and class 1 for lowest). The results presented by both authors mostly agree, indicating that the locations with the highest potential for wave energy exploitation, in terms of combined parameters, are those located on the coast of South Africa, Chile, Western Europe, Southern New Zeeland, West and South Australia, West of Canada, and the Gulf of Alaska. Conversely, the coasts showing the lowest potential are those in the Indonesian, Asian and Arabian enclosed seas and gulfs, such as the Arafura Sea, the Gulf of Bothnia, the Persian Gulf or the Yellow Sea. Moderate conditions (scores between 4 ‒ 5 in (Ahn et al., 2022) and between 10‒12 in (Fairley et al., 2020)) have been attributed to coastal areas of Brazil, Argentina, Uruguay, Eastern USA, Northern and Eastern Africa, China, and Japan.

Figure  5  Adequacy ranking for wave energy exploitation by different authors

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Besides the published papers and reports, recently some entities have built up online platforms where wave climate and wave power information can be interactively visualized in a map format and downloaded for different global regions (among other related spatial features). Examples include the Copernicus global database platform (Copernicus Global Database 2022); Marine Energy Atlas by NREL, where wave power and climate data models can be visualized for the United States (NREL 2022); the Australian Marine Energy Atlas, by CSIRO and the Australian Government (Australian Marine Energy Atlas 2022, CSIRO 2022); and the MORE-EST platform which includes data for the European continent (including the Mediterranean and Black Sea) by the University di Torino (MORE-EST 2022).

3.2   Wave resource characterization by continents

An overview of the wave energy resource in the different continents has been synthesized after reviewing over a hundred scientific papers. The highest number of publications reviewed were found to assess the resource in European waters (35%), followed by Asia (25%), North America (12%), South America and Oceania (9%) and Africa (7%), as per Figure 6. Further details about the reviewed publications by continents are given in Tables S2.2 to S2.8 (see Supplementary Material 2).

Figure  6  Regional focus of reviewed publications dedicated to wave energy resource assessments

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3.2.1   North America

In terms of theoretical resources, the most significant wave energy potential in North America is found along the Pacific Northwest Coast of the USA, Canada and the southern coast of Alaska (exceeding 46 kW/m, or 400 MWh/m). Waters along the coast of California and Hawaii have moderate energy compared to those along the Pacific Northwest Coast, on the order of 34 kW/m (300 MWh/m). Southern on the Pacific, the average wave power along the American Samoa's coastal waters was estimated about is 14 kW/m (Garcia-Medina et al., 2023). The waters along the East Coast and Atlantic Ocean side of Puerto Rico are typically below (power densities below 26 kW/m and energy density about 100 MWh/m). The lowest energy, excluding arctic Alaska, occurs in waters in the Gulf of Mexico and along the Caribbean waters of Puerto Rico (average power densities below 10 kW/m and 50 MWh/m) (Robertson et al., 2016; Ahn et al., 2019, 2020). Nonetheless, some studies show that energy harvesting in the Mexican Caribbean is still feasible, especially in the northern coastal area of Cancun, where the power availability averages 45.6 MWh/m/yr (Chávez et al., 2023).

Regarding the temporal variability of the resource, the largest inter-annual oscillations occur within the Bering Sea below the Alaskan Arctic region and the central-eastern Gulf of Mexico. On the other hand, the seasonal variability is highest in the nearshore arctic areas because of the effects of intermittent ice cover. Following this, the Pacific Northwest Coast, the southern coast of Alaska, and the northern coast of Hawaii also present significant seasonal variation. Along the Florida Shelters, the eastern Gulf of Mexico also presents a large variability where the most energetic seas are primarily concentrated in winter. Conversely, the seasonal variation is low in the coastal waters along California. Therefore, despite the Pacific Northwest being a more considerable power resource, coastal California may offer better opportunities with a more reliable and steady energy supply (Ahn et al., 2020).

To provide technical information for technology designers, Ahn et al. (Ahn et al., 2019) created a classification system that involves key resource attributes relevant to the design and operation of a WEC (such as the matching between the most energetic wave period bands of a location with the operating resonant period bandwidth of a WEC technology). According to this classification, the most energetic regions that support utility-scale applications are predominant all along the West Coast, the northern and eastern shores of Hawaii, the southern coast of Alaska extending west along the Aleutians, and offshore locations in the Bering Sea. Second in the classification scale, sites were spotted along the East Coast and the southern portion of the West Coast. Sites attributed with lower classification were found along the Gulf Coast and along the west coast of Alaska and offshore in the Bering Sea above sixty-degrees latitude (Ahn et al., 2019).

On practice, just a few prototypes of WEC have been yet tested in North American waters, and those test sites are all located in USA territories such as Hawaii, Oregon, North Carolina, and New Hampshire (see Section 4).

3.2.2   South america

The geographical distribution of the wave energy resource in South America is strongly associated with latitude. The maximum resource happens on the southern coasts and decreases significantly towards the equator. The importance of latitude in the spatial distribution of wave power is especially obvious on the west coast, especially in Chile, which constitutes the South American country whose coasts receive the highest power carried along predominant swell waves (wave power level increases from 20 to 100 kW/m, as the latitude increases) (Monárdez et al., 2008; Lucero et al., 2017).

Moreover, the variability of the resource is relatively scarce during the various seasons, which makes the Chilenean coast one of the most appealing for the exploitation of wave energy. To get further insights about the technical potential of the resource, an estimate of the output power of some wave energy converters on the market was performed by Monárdez et al. (Monárdez et al., 2008; Mazzaretto et al., 2020). Northwards along the west coast, the wave resource decreases, although relatively significant power can still be found in the coastal waters of Peru, Ecuador and Mexico (Gorr-Pozzi et al., 2021). The rich marine resources along the Chilenean coasts encouraged the Marine Energy Research and Innovation Center (MERIC) creation in 2015.

An assessment of the wave resource in deep waters along the Argentinian coastline and the project's progress of the first WEC in Argentina can be found in (Das Neves Guerreiro and Chandare, 2010).

On the east coast, Brazil is the country receiving the most energetic seas, where the total theoretical potential of wave energy has been estimated to be 91.8 GW along the whole coastline. A substantially lower resource characterizes Argentina, Uruguay, and the northern countries in this hemisphere. Along the Brazilian coast, swell waves are more prevalent and carry more energy in the offshore areas, while wind sea waves dominate the nearshore regions, especially along the northern coast (Sa Cortim et al., 2022). However, the southern coasts of the country (covering the regions of Rio Grande do Sul, Santa Catarina, and Paraná) receive the most energetic waves, with annual average power values estimated at around 21 kW/m (Shadman et al., 2019).

Three ocean renewable energy projects are being carried out in Brazil. One is a prototype of a hyperbaric wave converter installed over a breakwater developed by the Federal University of Rio de Janeiro (UFRJ), which had a full-scale single device of this technology installed in 2011 in Pecém port (Ceará). The device was decommissioned after six months of operation due to the port extension project, but the project is expected to have continuity. Another project is a nearshore wave energy converter at the R & D stage (also by the UFRJ), which is expected to be installed about 25 ‒ 30 m water depth off the Rio de Janeiro coast (Shadman et al., 2019).

A deeper review of the status and future perspectives for harnessing the wave energy in South America is given in (Shadman et al., 2023). The active, decommissioned, and planned projects, research groups and laboratory infrastructures are presented. Despite the great potential for offshore renewable energy on the South American coasts, these resources have not been explored commercially. Thus, larger investment, an adequate legal framework and more full-scale demonstration projects at sea are necessary to keep moving forward.

3.2.3   Oceania

Wave power in Australia is most significant along the southern Australian shelf, covering the states of Tasmania/Victoria, southern Western Australia, and South Australia (with average values exceeding 30 kW/m). The densely populated coasts of New South Wales and Queensland are also found to be potential sites for wave energy harvesting, with moderate levels of average wave power (10–20 kW/m). Time-average wave power for most of the northern Australian shelf was found to be lower than 10 kW/m. Moreover, nearshore wave energy resources are found to be significant and fairly sustained throughout the year for most of the southern Australian states, with the highest mean wave energy power observed during spring and winter (Hughes and Heap, 2010; Morim et al., 2014). Research using currently available WEC prototypes simulated annual electric power at different coastal locations in the southern and southeast regions (Morim et al., 2014; Liu et al., 2023). The LCOE of wave energy on the Australian southern coast is as low as ~100 ＄/MWh, and the capacity factor is as high as ~54%. (Morim et al., 2014).

In New Zealand, results of analysing 20 years of hindcast data pointed at average annual wave power values that range significantly in the marine space, from 28 kW/m (at Greymouth) to almost triple that at Invercargill (78 kW/m). Moreover, techno-economic performance indicators were also identified to rank and determine the optimal device for specific locations on the island (Bertram et al., 2020; Albuquerque et al., 2022).

3.2.4   Europe

Europe has been the continent receiving more interest in wave energy exploration research since the late nineties, when the first broad wave energy resource characterization was developed at the European level using a standard methodology and similar wave data set characteristics (Pontes et al., 1996, 1998). The resulting metrics were made available in a user-friendly interactive software. From this characterization, the European offshore resource was computed to be 320 GW (290 GW in the Atlantic coasts and 30 GW in the Mediterranean).

To increase homogeneity on the atmospheric forcing and improve the spatial and temporal resolution of the coarse initial assessments, the HIPOCAS project was initially reported in 2002 (Guedes Soares et al., 2002; Guedes Soares, 2008). Within this project, a database containing climatological parameters and statistics was developed by several authors or entities, who run the WAM model for up to 44 years and developed wave resource assessments with various fine resolution nested grids (spatial resolution varying between 2° offshore and 0.05° in the coastal areas, and temporal resolutions between 1 and 3 hours), in different regional European seas: the Southern North Sea (Weisse et al., 2002; Weisse and Günther, 2007); a small region in the German Bight (Gaslikova and Weisse, 2006); the Mediterranean basin (Sotillo et al., 2005; Ratsimandresy et al., 2008); the North East Atlantic, including Azores and Canary Islands (Pilar et al., 2008; Iglesias and Carballo, 2010, 2011); the Western Iberian Coast (Rusu et al., 2008), the Black Sea (Cherneva et al., 2008), the Baltic Sea (Cieślikiewicz and Paplińska-Swerpel, 2008); and in the Irish (Vijaykumar et al., 2004).

From these results, several locations in Europe were spotted as locations of great interest for wave energy exploration in terms of power density, especially on the West European Atlantic coast. The most attractive locations have pointed at the coasts of Ireland, UK, France, Galicia (Spain), and Portugal (Gleizon et al., 2017).

In Ireland, a mean theoretical power flux between 50 and 60 kW/m was found on the West Coast, within 25 km of the Mayo and Kerry coasts (ESBI 2005), where the West Wave test site is located. At the local scale, average annual power densities of 50 kW/m and 3 kW/m were estimated at the WestWave, Galway Bay (GBTS) and Killar Point test sites, respectively (Atan et al., 2018). North Ireland presents higher energy values measuring up to 160 kW/m, at the nearshore area of Belmullet (Bento et al., 2011). These values tend to decline quickly when moving toward the Irish Sea at the east, which suffers from the island's shadow effect and where the same parameter was as low as 10 kW/m. Although wind waves are the main contributor to annual average wave power density in some regions of this area (Arinaga and Cheung, 2012), the wave climate off Ireland's North and West coasts was determined to be one of the most favourable environments for potential wave energy exploration.

In the UK, up to 95 TWh/yr of wave energy was estimated to be theoretically possible to extract from offshore sites in UK waters. In contrast, the energy that could practically and economically be extracted was found to be between 32 and 42 TW/yr (Carbon Trust 2012). Studies clearly suggest that both Cornwall and the North and West Coasts of Scotland are the most attractive sites for offshore devices, especially in places such as The Hebrides, Orkney, and Pentland Firth. Near the Hebrides and Shetlands shores, the wave power spatial distribution was estimated to be between 40 and 45 kW/m, with maximum values of up to 650 kW/m. For Orkney, the annual wave power density was estimated between 10 and 35 kW/m (Neill et al., 2014, Venugopal and Nemalidinne 2015). The theoretical and technical wave resource in Scotland, as well as an overview of commercial progress has been examined in (Neill et al., 2017). In the region of Cornwall, several wave power characterizations were deployed as well, with a special focus on the Wave Hub & FAB test sites (Smith et al. 2013, van Nieuwkoop et al., 2013, Fairley et al., 2017), in which various wave energy converters have already been tested (see Section 5). The results showed that the most energetic waves, and therefore the wave power, are more significant in the southwest corner of the region (van Nieuwkoop et al., 2013). The contribution to power levels from the northerly waves decreases moving eastward along the north coast of Cornwall and into the South Wales locations due to the decreased fetch, whereas southerly sea states show increasing levels of power at the Welsh locations (Fairley et al., 2017). Thus, the west side of the Isles of Scilly was characterized by a mean wave power of approximately 30 kW/m, the northwest-facing Cornish coast with approximately 10–25 kW/m, and the southeast-facing Cornish coast with about 2–15 kW/m. The LCOE of wave energy farms in the Irish and western UK waters was estimated by (O'Connell et al., 2020), considering different technology types and the geospatially variable inputs at play. The results reveal areas of high project feasibility off the west coast of Ireland, the Celtic Sea and the Inner Seas off the West Coast of Scotland, with LCOE values below 110 €/MWh along the shores of these areas (O'Connell, 2024).

In the North Sea, which is characterized by shallow waters with a mean water depth of 90 metres, most parts are hardly shaded by the UK. Wave power resource was found to exceed 15 kW/m in very nearshore areas, and it declines steadily when moving southwards, near the English Channel, where the values were found at approximately 5 kW/m. Only the resources in the most exposed northern part of the North Sea were comparable to those of the West European coast. However, the relevance of a softer wave climate and the accessible properties of the North Sea confer beneficial properties for the development and installation of WECs, even if it has been previously overlooked (Lavidas and Polinder, 2019).

In France, most of the research evaluating the wave energy resource was carried out over the French West Coast, in the Bay of Biscay. Results suggest a significant amount of energy resources around Le Croisic, between 25 and 30 kW/m (Mattarolo et al., 2009; Gonçalves et al., 2014a, 2018). Located in the offshore waters of Le Croisic, the grid-connected SEM-REV test site offers operational conditions for WEC and wind turbine demonstrations. However, the Iroise Sea has also been pointed out as one of the most interesting areas for extracting marine renewable energy in France and Europe, despite its heavy marine traffic, fishing activities and recreation. Studies showed that the annual average wave power can reach up to 45 kW/m (Smith and Maisondieu, 2014).

In Spain, the highest energetic area is around the Galician coast, accounting for approximately 35‒40 kW/m of mean wave power in deep waters (Losada et al., 2010; Bento et al., 2012, 2018). The mean wave power density decreases west to east, with the deep-water areas along the Cantabrian Coast receiving around 30 kW/m.

The Basque Country currently counts two wave energy generation test sites: BiMEP (located at the northern coast of Bilbao), and Mutriku (located more eastern between the cities of Bilbao and San Sebastian). BiMEP hosted the first grid-connected offshore wave energy converter in Spain and one of the first in the world, the point absorber MARMOK-A-5 (Thomaz et al., 2019). This device was set up about 4 km offshore and is delivering electrical energy to the grid from December 2016 to June 2019. Thomaz et al. (2019) present an O & M model calibrated with actual data from this wave energy device and estimate socioeconomic indexes, such as the LCOE of this device, for different case studies. On the other hand, the Mutriku is a wave energy generating and testing plant with 14 OWC devices located at a breakwater that came into operation in 2011. It is the only wave farm in the world supplying electricity to the grid about 74.4% of the time, still up to this date. Its main operational aspects, such as its average capacity factor and seasonal variability, have been reported by (Ibarra-Berastegi et al., 2018; Serras et al., 2019).

For the Mediterranean and South Atlantic coast, average wave power values were estimated at 8 kW/m or less. The wave energy was also found to vary from deep water to the shallows, and the coastal shape and bathymetry produced local wave energy concentrations in some areas.

In Portugal, a typical annual average wave power of 25 kW/m was estimated by Pontes et al. (2005), with higher wave heights and power happening at unsheltered sites. The trend identified was that the wave energy is highest in the north and decreases slightly towards the south. The same trend would be later identified in further studies (Rusu and Guedes Soares, 2009; Silva et al., 2013, 2015, 2018; Bento et al., 2014). The efficiency of different WECs along the Portuguese and Galician coasts for a near future scenario was evaluated in (Ribeiro et al., 2020). Results concluded that both the wave power resource and the electric power capacity are expected to decrease in the near future, while the capture width and cost of energy will increase.

Nowadays, a few areas off the Portuguese continental coast serve to support the testing of offshore wave and wind energy prototypes and farms for ocean energy companies. The "Ocean Plug- Portuguese Pilot Zone" was first set up in São Pedro de Moel (Leiria) and later moved to Viana do Castelo (northern coast), where it presently seats in depths between 85 and 100 m (Ocean Plug, 2021). This project was the worldwide pioneer in implementing a maritime zone to install pre-commercial and commercial phases of WECs. A small area about 900 m out of the coast of Peniche is currently hosting an experimental test of the WaveRoller WEC (WaveRoller, 2021), and a cooperative OceanLab in Agucadoura is presently being established to support future marine energy technology experiments.

The wave energy resource is also significant over the European Atlantic Islands (Canary Islands, Madeira, Açores and Iceland). Various authors studied the wave energy potential in the Canary Islands (Chiri et al., 2013; Gonçalves et al., 2014b, 2020; Rusu, 2014; Rodríguez et al., 2015), and determined a significant space variability around the archipelago, with the North and Northeast sides of the islands presenting higher average annual values of available wave energy (20‒32 kW/m), compared to the Southern areas (4‒13 kW/m) (Fernández Prieto et al., 2019).

Regarding the Portuguese territories, detailed assessments resulted on annual average power densities of 30 ‒ 60 kW/m in the Azores (Rusu and Guedes Soares, 2012b; Gonçalves and Guedes Soares, 2021); and an average of 14 kW/m in Madeira Islands (Rusu and Guedes Soares, 2012a). Assessments were also performed to evaluate the practicable resource and the marine space availability for the nearshore and offshore wave energy exploration in the Azorean archipelago (Ramos et al., 2021) and the techno-economic suitability of marine areas around Madeira for the exploration of wave energy (Ramos et al., 2020).

Further up to the north, Iceland and the Faroe Islands are particularly interesting locations for wave energy exploration, as those islands are completely self-reliant and have no interconnections with other countries. In Iceland, the southern areas of the island were found to be more appealing for the deployment of a WEC farm, as the average Pw in four decades was found to be 59 kW/m, significantly higher compared to less the 10 kW/m in the northern areas (Penalba et al., 2020). For the Faroe Islands, the local wave power potential has been analysed by (Joensen et al., 2021), who found the average wave energy flux at nearshore locations to the west and north shores to be 45‒55 kW/m, while significantly lower flux of 10‒25 kW/m was found at eastern locations.

An extended overview of the wave energy resource characterization in Europe refer to (Ramos-Marin and Guedes Soares 2024, Lavidas and Venugopal 2018a).

3.2.5   Africa

The African continent has received, by far, the least interest in wave energy resource assessment (despite Antarctica) due to its less developed energetic framework and economy. However, some authors evaluated the resources on the Moroccan and South African coasts. Ocean wave energy has been found available all over the Atlantic Moroccan coastline (average wave power up to 30 kW/m and average annual wave energy up to 262 MW h/m), with peaks between the regions of Essaouira and Agadir where the wave heights are between 1.9 and 2.13 m (Sierra et al., 2016; Alaoui, 2019). The wave energy is relatively abundant in the region of Casa Blanca as well, with an average annual wave potential of about 22 kW/m (Mouakkir et al., 2022). Nonetheless, the resource is slightly lower than in the neighbouring Canary Islands. A considerable seasonal trend has been found, with the wave energy resource over four times greater in winter than summer (Sierra et al., 2016).

In South Africa, the predominant wave energy is mainly originated from the Southeast swell components. This phenomenon makes nearshore magnitudes of wave power slightly higher for the South-eastern coast (15–20 kW/m) than for the Western coast (5–10 kW/m), where the complex orography increases the non-linear interactions reducing the wave power levels (Lavidas and Venugopal, 2018b). Previous results estimated that the coast of Cape Nature Walker Bay would be the most effective for South Africa's wave energy farm deployments (Wang and Nhieu, 2023).

In the coastal areas of the Cape Verde archipelago, the wave energy potential has also been spotted significantly, with mean wave power densities over 7 kW/m (Bernardino et al., 2017).

3.2.6   Asia

The highest wave energy resource in Asia is concentrated in the Pacific coasts of eastern Japan and the Russian Bering Sea (Hs ≈ 2‒ 3 m, Tp ≈ 7‒ 9 s, Pw ≈ 20‒ 40 kW/m) (Martinez and Iglesias, 2020; Rusu and Rusu, 2021).

In Japan, some areas offshore Kamaishi and Oarai have been catalogued as favourable for wave energy generation, because its average wave density levels (> 10 kW/m) and low seasonality variations. Indeed, WEC tests have already been performed or are planned for these regions adjacent to cities with large energy consumption. Areas near the Izu Island and east of the Ryukyu might also be suitable for installation of a small number of WECs (since the local energy consumption is lower) (Webb et al., 2020).

In the South Korean Peninsula, the average annual resource in different regions has been characterized by Kim et al. (Kim et al., 2012) as follows: Yellow Sea (0.6–13.3 kW/m), Korea Strait (3–9 kW/m) and East Sea (3–8 kW/m). However, it was found that the wave energy is the highest in the vicinity of Jeju Island (7–12 kW/m).

Less energetic seas characterize the coasts of south-eastern China, north-eastern Indonesia, and the Philippines (Hs ≈ 1‒2 m, Tp ≈ 4‒8 s, Pw ≈ 2‒20 kW/m) (Martinez and Iglesias, 2020; Rusu and Rusu, 2021).

Along Chinese coasts, the spatial distribution of ocean wave power is uneven. The wave power density increases from north to south and from the nearshore to the offshore waters. The wave potential is less than 2 kW/m in most areas of the Bohai Sea. The average value for the northern and nearshore areas of the Yellow Sea is 1–2 kW/m, while it is 2–3 kW/m offshore for the southern part. For the East China Sea, the wave power density is generally greater than 2 kW/m around the Zhejiang Province, and for the south part, such as on Dachen Island, it is greater than 3 kW/m. For the northern part of the South China Sea along the coastline of Guangdong Province and Hainan Island, this value is generally between 3 and 5 kW/m (Qiu et al., 2019). From a global perspective, these low values make wave energy development a challenge in China. Thus, different means should be taken to design small-scale WECs suitable for China's low wave power density.

However, wave power density has been found to be remarkable in areas such as the southeast of Vietnam coasts, although with significant intra-annual variability (ranging from 2 to 40 kW/m) (Kamranzad and Lin, 2020). Other areas with more abundant and stable wave power density are in the north-central part of the South China Sea, the Luzon Strait, and southeast of Taiwan (mean annual power ranging from 14.0–18.5 kW/m) (Wan et al., 2015). Mainly Taiwan has been characterized as having the most abundant wave resource in China, which is 4.3 GW, but ocean energy remains relatively unexplored there due to the lack of technological development and special financial support (Wang et al., 2011). Some specific regions, such as Xiashan Island, Nanlu Island, Yun'ao and Zhelang, have been prioritized for the potential exploitation of wave energy because of their relatively higher energy density, lower seasonal variation, small mean range of tide, deep nearshore water, petrous seaboard, and steep slopes. A wave energy testing site (NOITS) is being developed by the National Ocean Technology Center in Weihai (Shandong Province) to facilitate testing scaled wave and tidal energy converters in an open sea environment. The analysis of the wave resource and its spatio-temporal distribution in this site has already been the subject of study by some authors (Fang et al., 2022). For a review of the main achievements of the past several decades, present relevant policies and projects that have been conducted in China refer to (Wang et al., 2011; Qiu et al., 2019).

In Indonesia, mean wave energy has been classified based on meteorological seasons, and it was found that the most energetic months are June, July, and August for all areas of south, southwest and west of Indonesia, where it can exceed 30 kW/m. In some locations like the south of Jawa Island, Bali Island and West Nusa Tenggara, wave energy is available throughout the entire year, while in the region of west Sumatera, promising wave energy is available during the time from March to November (Ribal et al., 2020).

In Malaysia, assessments show that the average wave energy density of the coasts facing the South China Sea ranges from.41 kW/m to 7.92 kW/m (Yaakob et al., 2016).

Finally, studies have evaluated the wave resource along the coasts of India (Sanil Kumar and Anoop, 2015; Sannasiraj and Sundar, 2016; Patel et al., 2020), finding the mean annual wave power along the eastern Indian shelf seas between 2 and 4 kW/m, lower than the mean yearly wave power along the western part (9‒12 kW/m). During the monsoon season, the maximum potential at times reached 30 kW/m (Patel et al., 2020). Three potential sites for harnessing wave energy and its techno-economic feasibility using four different wave energy converters were also identified, pointing at a maximum capacity factor of about 22 – 31% and a minimum LCOE between 354 and 505 €/MWh at selected hotspots (Patel et al., 2022).

An overview of wave energy research in and around the Indian Ocean is given in Alam et al., (2024).

3.2.7   Enclosed and semi-enclosed basins

Enclosed and semi-enclosed basins represent the least energetic seas globally, where waves are often small, short-crested, and strongly dependent on wind forcing, as limited space and fetch lengths prevent waves from evolving to swell.

However, although characterized by low wave power density levels, existing research states that the wave energy can be successfully exploited if properly downscaling some state-of-the-art WEC technologies (Bozzi et al., 2018). Consequently, the wave resources in these basins have been the object of analysis in several studies (see Supplementary Material 2).

Estimates in the Black Sea indicate approximate values of time average power density between 1.6 and 6 kW/m and significant wave height between 0.6 and 1m (Akpınar et al., 2017; Rusu 2018). The Baltic Sea presents an average annual Hs < 1.5 m and Pw ≈ 0.7‒1.5 kW/m (Björkqvist et al. 2014, 2018). In the Red Sea, average power density levels of about 4.5 kW/m were estimated (Aboobacker et al., 2017). The Persian Gulf in western Asia represents mean power density values below 2 kW/m (Goharnejad et al., 2021).

In the Mediterranean Sea, waves have been characterized by average Hs ranging from 0.05‒1.2 (Soukissian et al., 2017) 5 and Pw ≈ 2‒12 kW/m. Nonetheless, all Mediterranean basin is characterized by a strong variability on monthly base, which results in relevant fluctuations on a seasonal base.

Several studies have evaluated the wave resource for energy exploitation across the Mediterranean basin (Liberti et al., 2013; Besio et al., 2016; Soukissian et al., 2017; Lavidas et al., 2016, 2018a; Bozzi et al., 2018; Ferrari et al., 2020; Acar et al., 2023). Some of them focused specifically in one of the internal regions or seas: Balearic Sea (Sierra et al., 2014; Ponce de Leon et al., 2016), Ligurian Sea (Lira-Loarca et al., 2022), Sea of Sicily (Monteforte et al., 2015), Eastern Mediterranean (Ayat, 2013), Ionian and Aegean Seas (Emmanouil et al., 2016; Jadidoleslam et al., 2016; (Lavidas & Venugopal 2017a; Kozyrakis et al., 2023), the Levantine Basin (Zodiatis et al., 2014), and the African coasts of Algeria and Libya (Amarouche et al., 2020; Lavidas & Venugopal, 2017b). Generally, the average wave energy flux in the Mediterranean ranges from a few kW/m in the less dynamic regions (Alboran Sea, Adriatic Sea, Aegean Sea) to over 10 kW/m in the Central Mediterranean, specifically between the Balearic Islands and Sardinia. Certain areas, such as the Eastern Mediterranean, can be considered moderately energetic, exhibiting values of the available energy flux between 6 and 9 kW/m (Besio et al., 2016). Although the area extending between Sardinia and the Balearic Islands has been historically characterized as the most energetic in the Mediterranean, this area represents a quite low efficiency for WECs because extreme and rare events provide a large part of the available energy (Soukissian et al., 2017; Bozzi et al., 2018). Conversely, coastal areas in the Gulf of Lion, the Sicily channel, the Alboran Sea, the Libyan coast, Crete and Cyprus represent the best performance for scaled WEC technologies (Bozzi et al., 2018). Interestingly, the exploitation of coupled offshore wind-wave energy in the region of the Algerian Coast has been found especially advantageous over the sole exploitation of one energy type, as it lowers the variability of the available resource (Ferrari et al., 2020).

In the Gulf of Oman, the spatial distribution of wave power increases from west to east towards the Indian Ocean and the surroundings of the port of Chabahar is suggested as the best area for the installation of a wave farm (Saket and Etemad-Shahidi, 2012; Kamranzad et al., 2016a; Pourali et al., 2023). Finally, in the Caspian Sea (located between Asia and Europe), the richest area of wave energy potential is in the central part of the southern sea, with maximum values of 1.5 kW/m of mean wave power (Kamranzad et al., 2016b). Due to those low levels of wave power, wind energy resources have been found to have a greater potential in the coastal environment (Rusu and Onea, 2013).

4   World test facilities

Throughout the last decades, several test sites included in Figure 7 have been globally established to support the actual testing of different WEC devices and prototypes in the open sea. Extended details about the spatial characteristics of the test sites, wave resource characterizations and status are included in Table S3.1 (Supplementary Material 3). Further information can also be found in (SOWFIA 2011, Aderinto and Li 2019, May-Varas and Robertson 2020) and (Tethys, 2022a).

Figure  7  World wave energy test sites

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Recently, a data platform known as MARENDATA (Hidromod, 2020) has been made available, enabling access to a marine energy resource repository and impact assessment raw data from different test sites within the European NE Atlantic region. It can be used to find detailed information on a particular marine energy project test site or to view data regarding one or multiple environmental parameters at different test centres. Similarly, another open access tool has been created, which permits interactive assessment of the suitability of wave energy projects in different European regions in terms of the potential impacts that they can cause, and other criteria related to the practicable potential of the wave resource. It is named WEC-ERA and has been built within the scope of the WESE project (WESE Project, 2021). The tool visualises the pressures and ecological risks of three different wave energy converter technologies during their life-cycle stages–from installation to operation and decommissioning.

5   Conclusions

The main approaches and metrics used for the wave energy resource characterization for exploitation at different levels have been reviewed, as well as existing global and continental wave energy resource assessments and wave energy test sites around the world.

Most of the existing research has focused on describing the wave energy potential at the theoretical level of the resource. Although early wave characterizations relied on observed in-situ data from buoys and other measurement devices, nowadays, numerical modelling has become the most popular methodology for wave resource assessment. Satellite imagery has also increased in popularity and is expected to become more used as the frequency and coverage of satellite imagery expands. Numerical modelling allows the computation of spectral or integrated wave parameters (wave height, period, and direction), which are fundamental metrics in every resource assessment. Those parameters have further been used to compute a wide variety of adequacy indexes and metrics for wave energy exploitation. No specific metric has yet been established as preferred for the evaluation of the wave energy resource to determine an adequate location and technology for energy exploitation. However, a significant part of existing research converges into determining the available wave power density to theoretically evaluate the wave energy resource. Bivariate occurrence diagrams, coefficient of variation, and temporal variability indexes have also been rather common metrics at this level. This convergence allows to compare and evaluate the resources in different regions.

Nonetheless, when it comes to analysing the potential of the wave energy for exploitation purposes, the computation of metrics at the theoretical level is not sufficient, especially in wave farm feasibility and design assessments at local scales. Other performance metrics and indexes at the practicable, technical, and socio-economic levels should be computed in both spatial and temporal domains at a sufficient resolution to accomplish a comprehensive wave resource assessment for exploitation. Marine spatial planning techniques are frequently needed to explore marine space availability to exploit wave energy at a practicable level. The net wave power output, the capacity factor, and capture width are some of the metrics most frequently assessed at the technical level, and the levelized cost of energy is the most conventional index at the socio-economic level. Recent publications have considered different index classification systems and multi-criteria techniques as useful approaches that enable the creation of spatial rankings of adequacy and the combined consideration of different metrics belonging to different resource levels.

The temporal and spatial variability of such metrics should also be carefully analysed, as it greatly influences the adequacy of a region for wave energy exploitation. Although in recent years, modelling approaches have become more sophisticated and efforts have been made towards the standardization of numerical simulations to perform appropriate wave resource and climate characterizations (such as the specifications proposed by the IEC-62600-101), a great number of studies still do not comply with the specified input data span, or with the temporal, spatial and frequency resolutions. The use of short-term datasets increases intra-annual and decadal variation uncertainties. Similarly, coarse characterizations are not appropriate for capturing the spatial variations of the wave resource at nearshore and local scales, especially at irregular bathymetries and coastal geography.

Consensually, existing global research points at global temperate regions of both hemispheres as those where the highest wave power density is concentrated. The South Hemisphere has been characterized by slightly higher mean annual wave power than the North Hemisphere, and the areas where the largest wave power density occurs are located at offshore regions of southern Australia, New Zealand, South Africa, Chile, North-west Europe, Iceland, and Greenland those characterized by the highest power densities. The lowest wave energy density is attributed to the Pacific equatorial waters and the enclosed and semi-enclosed basin.

Nonetheless, when considering other metrics at the practicable, technical, and socio-economic level (and their temporal and spatial variability), some references have suggested that regions previously neglected due to their perceived "milder" theoretical resource may, in fact, constitute "hidden opportunities" where wave farms could show better performance than other regions, especially if considering the proper scalation of wave energy converters.

Although great efforts have been put into wave energy exploration research and several wave energy converters have already been tested in the open sea, no convergence yet exist towards the most efficient technology. Thus, the exploitation of wave energy is still not matured in terms of grid integration, mass production, and, thus, far-off commercialization.

Overall, regions within the European Union have received the most significant interest in wave energy exploration research (encouraged by governmental interest and special public funding). Moreover, Europe has led the progression towards commercialising wave energy as it has the most significant number of wave energy test sites. Conversely, research in coastal regions of less developed or populated areas, such as middle Africa and Antarctica, is relatively scarce.