scholarly journals Wave Energy Resource Harnessing Assessment in a Subtropical Coastal Region of the Pacific

2021 ◽  
Vol 9 (11) ◽  
pp. 1264
Author(s):  
Emiliano Gorr-Pozzi ◽  
Héctor García-Nava ◽  
Marco Larrañaga ◽  
Melissa G. Jaramillo-Torres ◽  
Manuel G. Verduzco-Zapata

Most wave energy converters (WECs) are designed to operate in high-latitude energetic seas, limiting their performance in regions usually dominated by milder conditions. The present study assesses the performance of complete test-stage WECs in farms that satisfy a decentralized energy scheme (DES) on the coast of Baja California, which is considered one of the most energetic regions along the Mexican Pacific. A high-resolution 11-year nearshore wave hindcast was performed and validated with Acoustic Doppler Current Profilers (ADCPs) data to characterize the wave energy resource in the study area. Two hotspots were identified from the wave power climatology. In these sites, the extractive capacities of seven well-known WEC technologies were determined based on their power matrices. Finally, the power extracted by small WEC farms, with the minimum number of devices required to satisfy a DES, was estimated. The studied region has moderate wave power availability with marked seasonality and low inter-annual variability. Out of all the evaluated devices, WaveDragon extracts the highest wave power; however, Pelamis has the best performance, with maximum monthly mean capacity factors up to 40%. Coupling WEC farms with storage modules or hybrid renewable systems are recommended to satisfy a continuous DES during the less energetic summer months.

Author(s):  
Garlapati Nagababu ◽  
Ravi Patel ◽  
Seemanth Moideenkunju ◽  
Abhinaya Srinivas Bhasuru ◽  
Surendra Singh Kachhwaha ◽  
...  

Identification of the best location for wave farm installation, wave resource assessment needs to be carried out. In the present work, wave resource assessment along the Indian EEZ was carried out using the 17-year (2000 to 2016) output simulation of the third generation wave model WAVEWATCH-III (WWIII). Spatial distribution of significant wave height, mean wave energy period and annual mean of wave power is plotted. Further, the monthly and seasonal variation has been carried out to assess the effect on temporal variability at a specific location. The results show the annual mean wave power is in the range of 1–12 kW/m across the Indian EEZ. Further, it was observed that wave power along the western coast of India is more energetic than the eastern coast of India, with annual average wave power of 8–12 kW/m and 2–6 kW/m respectively. However, coastlines of Gujarat and Maharashtra experience the maximum seasonal and monthly variability across Indian EEZ, which is 2 and 3.5 respectively. By using different wave energy converters (WEC), the capacity factor and technical wave energy potential over the study area are estimated. Oceantec WEC shows maximum capacity factor (0.35) among the all selected wave energy converters. The results reveal that the electric wave power generation is 3 times more in the western coastal region as compared to the eastern coast of India.


Author(s):  
Arne Vögler ◽  
Vengatesan Venugopal

The Outer Hebrides of Scotland were identified as an area with a high wave power resource of 42.4kW/m. The Outer Hebrides of Scotland are currently targeted by a range of developers for demonstration and commercial developments of wave energy converters and current planning efforts are based on initial deployments by 2014. Technology providers with well advanced plans to develop the Hebridean wave resource include Aquamarine Power (Oyster) [1], Pelamis (P2) [2] and Voith Wavegen (OWC) [3]; all of these companies are partners in the Hebridean Marine Energy Futures project [4] to help move the industry into the commercialisation stage. As part of the Hebridean Marine Energy Futures project, a three year programme aimed at developing a high resolution wave energy resource map to support the site selection process of marine energy developers, a network of three wave measuring buoys was deployed 15km offshore in a depth of 60m and at distances of 11km between buoys. Measured wind and wave data from this buoy network for autumn 2011 are analysed and presented in this paper along with estimated wave power for the same duration.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3482
Author(s):  
Ruth Branch ◽  
Gabriel García-Medina ◽  
Zhaoqing Yang ◽  
Taiping Wang ◽  
Fadia Ticona Rollano ◽  
...  

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.


Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2993
Author(s):  
Joan Pau Sierra ◽  
Ricard Castrillo ◽  
Marc Mestres ◽  
César Mösso ◽  
Piero Lionello ◽  
...  

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.


Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 333 ◽  
Author(s):  
Carlo Re ◽  
Giorgio Manno ◽  
Giuseppe Ciraolo ◽  
Giovanni Besio

This paper presents the estimation of the wave energy potential around the Aegadian islands (Italy), carried out on the basis of high resolution wave hindcast. This reanalysis was developed employing Weather Research and Forecast (WRF) and WAVEWATCH III ® models for the modelling of the atmosphere and the waves, respectively. Wave climate has been determined using the above-mentioned 32-year dataset covering the years from 1979 to 2010. To improve the information about wave characteristics regarding spatial details, i.e., increasing wave model resolution, especially in the nearshore region around the islands, a SWAN (Simulating WAves Nearshore) wave propagation model was used. Results obtained through the development of the nearshore analysis detected four energetic hotspots close to the coast of the islands. Near Marettimo island, only one hotspot was detected with a maximum wave energy flux of 9 kW/m, whereas, around Favignana, three hotspots were identified with a maximum wave energy flux of 6.5 kW/m. Such values of available wave energy resource are promising to develop different projects for wave energy converters in specific areas along the coast, in order to improve the energetic independence of Aegadian islands.


2021 ◽  
Vol 13 (11) ◽  
pp. 2070
Author(s):  
Ana Basañez ◽  
Vicente Pérez-Muñuzuri

Wave energy resource assessment is crucial for the development of the marine renewable industry. High-frequency radars (HF radars) have been demonstrated to be a useful wave measuring tool. Therefore, in this work, we evaluated the accuracy of two CODAR Seasonde HF radars for describing the wave energy resource of two offshore areas in the west Galician coast, Spain (Vilán and Silleiro capes). The resulting wave characterization was used to estimate the electricity production of two wave energy converters. Results were validated against wave data from two buoys and two numerical models (SIMAR, (Marine Simulation) and WaveWatch III). The statistical validation revealed that the radar of Silleiro cape significantly overestimates the wave power, mainly due to a large overestimation of the wave energy period. The effect of the radars’ data loss during low wave energy periods on the mean wave energy is partially compensated with the overestimation of wave height and energy period. The theoretical electrical energy production of the wave energy converters was also affected by these differences. Energy period estimation was found to be highly conditioned to the unimodal interpretation of the wave spectrum, and it is expected that new releases of the radar software will be able to characterize different sea states independently.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3668
Author(s):  
Anders H. Hansen ◽  
Magnus F. Asmussen ◽  
Michael M. Bech

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.


Author(s):  
Dean L. Millar

This chapter reviews how electricity can be generated from waves and tides. The UK is an excellent example, as the British Isles have rich wave and tidal resources. The technologies for converting wave power into electricity are easily categorized by location type. 1. Shoreline schemes. Shoreline Wave Energy Converters (WECs) are installed permanently on shorelines, from where the electricity is easily transmitted and may even meet local demands. They operate most continuously in locations with a low tidal range. A disadvantage is that less power is available compared to nearshore resources because energy is lost as waves reach the shore. 2. Nearshore schemes. Nearshore WECs are normally floating structures needing seafloor anchoring or inertial reaction points. The advantages over shoreline WECs are that the energy resource is much larger because nearshore WECs can access long-wavelength waves with greater swell, and the tidal range can be much larger. However, the electricity must be transmitted to the shore, thus raising costs. 3. Offshore schemes. Offshore WECs are typically floating structures that usually rely on inertial reaction points. Tidal range effects are insignificant and there is full access to the incident wave energy resource. However, electricity transmission is even more costly. Tidal power technologies fall into two fundamental categories:1. Barrage schemes. In locations with high tidal range a dam is constructed that creates a basin to impound large volumes of water. Water flows in and out of the basin on flood and ebb tides respectively, passing though high efficiency turbines or sluices or both. The power derives from the potential energy difference in water levels either side of the dam. 2. Tidal current turbines. Tidal current turbines (also known as free flow turbines) harness the kinetic energy of water flowing in rivers, estuaries, and oceans. The physical principles are analogous to wind turbines, allowing for the very different density, viscosity, compressibility, and chemistry of water compared to air. Waves are caused by winds, which in the open ocean are often of gale force (speed >14 m/s).


Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2633
Author(s):  
Addy Wahyudie ◽  
Tri Bagus Susilo ◽  
Fatima Alaryani ◽  
Cuk Supriyadi Ali Nandar ◽  
Mohammed Abdi Jama ◽  
...  

An assessment of the wave power at the southern coast of the middle part of Java Island (Indonesia) was conducted based on a 15-year hindcast spectral wave model using the MIKE 21 Spectral Wave software. The model was forced with wind data with a 0.125° spatial interval and hourly time resolution. The obtained model was validated with field data collected from a buoy station that provided a set of significant wave height data with an hourly data interval for the whole month of June 2014. The validation showed that the obtained model matched the observed data with a minor average error. A spatial analysis was conducted in order to find the most suitable location for installing wave energy converters while taking into consideration the potential area demand, the wave power intensity, and the distance from the shore. Moreover, spatial analysis is conducted in order to find a suitable location to install wave energy converters, with consideration to potential area demand, wave power intensity, and distance from the shore. The best prospective location reached 30 kW/m of mean wave power intensity, 2.04 m of mean significant wave height, 8.9 s of mean wave period, 150 m of distance from the shoreline.


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