scholarly journals Comparative Study on Impacts of Power Curve Model on Capacity Factor Estimation of Pitch-Regulated Turbines

2012 ◽  
Vol 9 (2) ◽  
pp. 36 ◽  
Author(s):  
MH Albadi ◽  
EF El-Saadany
Keyword(s):  
Wind Speed ◽  
Average Energy ◽  
Capacity Factor ◽  
Power Curve ◽  
Performance Curve ◽  
Power Performance ◽  
Wind Speeds ◽  
Curve Model ◽  
Mean Wind Speed ◽  
Turbine Output

The amount of energy produced by a turbine depends on the characteristics of both wind speed at the site under investigation and the turbine's power performance curve. The capacity factor (CF) of a wind turbine is commonly used to estimate the turbine's average energy production. This paper investigates the effect of the accuracy of the power curve model on CF estimation. The study considers three CF models. The first CF model is based on a power curve model that underestimates the turbine output throughout the ascending segment of the power curve. To compensate for the aforementioned discrepancy, the Weibull parameters, c and k, which are used to describe wind profile, are calculated based on cubic mean wind speed (CMWS). The second CF model is based on the most accurate generic power curve model available in open literature. The third CF model is based on a new model of power performance curve which mimics the behavior of a typical pitch-regulated turbine curve. As the coefficients of this power curve model are based on a general estimation of the turbine output at different wind speeds, they can be further tuned to provide a more accurate fit with turbine data from a certain manufacturer. 

scholarly journals Nacelle power curve measurement with spinner anemometer and uncertainty evaluation

2016 ◽  
Author(s):  
Giorgio Demurtas ◽  
Troels Friis Pedersen ◽  
Rozenn Wagner
Keyword(s):  
Wind Speed ◽  
Transfer Function ◽  
Probability Distribution ◽  
Wind Turbines ◽  
Energy Production ◽  
Power Curve ◽  
Power Performance ◽  
Mean Wind Speed ◽  
Set Up ◽  
Power Curves

Abstract. The objective of this investigation was to verify the feasibility of using the spinner anemometer calibration and nacelle transfer function determined on one reference turbine, to assess the power performance of a second identical turbine. An experiment was set up with a met-mast in a position suitable to measure the power curve of the two wind turbines, both equipped with a spinner anemometer. An IEC 61400-12-1 compliant power curve was then measured for both turbines using the met-mast. The NTF (Nacelle Transfer Function) was measured on the reference turbine and then applied to both turbines to calculate the free wind speed. For each of the two wind turbines, the power curve (PC) was measured with the met-mast and the nacelle power curve (NPC) with the spinner anemometer. Four power curves (two PC and two NPC) were compared in terms of AEP (Annual Energy Production) for a Rayleigh wind speed probability distribution. For each turbine, the NPC agreed with the corresponding PC within 0.10 % of AEP for the reference turbine and within 0,38 % for the second turbine, for a mean wind speed of 8 m/s.

scholarly journals Nacelle power curve measurement with spinner anemometer and uncertainty evaluation

2017 ◽  
Vol 2 (1) ◽  
pp. 97-114 ◽  
Author(s):  
Giorgio Demurtas ◽  
Troels Friis Pedersen ◽  
Rozenn Wagner
Keyword(s):  
Wind Speed ◽  
Transfer Function ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Power Curve ◽  
Power Performance ◽  
Mean Wind Speed ◽  
Set Up ◽  
Power Curves

Abstract. The objective of this investigation was to verify the feasibility of using the spinner anemometer calibration and nacelle transfer function determined on one reference wind turbine, in order to assess the power performance of a second identical turbine. An experiment was set up with a met mast in a position suitable to measure the power curve of the two wind turbines, both equipped with a spinner anemometer. An IEC 61400-12-1-compliant power curve was then measured for both wind turbines using the met mast. The NTF (nacelle transfer function) was measured on the reference wind turbine and then applied to both turbines to calculate the free wind speed. For each of the two wind turbines, the power curve (PC) was measured with the met mast and the nacelle power curve (NPC) with the spinner anemometer. Four power curves (two PCs and two NPCs) were compared in terms of AEP (annual energy production) for a Rayleigh wind speed probability distribution. For each wind turbine, the NPC agreed with the corresponding PC within 0.10 % of AEP for the reference wind turbine and within 0.38 % for the second wind turbine, for a mean wind speed of 8 m s−1.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

scholarly journals Validation of Dual-Doppler Wind Profiles with in situ Anemometry

2015 ◽  
Vol 32 (5) ◽  
pp. 943-960 ◽  
Author(s):  
W. Scott Gunter ◽  
John L. Schroeder ◽  
Brian D. Hirth
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Atmospheric Conditions ◽  
Wind Speeds ◽  
Time Histories ◽  
Mean Wind Speed ◽  
Wind Profiles

AbstractTypical methods used to acquire wind profiles from Doppler radar measurements rely on plan position indicator (PPI) scans being performed at multiple elevation angles to utilize the velocity–azimuth display technique or to construct dual-Doppler synthesis. These techniques, as well as those employed by wind profilers, often produce wind profiles that lack the spatial or temporal resolution to resolve finescale features. If two radars perform range–height indicator (RHI) scans (constant azimuth, multiple elevations) along azimuths separated by approximately 90°, then the intersection of the coordinated RHI planes represents a vertical set of points where dual-Doppler wind syntheses are possible and wind speed and direction profiles can be retrieved. This method also allows for the generation of high-resolution wind time histories that can be compared to anemometer time histories. This study focuses on the use of the coordinated RHI scanning strategy by two high-resolution mobile Doppler radars in close proximity to a 200-m instrumented tower. In one of the first high-resolution, long-duration comparisons of dual-Doppler wind synthesis with in situ anemometry, the mean and turbulence states of the wind measured by each platform were compared in varying atmospheric conditions. Examination of mean wind speed and direction profiles in both clear-air (nonprecipitating) and precipitating environments revealed excellent agreement above approximately 50 m. Below this level, dual-Doppler wind speeds were still good but slightly overestimated as compared to the anemometer-measured wind speeds in heavy precipitation. Bulk turbulence parameters were also slightly underestimated by the dual-Doppler syntheses.

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

scholarly journals Evaluation of wind characteristics in Bac Lieu in 2016 using the weibull function

2017 ◽  
Vol 17 (4B) ◽  
pp. 37-43
Author(s):  
Pham Xuan Thanh ◽  
Nguyen Xuan Anh ◽  
Le Van Luu ◽  
Hiep Van Nguyen ◽  
Hoang Hai Son ◽  
...  
Keyword(s):  
Wind Speed ◽  
Shape Factor ◽  
Maximum Energy ◽  
Weibull Function ◽  
Data Set ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
Two Parameters ◽  
Factor C

In this paper, the characteristics of wind speed at 20 m height at the Bac Lieu atmospheric physic station (Bac Lieu station) in 2016 were evaluated using the Weibull distribution function. The wind speed data set (every minute) from January 7th  to December 31st, 2016 was used to calculate the two parameters of  Weibull function including Weibull shape factor “k” and Weibull scale factor “c”. The results showed that at the Bac Lieu station in 2016, the values of k and c were 1.69 and 3.91, respectively. Some characteristics of wind speed were also estimated such as wind energy density (Pa/A=57.3 W/m2), wind speed of maximum energy carrier (Vmec=6.2 m/s), the most probable wind speed (Vmp=2.3 m/s), mean wind speed (Vmean­=3.5 m/s)  and standard deviation of wind speeds (s = 2.1 m/s).

scholarly journals Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models

2018 ◽  
Author(s):  
Laban N. Ongaki ◽  
Christopher M. Maghanga ◽  
Joash Kerongo
Keyword(s):  
Wind Speed ◽  
Rayleigh Distribution ◽  
Series Data ◽  
Energy Potential ◽  
Distribution Models ◽  
Wind Speeds ◽  
Average Wind ◽  
Mean Wind Speed ◽  
Wind Energy Potential

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68oS, 34.79o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m2, 181.75W/m2, 470.4W/m2 and 879.9W/m2 respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

scholarly journals The Potential Wind Power Resource in Central-South of the Constanta County

2019 ◽  
Vol 15 (3) ◽  
pp. 1-12
Author(s):  
Emilian Boboc
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Extreme Values ◽  
Reanalysis Data ◽  
Value Theory ◽  
Physical Models ◽  
Structural Safety ◽  
Energy Yield ◽  
Wind Speeds ◽  
Mean Wind Speed

Abstract Usually, wind turbine generator’s structures or radio masts are located in wind exposed sites. The paper aims to investigate the wind conditions in the nearby area of Cobadin Commune, Constanta County, Romania at heights of 150-200m above the surface using global reanalysis data sets CFSR, ERA 5, ERA I and MERRA 2. Using the extreme value theory and the physical models of the datasets, the research focuses on the assessment of the maximum values that are expected for the wind speeds, but the wind statistics created can be used for a further wind or energy yield calculation. Without reaching the survival wind speed for wind turbine generators, with mean wind speed values higher than 7 m/s and considering the cut-in and cut-out wind speeds of 3 m/s, respectively 25 m/s, the site can be exploited in more than 90% of the time to generate electricity, thus, the paper is addressed to the investors in the energy of renewable sources. At the same time, the insights of the wind characteristics and the knowledge of the extreme values of the wind speed can be useful, not just for the designers, in the rational assessment of the structural safety of wind turbines, but also those evaluating the insured losses.

scholarly journals Assessment of wind energy potential in East Azarbaijan province of Iran (Case Stady: Sahand station)

2015 ◽  
Vol 17 (2) ◽  
pp. 418-425
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Fossil Fuels ◽  
Ground Level ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Seasonal Wind

<p>Today&#39;s world requires a change in how the use of different types of energy. With declining reserves of fossil fuels for renewable energies is of course the best alternative. Among the renewable energy from the wind can be considered one of the best forms of energy can be introduced. Accordingly, most countries are trying to identify areas with potential to benefit from this resource.</p> <p>The aim of this study was to assess the potential wind power in Sahand station of Iran country. Hourly measured long term wind speed data of Sahand during the period of 2000-2013 have been statistically analyzed. In this study the wind speed frequency distribution of location was found by using Weibull distribution function. The wind energy potential of the location has been studied based on the Weibull mode. The results of this study show that mean wind speed measured at 10 m above ground level is determined as 5.16 m/s for the studied period. This speed increases by, respectively, 34.78 % and 41.21 %, when it is extrapolated to 40 and 60 m hub height.</p> <div> <p>Long term seasonal wind speeds were found to be relatively higher during the period from January to September. At the other hand, higher wind speeds were observed between the period between 06:00 and 18:00 in the day. These periods feet well with annual and daily periods of maximum demand of electricity, respectively.&nbsp;</p> </div> <p>&nbsp;</p>

ANALYSIS OF PEDESTRIAN-LEVEL WIND VELOCITY IN FOUR NEIGHBOURHOODS IN KLANG VALLEY

2015 ◽  
Vol 76 (5) ◽  
Author(s):  
Azli Abd Razak ◽  
Mohd Azhari Mohd Rodzi ◽  
Amirul Hakim Jumali ◽  
Sheikh Ahmad Zaki
Keyword(s):  
Wind Speed ◽  
Field Measurements ◽  
Area Ratio ◽  
Frontal Area ◽  
Speed Ratio ◽  
Pollution Dispersion ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Klang Valley ◽  
The Mean

Urban ventilation is important for the purpose of pollution dispersion, indoor ventilation for free running buildings and urban thermal comfort. In comparison to suburban cities, high-density cities have very low wind speeds at pedestrian level due to the densely built buildings blocking the wind and creating stagnant zones locally. Under this circumstance, field measurements were performed to investigate the performance of pedestrian wind at four major cities in Klang Valley. Mean wind speed was measured using anemometers at 1 minute data interval for 3 hours  and the  data collection for each case were obtained at pedestrian level. The mean wind speed ratio was plotted against the frontal area ratio and plan area ratio. The result indicates that: (1) the mean wind speed dramatically decreases with the increase of plan area ratio and (2) the mean wind speed exponentially decreases with the increase of frontal area ratio and qualitatively agrees with the power law relationship which is proposed by previous researcher. In addition, the frontal area ratio is considered as a better parameter to evaluate the performance of urban ventilation. 

Sign in / Sign up

Export Citation Format

Share Document