Modelling Wave Energy Resources in the Irish West Coast

2011 ◽  
Author(s):  
A. Rute Bento ◽  
Paulo Martinho ◽  
Ricardo Campos ◽  
C. Guedes Soares
Keyword(s):  
Wave Energy ◽  
West Coast ◽  
Wave Climate ◽  
Extensive Study ◽  
Wave Power ◽  
Target Area ◽  
Wave Models ◽  
The Time Domain ◽  
Validation Tests ◽  
Buoy Data

In order to assess the potential wave energy extraction, a study is made to validate a model that can be used to characterize Ireland’s wave climate in a more extensive study. The target area is the Irish West Coast, known for having the highest average wave power in Europe. The wave conditions in the coastal area were characterized by coupling the wave models SWAN and WAVEWATCH III. Validation tests are carried out with buoy data so that the model’s performance can be evaluated. The wave parameters considered for the comparisons in the time domain are significant wave height and mean period, and the spatial distribution of wave energy is examined in a case study. Theoretical values of wave power are obtained for sites close to the coast and in particular for the two tests sites of Galway and Belmullet.

scholarly journals Modeling Sea Ice Effects for Wave Energy Resource Assessments

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3482
Author(s):  
Ruth Branch ◽  
Gabriel García-Medina ◽  
Zhaoqing Yang ◽  
Taiping Wang ◽  
Fadia Ticona Rollano ◽  
...  
Keyword(s):  
Sea Ice ◽  
Wave Height ◽  
Wave Energy ◽  
Numerical Models ◽  
Energy Resource ◽  
Wave Climate ◽  
Wave Power ◽  
Wave Energy Converters ◽  
Wave Models ◽  
Mean Square Errors

Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

A Detailed Investigation of the Nearshore Wave Climate and the Nearshore Wave Energy Resource on the West Coast of Ireland

2013 ◽  
Author(s):  
Sarah Gallagher ◽  
Roxana Tiron ◽  
Frederic Dias
Keyword(s):  
Wave Energy ◽  
West Coast ◽  
Energy Resource ◽  
Wave Model ◽  
Wave Climate ◽  
Western Coast ◽  
Climate Data ◽  
Offshore Area ◽  
Medium Range Weather Forecast ◽  
Maintenance Activities

The western coast of Ireland possesses one of the highest wave energy resources in the world and consequently is a promising location for the future deployment of Wave Energy Converters (WECs). Most wave climate studies for this region have focused primarily on the offshore area since it enjoys higher energy densities. However, recent studies have shown that nearshore locations offer a similar potential for the exploitation of wave energy as offshore sites [13]. Furthermore, the proximity of WEC devices to the shore will likely reduce losses in power transport, and facilitate access for maintenance activities. In this context, we analyse the wave climate over a ten year period for several nearshore sites off the Irish West Coast. The wave climate is estimated using a spectral wave model, WaveWatch III, forced with wind and spectral wave data from the ECMWF (European Centre for Medium Range Weather Forecast) operational archive. The wave model is validated with wave buoy data from intermediate to shallow depths (< 60 m). Our focus is on two aspects of the wave climate resource assessment. Firstly, we characterise the directionality of the wave energy resource (mean direction, directional spread) which affects the site selection, design and performance of nearshore WECs. Secondly, we discuss the climate data from the perspective of accessibility for maintenance. When selecting sites for the deployment of WECs, a balance needs to be found between two opposing criteria: the existence of sufficiently long, continuous time intervals of calm sea states (weather windows) which are necessary for maintenance activities to take place, and a high, consistent level of wave energy density, essential for economically viable wave energy extraction.

Wave Energy Assessments in the Coastal Environment of Portugal Continental

2008 ◽  
Author(s):  
Eugen Rusu ◽  
C. Guedes Soares
Keyword(s):  
Wave Energy ◽  
Numerical Models ◽  
Specific Area ◽  
Wave Climate ◽  
Coastal Environment ◽  
Wave Power ◽  
Relevant Parameter ◽  
Density Spectrum ◽  
Energy Devices ◽  
Power Resources

The potential for wave energy extraction can be obtained from the analysis of the wave climate which can be determined with numerical models. The wave energy devices can be deployed in offshore, nearshore and shoreline. From this reason, it is important to be able to assess properly the spatial distribution of the wave energy in various locations from the offshore to the coastline in a specific area. The methodology proposed here considers a SWAN based wave model system focusing in the Portuguese continental coastal environment from deep water towards the nearshore. An analysis of the average and high energetic conditions was first performed for a ten-year period, between 1994 and 2003, considering the most relevant in situ measurements available in the Portuguese nearshore. In this way both the average and high energetic conditions corresponding to the Portuguese continental costal environment have been properly defined. For the most relevant average wave conditions, SWAN simulations were performed in some medium resolution areas covering the northern and central parts of Portugal continental, which are traditionally considered richer in wave power resources. The present work allows the identification of some locations in the continental coastal environment of Portugal with greater potential from the point of view of wave power resources. An important observation is related to the fact that the wave power depends on the product between the energy density spectrum and the group velocity of waves. This means that, although the significant wave height is a relevant parameter when assessing the wave power in a specific site, a location having in general higher wave heights is not necessarily also the richest in wave power.

scholarly journals Spatial and temporal variations of wave energy in the nearshore waters of the central west coast of India

2016 ◽  
Vol 34 (12) ◽  
pp. 1197-1208 ◽  
Author(s):  
M. M. Amrutha ◽  
V. Sanil Kumar
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Water Depth ◽  
Wave Energy ◽  
West Coast ◽  
Temporal Variations ◽  
Wave Power ◽  
Monsoon Period ◽  
West Coast Of India ◽  
Water Depths

Abstract. Assessment of wave power potential at different water depths and time is required for identifying a wave power plant location. This study examines the variation in wave power off the central west coast of India at water depths of 30, 9 and 5 m based on waverider buoy measured wave data. The study shows a significant reduction ( ∼  10 to 27 %) in wave power at 9 m water depth compared to 30 m and the wave power available at 5 m water depth is 20 to 23 % less than that at 9 m. At 9 m depth, the seasonal mean value of the wave power varied from 1.6 kW m−1 in the post-monsoon period (ONDJ) to 15.2 kW m−1 in the Indian summer monsoon (JJAS) period. During the Indian summer monsoon period, the variation of wave power in a day is up to 32 kW m−1. At 9 m water depth, the mean annual wave power is 6 kW m−1 and interannual variations up to 19.3 % are observed during 2009–2014. High wave energy ( >  20 kW m−1) at the study area is essentially from the directional sector 245–270° and also 75 % of the total annual wave energy is from this narrow directional sector, which is advantageous while aligning the wave energy converter.

scholarly journals Joint Modelling of Wave Energy Flux and Wave Direction

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 460
Author(s):  
Takvor H. Soukissian ◽  
Flora E. Karathanasi
Keyword(s):  
Energy Flux ◽  
Wave Energy ◽  
Goodness Of Fit ◽  
North Atlantic Ocean ◽  
Wave Climate ◽  
Western Mediterranean ◽  
Wave Direction ◽  
Bivariate Model ◽  
The North ◽  
Wave Energy Flux

In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained.

scholarly journals Hardware-in-the-Loop Validation of Model Predictive Control of a Discrete Fluid Power Power Take-Off System for Wave Energy Converters

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3668
Author(s):  
Anders H. Hansen ◽  
Magnus F. Asmussen ◽  
Michael M. Bech
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Fluid Power ◽  
Wave Power ◽  
Reactive Control ◽  
Power Extraction ◽  
Wave Energy Converters ◽  
Extraction Algorithm ◽  
Energy Converters

Model predictive control based wave power extraction algorithms have been developed and found promising for wave energy converters. Although mostly proven by simulation studies, model predictive control based algorithms have shown to outperform classical wave power extraction algorithms such as linear damping and reactive control. Prediction models and objective functions have, however, often been simplified a lot by for example, excluding power take-off system losses. Furthermore, discrete fluid power forces systems has never been validated experimentally in published research. In this paper a model predictive control based wave power extraction algorithm is designed for a discrete fluid power power take-off system. The loss models included in the objective function are based on physical models of the losses associated with discrete force shifts and throttling. The developed wave power extraction algorithm directly includes the quantized force output and the losses models of the discrete fluid power system. The experimental validation of the wave power extraction algorithm developed in the paper shown an increase of 14.6% in yearly harvested energy when compared to a reactive control algorithm.

scholarly journals Optimizing the Power Take Off of a Wave Energy Converter With Regard to the Wave Climate

2005 ◽  
Vol 128 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Gaelle Duclos ◽  
Aurelien Babarit ◽  
Alain H. Clément
Keyword(s):  
Wave Energy ◽  
Simple Wave ◽  
Wave Climate ◽  
Wave Energy Converter ◽  
Optimal Parameters ◽  
Energy Converter ◽  
Wave Energy Converters ◽  
Classical Wave ◽  
Project Site ◽  
Wave Conditions

Considered as a source of renewable energy, wave is a resource featuring high variability at all time scales. Furthermore wave climate also changes significantly from place to place. Wave energy converters are very often tuned to suit the more frequent significant wave period at the project site. In this paper we show that optimizing the device necessitates accounting for all possible wave conditions weighted by their annual occurrence frequency, as generally given by the classical wave climate scatter diagrams. A generic and very simple wave energy converter is considered here. It is shown how the optimal parameters can be different considering whether all wave conditions are accounted for or not, whether the device is controlled or not, whether the productive motion is limited or not. We also show how they depend on the area where the device is to be deployed, by applying the same method to three sites with very different wave climate.

Wave-Powered Desalination

2015 ◽  
Author(s):  
Brian Stiber ◽  
Asfaw Beyene
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Wave Energy ◽  
Specific Region ◽  
Wave Power ◽  
Wave Energy Conversion ◽  
Coastal Regions ◽  
Sustainable Resources ◽  
Modeling Software ◽  
The Cost

Climate change, drought, population growth and increased energy and water costs are all forces driving exploration into alternative, sustainable resources. The abundance of untapped wave energy often presents an opportunity for research into exploiting this resource to meet the energy and water needs of populated coastal regions. This paper investigates the potential and impact of harnessing wave energy for the purpose of seawater desalination. First the SWAN wave modeling software was used to evaluate the size and character of the wave resource. These data are used to estimate the cost of water for wave-powered desalination taking a specific region as a case example. The results indicate that, although the cost of water from this technology is not economically competitive at this time, the large available resource confirms the viability of significantly supplementing current freshwater supplies. The results also confirm that research into the feasibility of wave power as a source of energy and water in the area is warranted, particularly as water and energy become more scarce and expensive coinciding with the maturity of commercial wave energy conversion.

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