Investigation of wind shear coefficients and their effect on electrical energy generation

Fırtın, Ebubekir; Güler, Önder; Akdağ, Seyit Ahmet

doi:10.1016/j.apenergy.2011.05.025

Cited by 102 publications

(56 citation statements)

References 17 publications

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“…In this context, sea level observations are used for the operational activities; on the other hand, hub level observations are used for the power production calculations, for the maintenance activities that require equipment lifting, and also for the helicopter access. Although there are many models to extrapolate wind speed to different altitudes, the wind power law developed by Justus and Mikhail (1976) is the most widely used method (Fırtın et al, 2011); therefore, the wind power law in Eq. (1) is adopted to calculate the wind speed values at hub level and sea level.…”

Section: Climatementioning

confidence: 99%

Advanced logistics planning for offshore wind farm operation and maintenance activities

et al. 2015

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Offshore wind turbine technology is moving forward as a cleaner alternative to the fossil fuelled power production. However, there are a number of challenges in offshore; wind turbines are subject to different loads that are not often experienced onshore and more importantly challenging wind and wave conditions limit the operability of the vessels needed to access offshore wind farms. As the power generation capacity improves constantly, advanced planning of Operation and Maintenance (O&M)activities, which supports the developers in achieving reduced downtime, optimised availability and maximised revenue, has gained vital importance. In this context, the focus of this research is the investigation of the most cost-effective approach to allocate O&M resources which may include helicopter, crew transfer vessels, offshore access vessels, and jack-up vessels. This target is achieved through the implementation of a time domain Monte-Carlo simulation approach which includes analysis of environmental conditions (wind speed, wave height, and wave period), operational analysis of transportation systems, investigation of failures (type and frequency), and simulation of repairs. The developed methodology highlights how the O&M fleets can be operated in a cost-effective manner in order to support associated day-to-day O&M activities and sustain continuous power production

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Section: Climatementioning

confidence: 99%

Advanced logistics planning for offshore wind farm operation and maintenance activities

et al. 2015

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“…Rehman and Al-Abbadi [19] analyzed the effects wind shear on energy production. Firtin et al [21] described the importance of accurate determination of wind shear and stated that is critical for near reality assessment of wind energy yield. The mean wind shear coefficient for Nooriabad is 0.24 as given in Table 2 …”

Section: Site-specific Wind Shearmentioning

confidence: 99%

“…Rehman and Al-Abbadi [19,20] investigated wind shear and its effects on energy production and concluded the significant influence by the seasonal and diurnal changes. Firtin et al [21] suggested that accurate determination of wind shear is critical to design and optimization of wind power investment. Wind turbines are constantly subjected to asymmetrical loads like wind shear which will lead to unsteady loading upon the blade and affect its performance [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Technical and economic assessment of wind power potential of Nooriabad, Pakistan

2017

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Background: Pakistan is a developing nation and heavily spends on the development of conventional power plants to meet the national energy demand. The objective of this paper is to investigate wind power potential of site using wind speed, wind direction, and other meteorological data collected over a period of 1 year. This type of detailed investigation provides information of wind characteristics of potential sites and helps in selecting suitable wind turbine. Methods: The site-specific air density, wind shear, wind power density, annual energy yield, and capacity factors have been calculated at 30 and 50 m above the ground level (AGL). The Weibull parameters have been calculated using empirical (EM), maximum likelihood (MLM), modified maximum likelihood (MMLM), energy pattern (EPFM), and graphical (GM) methods to determine the other dependent parameters. The accuracies of these methods are determined using correlation coefficient (R

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“…The wind shear coefficient α depends on the stability of the atmosphere and can be derived empirically, but the results are very sensitive to a correct modelling and the right assumptions (Fırtın et al, 2011). The power law gives a "reasonable first approximation" (Brown et al, 1984(Brown et al, , p. 1190.…”

Section: Vertical Extrapolationmentioning

confidence: 99%

Designing an index for assessing wind energy potential

et al. 2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. To meet the increasing global demand for renewable energy such as wind energy, more and more new wind parks are installed worldwide. Finding a suitable location, however, requires a detailed and often costly analysis of the local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. In this paper, we suggest a new approach of assessing the local wind energy potential: Meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at turbine location and hub height; then, with actual high-frequency production data, the relation between wind data and energy production is determined via a five parameter logistic function. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of wind power potential for whole Germany exemplifies the approach. Terms of use: Documents in

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Investigation of wind shear coefficients and their effect on electrical energy generation

Cited by 102 publications

References 17 publications

Advanced logistics planning for offshore wind farm operation and maintenance activities

Advanced logistics planning for offshore wind farm operation and maintenance activities

Technical and economic assessment of wind power potential of Nooriabad, Pakistan

Designing an index for assessing wind energy potential

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