Variability Of Wave Power Research Articles

Integrated assessment of offshore wind and wave power resources in mainland Portugal

This study presents a comprehensive analysis of offshore wind and wave energy resources in mainland Portugal, aiming to facilitate sustainable energy exploitation. The study integrates the spatial distribution and temporal variability of those energy resources, as well as the interplay between wind and wave patterns and co-location feasibility. A 44-year dataset (1979–2022), derived from ERA5 reanalysis wind and SWAN wave model across the concession zones designated by the Portuguese government (labelled as P1 to P6) are utilised. The results indicate promising prospects for wind and wave power densities in these zones, emphasising the suitability of the offshore renewable energy extraction. Additionally, analysis revealed fluctuations in wind and wave power variability among the selected locations, with concession zone P3 (Leixões) emerging as a promising candidate due to its relatively lower variability and stable distribution patterns of both resources. The analysis on co-location feasibility demonstrated the potential for efficient energy extraction in location P5 proving to be the most favourable in wind-wave resource integration. Moreover, time lag analysis highlighted opportunities for optimising energy capture efficiency. Overall, this study provides valuable insights into the sustainable exploitation of wind and wave power resources, contributing to deliver informed decision-making for renewable energy investment.

Role of Atmospheric Indices in Describing Shoreline Variability Along the Atlantic Coast of Europe

AbstractBeaches are highly variable environments and respond to changes in wave forcing, themselves modulated by climate variability. Here, we analyze three high‐quality beach profile data sets to robustly investigate, for the first time, the link between shoreline change, wave forcing and climate variability along the Atlantic coast of Europe. Winter wave conditions are strongly associated with North Atlantic Oscillation (NAO) and Western Europe Pressure Anomaly (WEPA), with WEPA explaining 50%–80% of the winter wave power variability. Shoreline variability during winter is also strongly linked to NAO and WEPA, with WEPA explaining 25% of the winter shoreline variability. Winter wave conditions and associated shoreline variability are both unrelated to El Nino Southern Oscillation. In addition to the atmospherically‐forced beach morphological response, shoreline change also depends strongly on the antecedent morphology as evidenced by significant correlations between summer/winter shoreline response and the shoreline position at the start of each season.

Impact of leading Indo‐Pacific climatic modes in modulating the wave power variability and their trends in the North Indian Ocean

AbstractThe present study analyses the trend and variability in wave parameters (wave height and wave period) and wave power (WP) in the North Indian Ocean (NIO). The impact of climatic modes such as El‐Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on the WP of NIO has been investigated using the European Centre for Medium‐Range Weather Forecasts reanalysis datasets (ERA5) for the period 1959–2021. It is observed that along the west coast of India (WCI), the coastal WP increased from south to north during summer whereas, in winter and other seasons the WP increased from north to south. Instead, along the east coast of India (ECI), WP is higher on the north than the south, always. The annual WP climatology along the Indian coasts reveals that WP potential is higher along/adjacent to WCI than the ECI. It was observed that the total significant wave height (SWH) WP anomalies during normal and positive IOD (pIOD) events are mainly dominated by swell WP, whereas during El Niño and combined ENSO‐IOD events, dominated by wind seas. During the peak of pure El‐Niño, the SWH WP shows a basin‐wide increase in WP anomalies. However, during summer, SWH WP showed increasing trends over Bay of Bengal. It is evident from the composite analysis that annual averaged WP anomalies are decreasing in normal, pure pIOD and combined events, but El‐Niño is found to increase the WP anomalies over the Arabian Sea in the region north of 20°N. The present study advocates that a detailed analysis of WP along the Indian coastal regions is beneficial to the renewable energy industries to utilize this as an important energy resource.

Inter- and intra-annual wave energy resource assessment in the south-western Black Sea coast

This study focuses on the inter- and intra-annual variation in theoretical wave power along the south-western coast of the Black Sea. Long-term (1979–2009) hindcast developed using the calibrated three-layer nested SWAN model was used for a detailed assessment of wave energy resource. Annual change, monthly and seasonal wave power variability indices were evaluated, and the Optimal Hotspot Index (OHI) was calculated for 62 sites along the coast to rate the hotspot locations. The assessment shows the highest wave energy resources in western Karaburun with higher variability. However, the western Sinop sites have lower wave energy resources compared to western Karaburun sites, in spite of considering the lower variability, these sites are more appropriate for wave energy extraction. The location with the highest potential (KA5 100 m depth) has an average of 8.4 kW/m and a maximum of 1015 kW/m wave power capacity. The east sites of Sinop and Filyos are comparatively less dynamic. Moreover, it was found that the average peak values of wave heights are in February, and the lowest sea state was in June. 2003 was the most, and 1989 was the least energetic years in the 31-year period.

Impacts of Global Climate Change on the Future Ocean Wave Power Potential: A Case Study from the Indian Ocean

This study investigates the impacts of global climate change on the future wave power potential, taking Sri Lanka as a case study from the northern Indian Ocean. The geographical location of Sri Lanka, which receives long-distance swell waves generated in the Southern Indian Ocean, favors wave energy-harvesting. Waves projected by a numerical wave model developed using Simulating Waves Nearshore Waves (SWAN) wave model, which is forced by atmospheric forcings generated by an Atmospheric Global Climate Model (AGCM) within two time slices that represent “present” and “future” (end of century) wave climates, are used to evaluate and compare present and future wave power potential around Sri Lanka. The results reveal that there will be a 12–20% reduction in average available wave power along the south-west and south-east coasts of Sri Lanka in future. This reduction is due mainly to changes to the tropical south-west monsoon system because of global climate change. The available wave power resource attributed to swell wave component remains largely unchanged. Although a detailed analysis of monthly and annual average wave power under both “present” and “future” climates reveals a strong seasonal and some degree of inter-annual variability of wave power, a notable decadal-scale trend of variability is not visible during the simulated 25-year periods. Finally, the results reveal that the wave power attributed to swell waves are very stable over the long term.

Impact of Climate Change on Wave Energy Resource in the Mediterranean Coast of Morocco

The increasing demand for energy and the impacts generated by CO2 emissions make it necessary to harness all possible renewable sources of energy, like wave power. Nevertheless, climate change may generate significant variations in the amount of wave energy available in a certain area. The aim of this paper is to study potential changes in the wave energy resource in the Mediterranean coast of Morocco due to climate change. To do this, wave datasets obtained by four institutes during the Coordinated Regional Climate Downscaling Experiment in the Mediterranean Region (Med-CORDEX) project are used. The future conditions correspond to the RCP4.5 and RCP8.5 scenarios from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The results show that projected future wave power is very similar to that of the present considering the whole area, although at some specific points there are slight changes that are more evident for the RCP8.5 scenario. Another remarkable result of this study is the significant increase of the temporal variability of wave power in future scenarios, in particular for RCP8.5. This will be detrimental for the deployment of wave energy converters in this area since their energy output will be more unevenly distributed over time, thus decreasing their efficiency.

Evaluation of spatio-temporal variability of ocean wave power resource around Sri Lanka

The paper presents a detailed analysis of the spatio-temporal variability of wave power resource around Sri Lanka, using computationally simulated 25 years of wave data that represents the prevailing ocean climate in the region. The computational wave model was validated against a measured wave dataset collected over a 44-month period at 70 m water depth off the coast of the south-west of Sri Lanka and ERA-Interim Reanalysis wave data and, good agreement found. The analysis reveals that the ocean around Sri Lanka from the south-west to south-east have a substantial wave power resource. The available offshore wave power resource remains between 10 and 20 kW/s throughout the year although it is significantly modulated by the south-west monsoon which falls between May and September thus increasing the power up to around 30 kW/m. The inter-annual to decadal scale variability of wave power resource remains small. Wave power reduces when waves travel from the margin of the narrow continental shelf around Sri Lanka to shallow water areas closer to the shoreline. A significant longshore variability of wave power is also observed where the south-west coast of Sri Lanka has the highest available power under the prevailing ocean climate.

Assessment of wave power variability and exploitation with a long-term hindcast database

Numerical investigations dedicated to the impact of wave power variability on energy conversion were mainly conducted in the European shelf seas where a considerable amount of technological devices was developed. We complemented these studies by exploiting a 31-year consistent hindcast database of the wave climate, assessed against observations in 41 locations, in the North-West Atlantic, the Gulf of Mexico and the Caribbean Sea. With an exception in the Caribbean Sea where wave power density increased under the influence of an easterly zonal wind, a clear contrast was exhibited in the available wave energy flux between the oceanic energetic regions of the North-West Atlantic and the semi-enclosed basins, protected from incoming waves conditions by a series of islands. The analysis revealed furthermore contrasting wave climates characterized by (i) significant temporal variability in the Gulf of Mexico and the northern oceanic region off the USA East Coast, and (ii) more moderated variations in the Caribbean Sea off Colombia and the southern oceanic area off the Lesser Antilles. A generic method, independent from the device technology, was finally adopted to assess the effects of resource variability on energy output and converters performances. The area off the Lesser Antilles appeared particularly interesting to supply, at reduced installed capacity but with more regular waves conditions, renewable energy within surrounding island territories.

Projection of spatiotemporal variability of wave power in the Persian Gulf by the end of 21st century: GCM and CORDEX ensemble

This study investigates future variability of wave power in the Persian Gulf. The contribution of this paper is twofold: (a) to evaluate spatiotemporal resolutions, downscaling techniques and global circulation model (GCM) selection impacts running multi-climate models, and (b) to project wave energy resources and its variability by the end of 21st century using RCP4.5 and RCP8.5 as two different representative concentration pathways (RCPs). The SWAN (Simulating Waves Nearshore) model forcing with near surface wind components was employed for wave simulation. The numerical wave model was calibrated and validated using wave measurements by two buoys prior to wave energy computations. The results of wave models obtained from different climate models showed a wide range of variety for different climatic resources associated with GCM selection, temporal and spatial resolutions and downscaling approach. Outputs of the wave model forcing with 3 hourly wind data of CMCC-CM and CORDEX-MPI (Max Plank Institute) with daily temporal resolution were recognized as the models with the best performance. Using a weighted average of these two models, the wave characteristics were obtained and wave energy were computed for the historical and future periods. Temporal distribution of energy shows highly intra-annual and seasonal variability when the mean wave power for the strongest month exceeds 1000 Watt per meter that is 10 times higher than the mean wave power in the weakest month. Similarly, a strong spatial variability in wave power distribution was revealed where the middle part of the Gulf has found to have the highest energy and the eastern and northwestern regions have the lowest energy. The projections illustrated a decreasing trend on future wave energy up to 40% in the Iranian coastlines and lower rate of changes in the southern stripe of the study area.

The Changes of Theoretical Wave Power from Offshore to Coast in the South-western Black Sea

This study concentrates on the changes of theoretical wave power from offshore to coastal regions of south-western Black Sea. The investigation also offers a long-term (31-year) wave power quantification analysis between 1979 and 2009 using the SWAN version 41.01AB numerical wave model. The wave resource assessment is performed in terms of its seasonal and monthly variability of wave power, annual wave power directional distributions and the comparison of the maximum and median values of some important wave power parameters in the west of Istanbul a major city in Turkey that straddles Europe and Asia across the Bosphorus Strait. For this analysis, 10 point locations distributed on two perpendicular lines (KA and KE) to the coastline with five different depths (5, 25, 50, 75, and 100 m) in the areas of interest were selected. The data needed was extracted from the dataset produced by [1, 2] using a calibrated nested layered wave hindcast model SWAN forced with CFSR winds. The results show that the wave energy resource in the study area is high, and the potential locations can be considered for extracting wave electrical power.

Changes in Wave Energy in the Shelf Seas of India during the Last 40 Years Based on ERA5 Reanalysis Data

Ocean wave energy is one of the cleanest renewable energy sources around the globe, but wave energy varies widely from place to place and from time to time. The long-term variability of wave power at 20 locations in the Indian shelf seas from 1979 to 2018 is described here using the European Centre for Medium-Range Weather Forecasts recently released ERA5 reanalysis hourly data. The variability is calculated on a yearly and monthly basis for the locations based on the coefficient of variation. The annual average wave power varied from 2.3 (at location 16 in the western Bay of Bengal) to 11 kW/m (at location 2 in the northeastern Arabian Sea). Along the western shelf seas, the maximum value of wave power is during the southwest monsoon period and along the east coast, it is during the tropical cyclone period. The standard deviation in wave power is more than the mean value at locations along the northern shelf seas of India, indicating a large variability in wave power in an annual cycle. The west coast locations are shown to have a slightly higher increasing trend with an average of 0.024 kW/m per year, while the increasing trend in wave power of east coast locations is with an average of 0.015 kW/m per year. The study also examines the variation in wave power from deep to shallow water at 2 locations using the wave characteristics obtained from the numerical model SWAN. The electric power output from a few wave energy converters are calculated for all the locations and found that the southernmost locations have a steady and higher percentage of power production.

Quantification of Swell Energy and Its Impact on Wetlands in a Deltaic Estuary

The extensive coastal wetlands in Mississippi River Delta represent the seventh largest deltaic floodplain in the world, contributing to many services that sustain the economies of the region. Subsidence, sea level rise, saltwater intrusion, wave action from storms, and sediment depletion have contributed to chronic wetland losses, converting vegetated lands into open waters and increasing wind fetch. Among these factors listed, wave energy plays the largest role in marsh edge erosion in an open bay environment. Degrading barrier islands along the shoreline of this delta allow swell energy to enter protected bay areas, contributing to marsh edge erosion. Locally generated wind waves within enlarged bays also contribute to wetland loss. Quantifying the roles of swell and wind waves in marsh edge erosion is essential to any ecosystem restoration design. In this study, a numerical model is implemented to describe the wave climate of combined swell and wind waves in a deltaic estuary. Terrebonne Bay was chosen as the study area because it has experienced one of the largest reductions in barrier islands and wetland loss rates among Louisiana estuaries. A continuous wave measurement in upper Terrebonne Bay was obtained over the course of a year. A spectral wave model is used to hindcast the wave climate in the estuary. The model results are compared against the in situ wave measurement. The wave power is partitioned into swell and wind sea at different locations in Terrebonne Bay using the model results. An extensive analysis on a valid effective wave power range that directly impacts the marsh edge is performed and presented. Insight into the temporal and spatial variability of wave power is gained. Through differentiating swell and wind sea energies around the bay, improvements of long-term wave power computation for shoreline retreat prediction are made. It is found that the swell energy becomes the primary driver of marsh edge retreat in the southwest part of Terrebonne Bay as the barrier islands are degrading.

Decadal variability of wave power production in the North-East Atlantic and North Sea for the M4 machine

We look at the variability of the power produced by the three-float M4 wave energy converter for locations in the North-East Atlantic and North Sea using the NORA10 hindcast data from 1958−2011. The aim is to investigate whether the produced power is also strongly affected by the climate variability (such as the North Atlantic Oscillations) in the winter, just as the ocean wave power resource as observed in previous studies. In this study, we demonstrate the use of proxy indices in combination with the climate indices to reconstruct a historic practical wave power climate from 1665−2005. We also conduct sensitivity studies to assess the changes in the practical wave power variability in response to perturbing the machine size, the power take-off coefficient, the response bandwidth and the power limit of the power take off. We find that the resultant temporal variation is still dominated by the climate variability. However, the overall variability important for power availability and energy supply economics is smaller than that of the ocean wave power resource because of the finite capture bandwidth of the M4 machine. The statistical methodology presented here is also potentially relevant to other wave energy converters in similar locations.

Decadal wave power variability in the North‐East Atlantic and North Sea

AbstractEstimation of the long‐term behavior of wave climate is crucial for harnessing wave energy in a cost‐effective way. Previous studies have linked wave heights to the north‐south atmospheric pressure anomalies in the North Atlantic, suggesting that the wave climate fluctuates as a response to changes in zonal circulation in the atmosphere. We identify changes in wave power in the North‐East Atlantic that are strongly correlated to the dominant pressure anomalies, the North Atlantic Oscillation (NAO), and other modes. We present a reconstructed wave power climate for 1665–2005, using a combination of known and proxy indices for the NAO and other modes. Our reconstruction shows high interannual and multidecadal variability, which makes wave energy prediction challenging. This variability should be considered in any long‐term reliability analysis for wave energy devices and in power scheme economics.

Wave power variability and trends across the North Atlantic influenced by decadal climate patterns

AbstractClimate variations influence North Atlantic winter storm intensity and resultant variations in wave energy levels. A 60 year hindcast allows investigation of the influence of decadal climate variability on long‐term trends of North Atlantic wave power, PW, spanning the 1948–2008 epoch. PW variations over much of the eastern North Atlantic are strongly influenced by the fluctuating North Atlantic Oscillation (NAO) atmospheric circulation pattern, consistent with previous studies of significant wave height, Hs. Wave activity in the western Atlantic also responds to fluctuations in Pacific climate modes, including the Pacific North American (PNA) pattern and the El Niño/Southern Oscillation. The magnitude of upward long‐term trends during winter over the northeast Atlantic is strongly influenced by heightened storm activity under the extreme positive phase of winter NAO in the early 1990s. In contrast, PW along the United States East Coast shows no increasing trend, with wave activity there most closely associated with the PNA. Strong wave power “events” exhibit significant upward trends along the Atlantic coasts of Iceland and Europe during winter months. Importantly, in opposition to the long‐term increase of PW, a recent general decrease in PW across the North Atlantic from 2000 to 2008 occurred. The 2000–2008 decrease was associated with a general shift of winter NAO to its negative phase, underscoring the control exerted by fluctuating North Atlantic atmospheric circulation on PW trends.

Wave power variability and trends across the North Pacific

Multiyear climate variations influence North Pacific storm intensity and resultant variations in wave energy levels. The timing of these decadal fluctuations and strong El Niño's have had a strong influence on long‐term trends. Here we investigate variations in the North Pacific wave power, PW, determined from WAVEWATCH III (WW3) wave model significant wave height, Hs, and peak period data forced by NRA‐1 winds spanning the 1948–2008 epoch. Over the entire hindcast, upward trends in Hs and PW, especially in winter, are observed over much of the North Pacific, strongly influenced by an apparent storm intensification after the mid‐1970s regime shift. Heightened PW is concentrated in particular regions of the basin, and is associated with increased wave activity during the warm phase of the Pacific Decadal Oscillation (PDO). Wave power events, PE, defined as episodes when Hs exceeded the 90th percentile threshold for at least 12 h, exhibit significant upward trends along much of the U.S. Pacific coast during winter months. Importantly, the hindcast exhibits a recent decrease in PW across much of the North Pacific, in contrast to the long‐term increase of PW and Hs. This recent decrease is associated with the prevalent PDO cool phase that developed after the late 1990s. Variability and intensification of coastal PW and PE have important practical implications for shoreline and beach erosion, coastal wetlands inundation, storm‐surge flooding, and coastal planning. These considerations will become increasingly important as sea level rises.

A Preliminary Assessment of the Competitiveness of Wave Energy Technologies: A Regionally Detailed Analysis

In this paper, a regionally disaggregated global energy system model treating the electricity supply sector in detail is used to examine the competitiveness of wave energy technologies for each of 48 world regions over the period to 2050 under a constraint of halving global energy-related CO2 emissions in 2050 compared to the 2000 level. It is first found that wave energy continues to be uncompetitive until 2050 due to (1) its high cost and (2) the large seasonal variability of wave power. Even if the reference wave electricity generation costs are assumed to be reduced by 90%, the latter factor severely limits the market penetration of wave energy technologies. It is then found that the UK and Ireland, Australia and New Zealand, Japan, South Africa, the western US, Latin America, Canada, and Spain and Portugal are the regions promising for wave energy deployment. Not only low-cost and abundant wave energy resources, but also the peak electric load in winter, the relatively small seasonal variability of wave power, and/or the low competitiveness of power sources substitutable by wave energy are the reasons for this.

Wave power variability over the northwest European shelf seas

Regional assessments of the wave energy resource tend to focus on averaged quantities, and so provide potential developers with no sense of temporal variability beyond seasonal means. In particular, such assessments give no indication of inter-annual variability – something that is critical for determining the potential of a region for wave energy convertor (WEC) technology. Here, we apply the third-generation wave model SWAN (Simulating Waves Nearshore) at high resolution to assess the wave resource of the northwest European shelf seas, an area where many wave energy test sites exist, and where many wave energy projects are under development. The model is applied to 7years of wind forcing (2005–2011), a time period which witnessed considerable extremes in the variability of the wind (and hence wave) climate, as evidenced by the variability of the North Atlantic Oscillation (NAO). Our simulations demonstrate that there is much greater uncertainty in the NW European shelf wave resource during October–March, in contrast to the period April–September. In the more energetic regions of the NW European shelf seas, e.g. to the northwest of Scotland, the uncertainty was considerably greater. The winter NW European shelf wave power resource correlated well with the NAO. Therefore, provided trends in the NAO can be identified over the coming decades, it may be possible to estimate how the European wave resource will similarly vary over this time period. Finally, the magnitude of wave power estimated by this study is around 10% lower than a resource which is used extensively by the wave energy sector – the Atlas of UK Marine Renewable Energy Resources. Although this can partly be explained by different time periods analysed for each study, our application of a third-generation wave model at high spatial and spectral resolution significantly improves the representation of the physical processes, particularly the non-linear wave-wave interactions.