Numerical evaluation of the wave energy resource along the Atlantic European coast

Soares, C. Guedes; Bento, A. Rute; Gonçalves, Marta; Silva, Dina; Martinho, Paulo N.

doi:10.1016/j.cageo.2014.03.008

Cited by 79 publications

(12 citation statements)

References 40 publications

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“…A comparison with the results from similar studies that used the same modeling system to estimate the spatial distribution of wave energy in the west Iberian nearshore [43][44][45][46], and which were undertaken in the last 25 years, show many similar features, but also some differences. Thus, an important observation coming from the analysis of the case studies presented in this work, is that most of the wave energy hot spots already identified in the western Iberian nearshore appear to be persistent, since they were identified again in various computational domains and for various time frames.…”

Section: Discussionmentioning

confidence: 85%

Numerical Modeling of the Wave Energy Propagation in the Iberian Nearshore

Rusu¹

2018

Energies

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In the present work the wave energy propagation patterns in the western side of the Iberian nearshore were evaluated. This assessment takes into account the results provided by a wave modelling system based on spectral phase averaged wave models, which considers subsequent computational domains with increasing resolution towards the coast. The system was previously validated against both in situ measurements and remotely sensed data. Moreover, several data assimilation techniques were implemented as well. In this way, the reliability of the wave predictions was significantly increased. Although extended wave hindcasts have already been carried out close to the Iberian coast of the Atlantic Ocean, including wave energy assessments, they might not be completely accurate because of recent changes in the dynamics of the ocean and coastal wave climate. Thus, the present work considers wave nowcasts that correspond to the most recent and relevant wave energy propagation patterns in the targeted coastal environment. In order to perform this analysis, four different computational levels were considered. The first level corresponds to the sub oceanic domain and it is linked directly to the oceanic wave model, which is implemented over the entire North Atlantic Ocean. The second is related to the coarser computational domains of the coastal areas, while the third relates to the high-resolution domains. These three levels are defined as spherical coordinates (longitude, latitude). Finally, the last computational level includes some coastal areas which have the highest spatial resolution, defined considering the Cartesian coordinates. Moreover, for each level several computational domains have been considered. This work illustrates the most recent and significant wave transformation and energy propagation patterns corresponding to 18 computational domains with various resolutions in the western Iberian coastal environment.

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Section: Discussionmentioning

confidence: 85%

Numerical Modeling of the Wave Energy Propagation in the Iberian Nearshore

Rusu¹

2018

Energies

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“…Regarding the assessment, performance, and feasibility analysis: Rusu et al [37] developed the wave energy resource for Portugal; Bozzi et al [38] analyzed the wave energy feasibility in Italy considering three WECs: AquaBuOY, Pelamis, and Wave Dragon; Iuppa et al [39] analyzed the case of Sicily; Guedes Soares et al [40] considered several coastal locations to determine their efficiency; Vannucchi et al [41] considered several Italian coasts: "Tuscany, Sardinia, Liguria et Sicily"; Dalton [42] analyzed the "non-technical barriers of wave energy in Europe"; Dalton et al [43] considered the Pelamis in three different scenarios in Europe and the USA; and O'Connor et al [44] analyzed the analysis of Pelamis and Wavestar in Europe.…”

Section: Introductionmentioning

confidence: 99%

Economic Feasibility of Wave Energy Farms in Portugal

et al. 2018

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This paper develops a methodology to determine the economic feasibility of implementing offshore wave energy farms on the Portuguese continental coast. This methodology follows several phases: the geographic phase, the energy phase, the economic phase, and the restrictions phase. First, in the geographic phase, the height and the period of the waves, the bathymetry, the distance from the farm to the shore, from farm to shipyard, and from farm to port, are calculated. In the energy phase the energy produced by each wave energy converter is determined, and in the economic phase, the parameters calculated in the previous phases are used as input to find the economic parameters. Finally, in the restrictions phase, a limitation by the bathymetry will be added to the economic maps, whose value will be different depending on the floating offshore wave energy converter (WEC). In this study, three wave energy converters have been considered, Pelamis, AquaBuOY, and Wave Dragon, and several scenarios for electric tariffs have been taken into account. The results obtained indicate what the best WEC is for this study in terms of its levelized cost of energy (LCOE), internal rate of return (IRR), and net present value (NPV), and where the best area is to install wave energy farms.

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“…Therefore, for the implementation of projects on wave energy use, an analysis of the available local wave energy potential is required. Traditionally, the energy potential estimations of different parts of the World Ocean are performed by modeling waves based on wind reanalysis; for example, studies by Atan and Goggins [3] and Soares et al [4] discuss the Atlantic.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Variability of Wave Energy Due to Climate Changes on the Example of the Black Sea

Saprykina

Kuznetsov

2018

Energies

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An analysis of the variability of wave climate and energy within the Black Sea for the period 1960–2011 was made using field data from the Voluntary Observing Ship Program. Methods using wavelet analysis were applied. It was determined that the power flux of wave energy in the Black Sea fluctuates: the highest value is 4.2 kW/m, the lowest is 1.4 kW/m. Results indicate significant correlations among the fluctuations of the average annual wave heights, periods, the power flux of wave energy, and teleconnection patterns of the North Atlantic Oscillation (NAO), the Atlantic Multi-decadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO) and the East Atlantic/West Russia (EA/WR). It was revealed that, in positive phases of long-term periods of AMO (50–60 years) as well as PDO, NAO, and AO (40 years), a decrease of wave energy was observed; however, an increase in wave energy was observed in the positive phase of a 15-year period of NAO and AO. The positive phase of changes of EA/WR for periods 50–60, 20–25, and 13 years led to an increase of wave energy. The approximation functions of the oscillations of the average annual wave heights, periods, and the power flux of wave energy for the Black Sea are proposed.

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Numerical evaluation of the wave energy resource along the Atlantic European coast

Cited by 79 publications

References 40 publications

Numerical Modeling of the Wave Energy Propagation in the Iberian Nearshore

Numerical Modeling of the Wave Energy Propagation in the Iberian Nearshore

Economic Feasibility of Wave Energy Farms in Portugal

Analysis of the Variability of Wave Energy Due to Climate Changes on the Example of the Black Sea

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