Wave energy resource assessment along the Algerian coast based on 39-year wave hindcast

Amarouche, Khalid; Akpınar, Adem; Bachari, Nour El Islam; Houma, Fouzia

doi:10.1016/j.renene.2020.02.040

Cited by 48 publications

(19 citation statements)

References 64 publications

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“…In spite of increased spatial resolutions (and similar discretization in frequencies and directions) than in shelf-scale investigations, these resource assessments may cover several decades. Amarouche et al [97] implemented thus a 39-year wave simulation based on SWAN along the Algerian basin by adopting a spatial resolution of 0.033 • ( 3 km). Predictions, assessed against a series of six coastal wave-buoy observations, were exploited to identify the area with the highest WEDI index (Equation 9) and exhibit the high wave potential of the eastern coast of Algeria.…”

Section: Shelf-scale Investigationsmentioning

confidence: 99%

Wave Energy Resource Assessment for Exploitation—A Review

Guillou

Lavidas²,

Chapalain

2020

JMSE

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Over recent decades, the exploitation of wave energy resources has sparked a wide range of technologies dedicated to capturing the available power with maximum efficiency, reduced costs, and minimum environmental impacts. These different objectives are fundamental to guarantee the development of the marine wave energy sector, but require also refined assessments of available resource and expected generated power to optimize devices designs and locations. We reviewed here the most recent resource characterizations starting from (i) investigations based on available observations (in situ and satellite) and hindcast databases to (ii) refined numerical simulations specifically dedicated to wave power assessments. After an overall description of formulations and energy metrics adopted in resource characterization, we exhibited the benefits, limitations and potential of the different methods discussing results obtained in the most energetic locations around the world. Particular attention was dedicated to uncertainties in the assessment of the available and expected powers associated with wave–climate temporal variability, physical processes (such as wave–current interactions), model implementation and energy extraction. This up-to-date review provided original methods complementing the standard technical specifications liable to feed advanced wave energy resource assessment.

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Section: Shelf-scale Investigationsmentioning

confidence: 99%

Wave Energy Resource Assessment for Exploitation—A Review

Guillou

Lavidas²,

Chapalain

2020

JMSE

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“…To evaluate the temporal variability of the WPD in the offshore waters of Taiwan, the MVI and COV were calculated via Equations ( 13) and (14), respectively. The offshore areas displayed a relatively low MVI, and the COV presented weaker temporal variability; therefore, these offshore areas are considered to be potential zones for installing wave energy converters [64,65]. The spatial distribution of the MVI for the WPD in the offshore waters of Taiwan averaged over 1991 to 2010 is depicted in Figure 13.…”

Section: Variability Of Wave Powermentioning

confidence: 99%

Assessment of Offshore Wave Energy Resources in Taiwan Using Long-Term Dynamically Downscaled Winds from a Third-Generation Reanalysis Product

et al. 2021

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In this study, long-term wind fields during 1991–2010 from the Climate Forecast System Reanalysis (CFSR) were dynamically downscaled over Taiwan and its offshore islands at a 5 km horizontal resolution using the Weather Research and Forecasting (WRF) model. Simulations of the 10 m (above sea level) dynamically downscaled winds served as the atmospheric forcing for driving a fully coupled wave-circulation model. The sea states of the waters surrounding Taiwan during 1991–2010 were hindcasted to evaluate the offshore wave energy resources and optimal wave energy hotspots. This study reveals that the southeastern offshore waters of Taiwan and the Central Taiwan Strait exhibited the highest mean wave power density (WPD), exceeding 20 kW/m. The annual mean WPD, incidence of the hourly WPD greater than or equal to 4 kW/m, monthly variability index and coefficient of variation of the WPD indicated that the sea areas located between Green Island and Orchid Island (OH_1), southeast of Orchid Island (OH_2), south of the Hengchun Peninsula (OH_3), and north of the Penghu Islands (OH_4) were the optimal hotspots for deploying wave energy converters. The most energetic months were October for OH_1 and OH_2 and November for OH_3 and OH_4, while the wave power was weak from March to June for OH_1, OH_2 and OH_3 and in May for OH_4. The wave direction is prevailingly east-northeast for OH_1, OH_2 and OH_3 and nearly northeast for OH_4. These phenomena reveal that wave power in the waters offshore Taiwan is induced primarily by the northeast (winter) monsoon. The exploitable annual WPD was estimated to be 158.06, 182.89, 196.39 and 101.33 MWh/m for OH_1, OH_2, OH_3 and OH_4, respectively.

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“…The first database is CFSR v1 (Saha et al 2010), which covers the period from 1979 to 2010, with a spatial resolution of 0.3125° and the second database is CFSR v2 (Saha et al 2014), which covers the period from 2010 to the present, with a spatial resolution of 0.204°. The choice of CFSR wind data was based on two main criteria (Amarouche et al 2020a). Firstly, the high temporal resolution of 1 h, which allows a better estimation of storm peaks (Tiberi-Wadier et al 2016;Akpinar and Ponce de León 2016;Çakmak et al 2019).…”

Section: Copernicusmentioning

confidence: 99%

New Wind-Wave Climate Records in the Western Mediterranean Sea

Amarouche

Bingölbali

Akpınar

2021

Preprint

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This study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analyzed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in a large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends. Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilization to prevent probable catastrophic wave storms and ensure sustainable and economic development.

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Wave energy resource assessment along the Algerian coast based on 39-year wave hindcast

Cited by 48 publications

References 64 publications

Wave Energy Resource Assessment for Exploitation—A Review

Wave Energy Resource Assessment for Exploitation—A Review

Assessment of Offshore Wave Energy Resources in Taiwan Using Long-Term Dynamically Downscaled Winds from a Third-Generation Reanalysis Product

New Wind-Wave Climate Records in the Western Mediterranean Sea

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