Wave energy in the Balearic Sea. Evolution from a 29 year spectral wave hindcast

doi:10.1016/j.renene.2015.07.076

Renewable Energy

Volume 85, January 2016, Pages 1192-1200

https://doi.org/10.1016/j.renene.2015.07.076 Get rights and content

Highlights

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Wave climate for the Balearic Island Archipelago has been analyzed by performing a 29 year hindcast.
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Energy flux presents large variability with mean values of 9.1 ± 2.5 kW/m at the North of Menorca Island.
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Energy flux presents large seasonal variation, 6 times larger in the winter than in the summer.

Abstract

This work studies the wave energy availability in the Western Mediterranean Sea using wave simulation from January 1983 to December 2011. The model implemented is the WAM, forced by the ECMWF ERA-Interim wind fields. The Advanced Scatterometer (ASCAT) data from MetOp satellite and the TOPEX-Poseidon altimetry data are used to assess the quality of the wind fields and WAM results respectively. Results from the hindcast are the starting point to analyse the potentiality of obtaining wave energy around the Balearic Islands Archipelago. The comparison of the 29 year hindcast against wave buoys located in Western, Central and Eastern basins shows a high correlation between the hindcasted and the measured significant wave height (H_s), indicating a proper representation of spatial and temporal variability of H_s. It is found that the energy flux at the Balearic coasts range from 9.1 kW/m, in the north of Menorca Island, to 2.5 kW/m in the vicinity of the Bay of Palma. The energy flux is around 5 and 6 times lower in summer as compared to winter.

Introduction

Energy obtained from marine devices is one of the most promising renewable energy resources in coastal areas as the technology in wave energy converters (WEC hereinafter) is becoming more efficient [27], [14], [15]. To properly characterize the potential of the wave energy in a specific area, it is crucial to have an accurate analysis of the wave climate so as to dimension the WECs maximizing the energy obtained from the waves.

In the Balearic Sea, the most western basin of the Mediterranean Sea, the wave climate has already been identified to have, in general, a complex pattern as the result of the variability in the storm tracks, the complex orography and the relatively short fetch [5], [20]. Due to the complexity in the wave pattern, the search for appropriate locations for WECs has to account both for those locations where maximum energy is found but also maintained during large periods [22].

In the last decade the wave forecast has improved significantly, thanks to 1) the advance in the numerical models used for wave forecasting (in terms of physical processes resolved as well as in the numerical algorithms implemented), 2) the increase in the number of wave measurements (moorings, radar from satellite or coastal stations) and 3) the advances in data assimilation techniques. Today it is possible to compile large databases of wave parameters that are routinely used for prognostic or diagnostic purposes [1], [23].

Numerical studies for wave power considerations are mostly performed in areas with a high potential in wave energy generation. Since wave power is directly related with the significant wave height, H_s, and the energy period, T_e, coastal seas with moderate wave climate, such as the Mediterranean Sea, have not been fully studied. The above in spite that, under a technical and economical perspective, areas with moderate but sustained wave climate are very appropriate for the installation of power farms where the WECs will be able to operate during larger periods [17].

Wave conditions are certainly the major factor affecting wave energy production and a significant part of the energy will be obtained from exceptional wave conditions during extreme events. However, such conditions pose serious engineering challenges and increase the costs in the development of the WECs and therefore intricate the energy production, device installation and maintenance as well as the transport of energy. On the other hand, in calmer and semi-enclosed seas with relative moderate wave conditions such as the Mediterranean Sea, many technical issues related to extreme sea climate could be more easily solved, possibly making wave energy production economically viable.

The Balearic Archipelago (Northwestern Mediterranean Sea) is formed by four major islands (Mallorca, Menorca, Ibiza and Formentera). It is one of the largest touristic spots around the globe, hosting in 2014 more than 14 millions tourists and having a permanent population of 1.2 millions (80% of the population in Mallorca). The floating population oscillates seasonally from 2.6 millions during August to 140.000 in December, demanding goods and services that have to be imported from mainland (including energy).

Following these antecedents, this work studies the wave energy assessment in the Balearic Islands using a new wind-wave data base covering from 1983 to 2011. The paper first presents the new wave database generated by the WAM 4.5.2 model [11], while wind is given by the ECMWF ERA-Interim reanalysis [8] retrieved at a horizontal resolution of 0.125° (14 km). Next, wave climate is characterized by means of an EOF analysis of the significant wave height. Finally, a wave power analysis is presented for coastal stations around the Balearic Islands located at intermediate depths.

Section snippets

Wave model set-up

The wave model implemented is the third generation spectral wave model WAM [16]. A high resolution grid was implemented covering the whole Mediterranean Sea, extending from 30° N to 46° N and 06° W to 37° E. All the spectral components are calculated prognostically from the energy-balance equation up to a variable cut-off frequency [26].

A 29 years hindcast, from January 1983 to December 2011, was performed for the entire Mediterranean Sea using ECMWF ERA-Interim wind fields (http://www.ecmwf.int

ECMWF ERA-Interim against ASCAT

The 6 h ECMWF ERA-Interim data-set was compiled for the period between 1983 and 2011. ASCAT wind data were not used by ERA-Interim and here we have not performed any correction for ERA-Interim. In the Mediterranean, the accuracy of the winds is crucial for wave modeling. Cavaleri and Sclavo [6] treated this issue pointing out that in coastal areas, the model winds are unreliable because of the dominant influence of the orography that is not properly represented in the meteorological model

Wave height variability in the Mediterranean basin

Time average of H_s shows that the larger values are located in the northwestern basin and at the eastern part of the Island of Crete, two areas with strong local winds. The Gulf of Lions is greatly influenced by the Pyrenees to the west and by the Alps to the east, being two decisive boundaries that drive locally intense wind over the Ligurian Sea [19]. The combination of wind intensity and wind direction acting over a large area (fetch) generates strong sea states as depicted in Fig. 5 (top

Wave energy assessment in the Balearic Islands

A set of 9 virtual buoys surrounding the coasts of the three major Balearic Islands (Mallorca, Menorca and Ibiza) are selected in order to assess the potential for wave energy. These buoys are the hindcast presented in the previous section and are selected to be in deep waters in order to have an accurate representation of the wave field given by the numerical model (Fig. 1, lower panel). Location and depth of the buoys is indicated in Table 3.

The variation of wave energy is computed following

Conclusions

Wave climate for the Balearic Island Archipelago has been analyzed by performing a 29 year hindcast of the wave field. The numerical simulation has been performed for the entire Mediterranean Sea, and validated using buoys data. The 6 h wave climate has been used to infer the energy flux in shallow areas of the Archipelago. The energy flux has been found to present a large spatial and temporal variability with mean values ranging from 9.1 ± 2.5 kW/m at the north of the Island of Menorca to

Acknowledgments

AO thanks financial support from the ENAP-Colombian Army. GS is supported from the Spanish Government through the Ramon y Cajal program.

References (25)

C.M. Appendini et al.
Wave energy potential assessment in the caribbean low level jet using wave hindcast information
Appl. Energy
(2015)
L. Cavaleri et al.
The calibration of wind and wave model data in the Mediterranean Sea
Coast. Eng.
(2006)
D. Gomis et al.
Low frequency Mediterranean Sea level variability: the contribution of atmospheric pressure and wind
Glob. Planet. Change
(2008)
G. Iglesias et al.
Offshore and inshore wave energy assessment: Asturias (n spain)
Energy
(2010)
G. Iglesias et al.
Wave energy resource in the estaca de bares area (spain)
Renew. Energy
(2010)
L. Liberti et al.
Wave energy resource assessment in the mediterranean, the italian perspective
Renew. Energy
(2013)
S.C. Parkinson et al.
Integrating ocean wave energy at large-scales: a study of the US Pacific Northwest
Renew. Energy
(2015)
A.W. Ratsimandresy et al.
A 44-year high-resolution ocean and atmospheric hindcast for the Mediterranean Basin developed within the HIPOCAS Project
Coast. Eng.
(2008)
G. Reikard
Integrating wave energy into the power grid: simulation and forecasting
Ocean Eng.
(2013)
R. Waters et al.
Wave climate off the Swedish west coast
Renew. Energy
(2009)

E. Ash et al.

DUE GlobWave Wave Data Handbook

(2012)

J. Bidlot

Intercomparison of operational wave forecasting systems against buoys: data from ecmwf, metoffice, fnmoc, msc, ncep, meteofrance, dwd, bom, shom, jma, kma, puerto del estado, dmi, cnr-am, metno, shn-sm

(November 2012)

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View full text

Wave energy in the Balearic Sea. Evolution from a 29 year spectral wave hindcast

Highlights

Abstract

Introduction

Section snippets

Wave model set-up

ECMWF ERA-Interim against ASCAT

Wave height variability in the Mediterranean basin

Wave energy assessment in the Balearic Islands

Conclusions

Acknowledgments

Appl. Energy

Coast. Eng.

Glob. Planet. Change

Energy

Renew. Energy

Renew. Energy

Renew. Energy

Coast. Eng.

Ocean Eng.

Renew. Energy

DUE GlobWave Wave Data Handbook

Intercomparison of operational wave forecasting systems against buoys: data from ecmwf, metoffice, fnmoc, msc, ncep, meteofrance, dwd, bom, shom, jma, kma, puerto del estado, dmi, cnr-am, metno, shn-sm