Wave power potential assessment of Aegean Sea with an integrated 15-year data

Jadidoleslam, Navid; Özger, Mehmet; Ağıralioğlu, Necati

doi:10.1016/j.renene.2015.09.022

Cited by 47 publications

(21 citation statements)

References 41 publications

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“…Similarly, in S�anas and Kumar (2015), data from nearshore waters around India are compared with ERA-Interim and their results are closer to those represented in this study wi�� c�rrela�i�n c�efficien�s ranging in 0�71�0�98, RMSE ranging in 0�18�0�4 m and abs�lu�e bias in 0�09�0�31 m� Furthermore, in the North and South Aegean, where the larger fetch distances are present, the larger the sample size ��e smaller ��e c�rrela�i�n c�efficien� (als� in ��e case of Stopa and Cheung (2014)) in contradiction to the Previous studies that have used wind reanalysis datasets as inputs for hydrodynamic modelling have c�mpared ��eir resul�s f�r several l�ca�i�ns a� ��e Greek Seas (Table 7). The results of Jadid�leslam et al(2016) give the best error statistics for Athos, Lesvos, E1M3A, Mykonos, Santorini and Skyros when compared to the other studies. For Avgo, the results of this analysis are similar to the results of Zacharioudaki et al(2015), while the results of Lavidas and Venug�pal (2017) are better for Pylos.…”

Section: Sub-daily Analysismentioning

confidence: 68%

“…In addition, Poupkou et al(2011) and identify negative trends regarding the frequency of appearance and the wind speed of the Etesians, from the analysis of ERA-40. ARPERA wind dataset has been used as input for wave hindcasting in ��e Greek Seas (Zac�ari�udaki & Reeve, 2011) while NOAA's CFRS wind data for wave energy estimates (Lavidas & Venug�pal, 2017 & S�ukissian, 2004;S�ukissian, 2008;Soukissian et al, 2009;K�rres et al, 2011;Mazarakis et al, 2012;Zac�ari�udaki et al, 2015;Emman�uil et al, 2016;Jadid�leslam et al, 2016;Lavidas & Venug�pal, 2017; )� T� discuss ��e perf�rmance �f reanaly� . To discuss the performance of reanalysis gridded dataset, the closest grid intersect to the insitu data is considered as representative of the under examination area (Ruti et al, 2008;Mazarakis et al, 2012;S��pa et al, 2013;Sanil Kumar & Mu�ammed Naseef, 2015;Zac�ari�udaki et al, 2015;Lavidas & Venug�pal, 2017).…”

Section: Study Areamentioning

confidence: 99%

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Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

et al. 2017

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ERA-Interim, ECMWF’s reanalysis product, includes wave and atmospheric characteristics, with high temporal and spatial scale, providing more information on the marine state. Even though their assimilation process has been validated and verified in numerous studies, their performance in more local scales is still under examination. This research focuses on the evaluation of performance of ERA-Interim reanalysis datasets in the Greek Seas for wind and wave characteristics in comparison to POSEIDON buoy data. The results prove fair to good correlation for wave height (r = 0.67-0.94) and wind speed (r= 0.71-0.83) and different error statistics per sub-region. The upper 10% analysis shows an underestimate of 10-15% for wind speed and wave height from ERA-Interim in relation to the buoy measurements. The ERA-Interim and the buoy monthly means and standard deviations are also presented and discussed according to seasonal patterns. The results of the study are compared to other researches of wave hindcasting and wind reanalysis data for the Greek Seas and globally. It is shown that ERA-Interim products could be regarded as representative for the Greek Seas, although their application should be made with caution regarding the assessment of extreme conditions (i.e. given in analyses of upper percentiles) and especially at nearshore locations due to complex coastline configuration enhanced by the great number of islands.

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Section: Sub-daily Analysismentioning

confidence: 68%

Section: Study Areamentioning

confidence: 99%

Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

et al. 2017

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“…Because the seasonal variation of wave energy is very high here-in winter, the wave power flux can be up to 5-6 times that of the summer [47]-the actual "hot spot" for WEC in the Mediterranean Sea can be an area with the lowest coefficient of variation, which means a more consistent value of wave energy throughout the year [45]. For this reason the studies of the lower wave energy potential regions-areas such as the Aegean Sea, where the average wave power flux is 2-2.5 kW/m [48]-can become more and more important in the future.…”

Section: Europementioning

confidence: 99%

Spatial Distribution of the Baltic Sea Near-Shore Wave Power Potential along the Coast of Klaipėda, Lithuania

et al. 2017

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Abstract:Wave power is an abundant source of energy that can be utilized to produce electricity. Therefore, assessments of wave power resources are being carried out worldwide. An overview of the recent assessments is presented in this paper, revealing the global distribution of these resources. Additionally, a study, which aims to assess the spatial distribution of the Baltic Sea near-shore wave power potential along the coast of Klaipėda (Lithuania), is introduced in this paper. The impacts of the wave propagation direction and decreasing depth on wave power resources were examined using the numerical wind-wave model MIKE 21 NSW. The wave height loss of the design waves propagating to shore was modelled, and the wave power fluxes in the studied depths were calculated using the JONSWAP wave spectrum modified for the Baltic Sea. The results revealed that all waves that propagate to the shore in the Baltic Sea near-shore area along the coast of Klaipėda from 30 m depth to 5 m depth lose at least 30% of their power. Still, most common waves in this area are low, and therefore, they start to lose their power while propagating to the shore at relatively low (10-14 m) depths. To turn this into an advantage the wave power converter would have to work efficiently under low power conditions.

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“…Traditionally, the assessment of the wave energy has been carried out for offshore deep water wave data [1,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], while, more recently, coastal areas have been investigated in order to locate hotspots [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. At the oceanic global scale, the richest wave power areas are between 40 • and 60 • latitude of both hemispheres [10].…”

Section: Assessment Of the Offshore Potentialmentioning

confidence: 99%

“…Some authors [25][26][27][28][29][30][31] propagated the most significant three or five wave cases representing winter/autumn average condition, a summer/spring average condition and a particularly energetic situation. Other authors [20,22,23,[32][33][34][35][36][37] propagated the whole events in the time series of the offshore numerical model or the offshore wave buoy measurements and estimated the available nearshore wave power. For the Mediterranean nearshore, the wave power in the western side of Sicily has been estimated to be close to 8 kW/m by Iuppa et al [23] and 5 kW/m by Monteforte et al [32].…”

Section: Assessment Of the Nearshore Potentialmentioning

confidence: 99%

Wave Energy Assessment and Performance Estimation of State of the Art Wave Energy Converters in Italian Hotspots

Vannucchi

Cappietti

2016

Sustainability

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This paper presents an assessment of offshore wave energy potential at the scale of the whole Mediterranean Sea. The offshore wave data were propagated, by means of numerical modeling, toward four Italian coastal areas, namely stretches of coast of Tuscany, Liguria, Sardinia and Sicily. For each area, the wave power and the monthly, seasonal and annual variability at water depths of 50 m and 15 m were analyzed and hotspots were located. The results show strong variability of the wave energy potential from point to point of the same area thus highlighting the need for spatially detailed analysis. The higher values of wave energy potential are located in the hotspots of Sardinia and Sicily, at 11.4 kW/m and 9.1 kW/m, respectively. The Tuscany and the Liguria hotspots are characterized, respectively, by 4.7 kW/m and 2.0 kW/m. In order to point out which state of the art WEC is best suited for the Italian areas, the performances of six different state of the art Wave Energy Converters (WECs) were evaluated. Finally, a comparison of the performances of each WEC in the selected Italian sites and in some European (EU) oceanic sites was conducted. The energy potential in the most energetic EU oceanic site, among those here investigated, is up to 38-times greater than the potentials in the studied Italian areas but the power output, of the best WEC technology, is no more than nine times greater.

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Wave power potential assessment of Aegean Sea with an integrated 15-year data

Cited by 47 publications

References 41 publications

Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

Spatial Distribution of the Baltic Sea Near-Shore Wave Power Potential along the Coast of Klaipėda, Lithuania

Wave Energy Assessment and Performance Estimation of State of the Art Wave Energy Converters in Italian Hotspots

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