Wind energy resource assessment of Izmit in the West Black Sea Coastal Region of Turkey

Küçükali, Serhat; Dinçkal, Çiğdem

doi:10.1016/j.rser.2013.11.018

Cited by 35 publications

(21 citation statements)

References 7 publications

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“…Offshore wind energy resources are mainly estimated from in situ wind measurements [8], satellite data, numerical simulation results [9], and reanalysis data [10][11][12]. With progress in microwave remote sensing, a great deal of satellite-derived data have been obtained and applied in the study of wind energy resources, including sea surface wind distribution data derived from Synthetic Aperture Radars (SAR) and scatterometers, such as the Earth Resources Satellite ERS-2 SAR (1995-2011) [13,14], Environment Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) [14][15][16][17][18][19], RADARSAT-1 SAR (1995 [20], SeaWinds onboard QuikSCAT (1999QuikSCAT ( -2009 [17,[19][20][21][22][23][24][25][26][27], ASCAT onboard METOP-A (2007-present) [17,18,27,28] and OceanSat-2 scatterometer (OSCAT, 2009-present) [28,29].…”

Section: Introductionmentioning

confidence: 99%

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Guo

Zhang

et al. 2018

Remote Sensing

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Wind energy, as a vital renewable energy source, also plays a significant role in reducing carbon emissions and mitigating climate change. It is therefore of utmost necessity to evaluate ocean wind energy resources for electricity generation and environmental management. Ocean wind distribution around the globe can be obtained from satellite observations to compensate for limited in situ measurements. However, previous studies have largely ignored uncertainties in ocean wind energy resources assessment with multiple satellite data. It is against this background that the current study compares mean wind speeds (MWS) and wind power densities (WPD) retrieved from scatterometers (QuikSCAT, ASCAT) and radiometers (WindSAT) and their different combinations with National Data Buoy Center (NDBC) buoy measurements at heights of 10 m and 100 m (wind turbine hub height) above sea level. Our results show an improvement in the accuracy of wind resources estimation with the use of multiple satellite observations. This has implications for the acquisition of reliable data on ocean wind energy in support of management policies.

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Section: Introductionmentioning

confidence: 99%

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Guo

Zhang

et al. 2018

Remote Sensing

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“…As shown in Figure 3, at lower heights, turbulence intensity is higher. This is due to the fact that terrain influence on air flow decreases with height [2]. Those data indicate that wind turbines are subject to lower turbulence loads at higher levels.…”

Section: Introductionmentioning

confidence: 79%

Adaptive decision fusion based framework for short-term wind speed and turbulence intensity forecasting: case study for North West of Turkey

Dinçkal¹,

Töreyi̇n²,

Küçükali³

2017

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, an online learning framework called adaptive decision fusion (ADF) is employed for short-term wind speed and turbulence intensity forecasting by use of wind speed data for each season for the city ofİzmit, located in the northwest of Turkey. Fixed-weight (FW) linear combination is derived and used for comparison with ADF. Wind speeds and turbulence intensities are predicted from the existing wind speed data and computed turbulence intensities, respectively, using the ADF and FW methods. Simulations are carried out for each season and the results are tested on mean absolute percentage error criterion. It is shown that the proposed model captured the system dynamic behavior and made accurate predictions based on the seasonal wind speed characteristics of the site. The procedure described here can be used to estimate the local velocity and turbulence intensity in a wind power plant during a storm.

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“…was used to study the wind energy resource in the Turkish coastal area of Izmit, in the western Black Sea. 77 The annual average wind speed was found to be 6 ms -1 . Nine years of wind measurements taken at 10m a.g.l at meteorological stations in the central and eastern Black Sea region were used to determine that the annual mean wind speed ranges from 1.53 to 4.06 ms −1 , with the highest wind power potential found in the Sinop (wind energy density of 59.96 Wm -2 ), Hopa, and Trabzon areas.…”

Section: Studies Of Offshore Wind and Power In Europe Under Present Cmentioning

confidence: 95%

“…One year of wind measurements at 50 m a.s.l. was used to study the wind energy resource in the Turkish coastal area of Izmit, in the western Black Sea . The annual average wind speed was found to be 6 ms –1 .…”

Section: Determination Of the Best Locations From A Physical Point Ofmentioning

confidence: 99%

An overview of offshore wind energy resources in Europe under present and future climate

deCastro

Costoya

Salvador

et al. 2018

Annals of the New York Academy of Sciences

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Long-term sustainable development of European offshore wind energy requires knowledge of the best places for installing offshore wind farms. To achieve this, a good knowledge of wind resources is needed, as well as knowledge of international, European, and national regulations regarding conflict management, marine environment conservation, biodiversity protection, licensing processes, and support regimes. Such a multidisciplinary approach could help to identify areas where wind resources are abundant and where conflicts with other interests are scarce, support measures are greater, and licensing processes are streamlined. An overview of offshore wind power studies at present, and of their future projections for the 21st century, allows for determining the optimal European locations to install or maintain offshore wind farms. Only northern Europe, the northwest portion of the Iberian Peninsula, the Gulf of Lyon, the Strait of Gibraltar, and the northwest coast of Turkey show no change or increase in wind power, revealing these locations as the most suitable for installing and maintaining offshore wind farms in the future. The installation of wind farms is subject to restrictions established under international law, European law, and the domestic legal framework of each EU member state. Europe is moving toward streamlining of licensing procedures, reducing subsidies, and implementing auction systems.

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Wind energy resource assessment of Izmit in the West Black Sea Coastal Region of Turkey

Cited by 35 publications

References 7 publications

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

Adaptive decision fusion based framework for short-term wind speed and turbulence intensity forecasting: case study for North West of Turkey

An overview of offshore wind energy resources in Europe under present and future climate

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