Page 12 - ENERGIA_MARE
P. 12
Author's personal copy
L. Liberti et al. / Renewable Energy 50 (2013) 938e949 949
4. Conclusions [5] Barstow S, Mørk G, Lønseth L, Mathisen JP. Worldwaves wave energy resource
assessments from the deep ocean to the coast. In: Proceedings of the 8th
In this paper an in-depth analysis of the wave energy potential European wave and tidal energy conference; 2009. Uppsala, Sweden.
along the Italian coast was performed using a third generation ocean
wave model. A wave climatology based on a ten years long simula- [6] Mørk G, Barstow S, Kabuth A, Pontes MT. Assessing the global wave energy
tion covering the period 2001e2010 was produced using the WAM potential. In: proceedings of the 29th international conference on ocean.
Cycle 4.5.3 with a uniform resolution of 1/16 over the entire Offshore Mechanics and Arctic Engineering; 2010.
Mediterranean. Model results were validated against buoys and
satellite altimeters data. We found that the spatial resolution of the [7] Arinaga RA, Cheung KF. Atlas of global wave energy from 10 years of rean-
wave model alone plays a major role in improving the overall quality alysis and hindcast data. Renewable Energy 2012;39(1):49e64. doi:\bibinfo
of our results. To verify this ï¬nding, we compared wave data directly {doi}{10.1016/j.renene.2011.06.039}.
provided by the ECMWF at a 1/8 spatial resolution with buoy data
for the years 2001e2010. The ECMWF wave data are produced by [8] Vicinanza D, Cappietti L, Contestabile P. Assessment of wave energy around
forcing the WAM model with ECMWF wind ï¬elds. Table 9 shows the italy. In: Proceedings of the 8th European wave and tidal energy conference;
values of the statistics obtained by comparing ECMWF Hs data with 2009. Uppsala, Sweden.
corresponding buoy measurements. By comparing the values of bias
and slope found in Tables 5 and 9 we observe that the amount of Hs [9] Vicinanza D, Cappietti L, Ferrante V, Contestabile P. Estimation of the wave
underestimation is considerably less in our simulations. Also the energy in the Italian offshore. Journal of Coastal Research 2011;64(12):613e7.
dispersion of model values is reduced as shown by the lower values URL: http://www.ics2011.pl/artic/SP64_613-617_D.Vicinanza.pdf.
of rmse and si. Starting from the model output a detailed analysis of
wave energy availability and of its distribution among different sea [10] Cavaleri L, Bertotti L. Accuracy of the modelled wind and wave ï¬elds in
states was carried out. As already stated by [9], among others, the enclosed seas. Tellus Series A-Dynamic Meteorology and Oceanography 2004;
most promising locations for wave energy production along the 56(2):167e75. doi:\bibinfo1{doi}{10.1111/j.1600-0870.2004.00042.x}.URL:
Italian coastline are found on the western coast of Sardinia and along http://dx.doi.org/10.1111/j.1600-0870.2004.00042.x.
the north-western and southern coast of Sicily. However, at the
resolution of our model, we were able to observe that average power [11] Athanassoulis G, Stefanakos C, Cavaleri L, Ramieri E, Noel C, Lefevre JM, et al.
flux generally exhibits a considerable variability at relatively small Rtp 10.10 ww_medatlas scientiï¬c report. Tech. Rep. MEDATLAS Project; 2004.
spatial scales of the order of the tens of kilometers. For instance,
along the western coast of Sardinia two areas located in the northern [12] Cavaleri L. The wind and wave atlas of the mediterranean sea e the calibration
and southern sections of the coastline appear to be the most phase. Advances in Geosciences 2005;2:255e7. doi:\bibinfo{doi}{10.5194/
productive. Similarly, along the Sicily coastline the western section adgeo-2-255-2005}.URL: http://www.adv-geosci.net/2/255/2005/.
and the most southern tip are the most promising while the rest of
the southern coast is far less energetic. This fact suggests that high [13] Ponce de Leon S, Guedes Soares C. Sensitivity of wave model predictions to
resolution atlases of wave energy, like the one presented in this wind ï¬elds in the western Mediterranean sea. Coastal Engineering 2008;
paper, are required for an accurate evaluation of most suitable 55(11):920e9.
locations for wave energy extraction. Moreover, by analyzing the
wave energy distribution among sea states, we found that additional [14] Music S, Nickovic S. 44-year wave hindcast for the eastern mediterranean.
elements of variability emerge even between locations apparently Coastal Engineering 2008;55(11):872e80.
homogeneous in terms of the overall energy potential. Since the
actual amount of energy that can be extracted with a speciï¬c WEC [15] Contento G, Lupieri G, Venturi M, Ciuffardi T. A medium-resolution wave
depends on the distribution of available energy among sea states, it hindcast study over the central and western Mediterranean sea. Journal of
appears that a detailed knowledge of this information is extremely Marine Science and Technology 2011;16(2):181e201.
important to obtain reliable economical and technical assessments
of wave energy parks. [16] Mackay EB, Bahaj AS, Challenor PG. Uncertainty in wave energy resource
assessment. Part 2: variability and predictability. Renewable Energy 2010;35(8):
Acknowledgments 1809e19. doi:\bibinfo{doi}{10.1016/j.renene.2009.10.027}.URL: http://www.
sciencedirect.com/science/article/pii/S0960148109004534.
The altimeter products were produced by CLS Space Oceanog-
raphy Division and distributed by AVISO, with support from CNES. [17] Günther H, Behrens A. The wam model validation document version 4.5.3.
We are grateful to the CRESCO supercomputing facilities located at Tech. Rep. Institute of Coastal Research Helmholtz-Zentrum Geesthacht
ENEA (http://www.cresco.enea.it). (HZG); 2011.
References [18] GEBCO. http://www.gebco.net/data_and_products/gridded_bathymetry_data/,
2010.
[1] Association, EOE. Oceans of energy European ocean energy roadmap 2010-
2050. Tech. Rep. European Ocean Energy Association; 2010. [19] ECMWF Products. Medium range forecast, http://www.ecmwf.int/products/
forecasts/d/charts.
[2] Falcão AFDO. Wave energy utilization: a review of the technologies. Renew-
able and Sustainable Energy Reviews 2010;14(3):899e918. [20] Chelton DB, Freilich MH. Scatterometer-based assessment of 10-m wind
analyses from the operational ECMWF and NCEP numerical weather predic-
[3] IEA. Implementing agreement on ocean energy systems. Tech. Rep. IEA; 2010. tion models. Monthly Weather Review 2005;133(2):409e29. doi:\bibinfo
[4] Cornett AM. A global wave energy resource assessment. In: proceedings of the {doi}{10.1175/MWR-2861.1}.URL: http://dx.doi.org/10.1175/MWR-2861.1.
Eighteenth international offshore and polar engineering conference, Van- [21] Department ER. Ifs documentation part I: observation processing (CY25R1).
couver, BC, Canada, 2008. Tech. Rep. European Center for Medium-Range Weather Forecast; 2003.
[22] Aviso, ftp://ftp.aviso.oceanobs.com/pub/oceano/AVISO/; 2011.
[23] Queffeulou P, Bentamy A. Analysis of wave height variability using altimeter
measurements: application to the Mediterranean sea. Journal of Atmospheric
and Oceanic Technology 2007;24(12):2078e92. doi:\bibinfo{doi}{10.1029/
2006JC003924}.
[24] Willmott CJ. Some comments on the evaluation of model performance.
Bulletin of the American Meteorological Society 1982;63(11):1309e13. doi:
\bibinfo{doi}{10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2}.URL:
http://dx.doi.org/10.1175/1520-0477(1982)063<1309:SCOTEO>2.0.CO;2.
[25] Ardhuin F, Bertotti L, Bidlot JR, Cavaleri L, Filipetto V, Lefevre JM, et al.
Comparison of wind and wave measurements and models in the western
Mediterranean sea. Ocean Engineering 2007;34:526e41.
[26] Corsini S, Franco L, Piscopia R, Inghilesi R. L’atlante delle onde nei mari italiani e
Italian wave atlas. Tech. Rep. APAT(ISPRA); 2004.
[27] Signell RP, Carniel S, Cavaleri L, Chiggiato J, Doyle JD, Pullen J, et al. Assess-
ment of wind quality for oceanographic modelling in semi-enclosed basins.
Journal of Marine Systems 2005;53:217e33.
[28] Hanson LJ, Tracy AB, Tolman LH, Scott RD. Paciï¬c hindcast performance
evaluation of three numerical wave models. In: Proceedings 9th international
workshop on wave hindcasting and forecasting; 2006. Victoria, Canada.
[29] Mardia KV, Jupp PE. Directional statistics. Wiley Series in probability and
statistics. John Wiley & Sons, Ltd; 2000.
[30] Waters R, Engström J, Isberg J, Leijon M. Wave climate off the swedish west
coast. Renewable Energy 2009;34(6):1600e6. doi:\bibinfo{doi}{10.1016/j.
renene.2008.11.016}. URL: http://www.sciencedirect.com/science/article/pii/
S0960148108004242.
[31] Iglesias G, Carballo R. Wave energy resource in the Estaca de Bares area
(Spain). Renewable Energy 2010;35(7):1574e84. doi:\bibinfo{doi}{10.1016/
j.renene.2009.10.019}. Special Section: IST National Conference 2009,
http://www.sciencedirect.com/science/article/pii/S0960148109004455.
View publication stats

