Wind resource assessment of the Southern Appalachian Ridges in the Southeastern United States

Raichle, B. W.; Carson, W.R.

doi:10.1016/j.rser.2007.12.005

Cited by 49 publications

(17 citation statements)

References 1 publication

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“…Jowder [20] for countries like Korea [24], China [25], Malaysia [26], India [27], Kyrgyzstan [28], Pakistan [29], Oman [30], Turkey [31], Algeria [32], Iran [33], Egypt [34], Nigeria [35], Greece [36], Mexico [37], USA [38] and Venezuela [39] were reviewed to assess the methodology and techniques used for WRA.…”

Section: Introductionmentioning

confidence: 99%

Wind speed and power characteristics for Jubail industrial city, Saudi Arabia

Baseer

Meyer

Alam

et al. 2015

Renewable and Sustainable Energy Reviews

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Abstract:This paper presents the wind characteristics and resource assessment of the largest industrial base in the Middle East (Jubail industrial city) using measured hourly mean wind speed data at 10, 50 and 90 m above ground level (AGL) from 2008 to 2012. At respective heights, the mean wind speeds were found to be 3.34, 4.79 and 5.35 m/s. At 50 and 90 m AGL, the availability of wind speed above 3.5 m/s was more than 75%. The prevailing wind direction was from the north-west. The local wind shear exponent calculated using measured wind speed values at three heights was found to be 0.217.The mean wind power density values at measurement heights were 50.92, 116.03 and 168.46 W/m 2 respectively. The comparison of energy output from five commercially selected wind turbines of rated power ranging from 1.8 -3.3 MW showed that the most efficient wind turbine is 3.0 MW rated power. The annual energy production from this turbine was estimated to be 6,285 MWh with a plant capacity factor of 25%.

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Section: Introductionmentioning

confidence: 99%

Wind speed and power characteristics for Jubail industrial city, Saudi Arabia

Baseer

Meyer

Alam

et al. 2015

Renewable and Sustainable Energy Reviews

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“…So, wind energy appears as a clean and good solution to cope with a great part of this energy demand [3]. Recently, many researchers [4][5][6][7] have studied the wind energy resources in the sites all over the world. In Senegal, the development of new wind projects continues to be hampered by the lack of knowledge of wind potential and the absence of reliable and accurate wind resource data in many parts of the country.…”

Section: Introductionmentioning

confidence: 99%

Economic analysis of wind electricity generation in the northern coast of Senegal

Bilal

Kébé

Sabourin

et al. 2014

Int. J. Metrol. Qual. Eng.

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Abstract. The main target of this paper is to determine the seasonal features of the wind speed in the northwestern of Senegal and to assess the cost of annual energy output using wind turbines provided from several manufactures. The wind data used for this study were collected in four sites located in the northwestern coast of Senegal and cover the period of one year. The seasonal mean wind speed and the annual distribution curves were obtained by using the Weibull distribution function. A technical assessment of electricity generation from five big wind turbines which power is between 640 kW and 2000 kW and from six small wind turbines which power is between 250 W and 10 kW were carried out. The results obtained show that the lower cost (0.0265 e/kWh in Sokhar) was observed for the wind turbine Ecotècnia 62. The highest cost was 0.5103 e/kWh (in Gandon) observed for the technology of Alize. All wind turbines was better suited to the site of Sokhar with the highest capacity factor and the lowest cost of output energy.

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“…Brower [13] developed maps for monthly and annual mean wind speeds in Iowa using wind speed data from 21 locations, which would be beneficial for interested wind farms developers to obtain reasonably accurate estimates of potential wind energy production in Iowa. Raichle and Carson [14] reported that ridges in the Southern Appalachian Mountain region are suitable for utility-scale wind development. Muzathik et al [15] studied the daily, monthly and annual wind speed along with their prevailing direction at a site in Terengganu, Malaysia, and concluded that small (kW range) wind machines could be used to provide power during the northeast monsoon season.…”

Section: Introductionmentioning

confidence: 99%

Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

2011

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a b s t r a c tWind energy has become a major competitor of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, wind with reasonable speed is not adequately sustainable everywhere to build an economical wind farm. The potential site has to be thoroughly investigated at least with respect to wind speed profile and air density. Wind speed increases with height, thus an increase of the height of turbine rotor leads to more generated power. Therefore, it is imperative to have a precise knowledge of wind speed profiles in order to assess the potential for a wind farm site. This paper proposes a clustering algorithm based neuro-fuzzy method to find wind speed profile up to height of 100 m based on knowledge of wind speed at heights 10, 20, 30, 40 m. The model estimated wind speed at 40 m based on measured data at 10, 20, and 30 m has 3% mean absolute percent error when compared with measured wind speed at height 40 m. This close agreement between estimated and measured wind speed at 40 m indicates the viability of the proposed method. The comparison with the 1/7th law and experimental wind shear method further proofs the suitability of the proposed method for generating wind speed profile based on knowledge of wind speed at lower heights.

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Wind resource assessment of the Southern Appalachian Ridges in the Southeastern United States

Cited by 49 publications

References 1 publication

Wind speed and power characteristics for Jubail industrial city, Saudi Arabia

Wind speed and power characteristics for Jubail industrial city, Saudi Arabia

Economic analysis of wind electricity generation in the northern coast of Senegal

Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

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