scholarly journals The Influence of the Wind Measurement Campaign Duration on a Measure-Correlate-Predict (MCP)-Based Wind Resource Assessment

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3606
Author(s):  
José V. P. Miguel ◽  
Eliane A. Fadigas ◽  
Ildo L. Sauer
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Farm ◽  
Target Location ◽  
Resource Assessment ◽  
Measurement Campaign ◽  
Wind Measurement ◽  
Wind Resource Assessment ◽  
Wind Resource

Driven by the energy auctions system, wind power in Brazil is undergoing a phase of expansion within its electric energy mix. Due to wind’s stochastic nature and variability, the wind measurement campaign duration of a wind farm project is required to last for a minimum of 36 months in order for it to partake in energy auctions. In this respect, the influence of such duration on a measure-correlate-predict (MCP) based wind resource assessment was studied to assess the accuracy of generation forecasts. For this purpose, three databases containing time series of wind speed belonging to a site were considered. Campaigns with durations varying from 2 to 6 years were simulated to evaluate the behavior of the uncertainty in the long-term wind resource and to analyze how it impacts a wind farm power output estimation. As the wind measurement campaign length is increased, the uncertainty in the long-term wind resource diminished, thereby reducing the overall uncertainty that pervades the wind power harnessing. Larger monitoring campaigns implied larger quantities of data, thus enabling a better assessment of wind speed variability within that target location. Consequently, the energy production estimation decreased, allowing an improvement in the accuracy of the energy generation prediction by not overestimating it, which could benefit the reliability of the Brazilian electric system.

scholarly journals Wind Resource Assessment on Puná Island

2019 ◽  
Vol 9 (14) ◽  
pp. 2923
Author(s):  
Yuri Merizalde ◽  
Luis Hernández-Callejo ◽  
Javier Gracia Bernal ◽  
Enrique Telmo Martínez ◽  
Oscar Duque-Perez ◽  
...  
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Low Cost ◽  
Resource Assessment ◽  
Wind Resource Assessment ◽  
The Pacific ◽  
The Hours ◽  
The Pacific Ocean ◽  
Wind Resource

Puná Island, located in the Pacific Ocean off the southern coast of Ecuador, has a population of approximately 3344 inhabitants. However, not all inhabitants have access to electricity, which is largely supplied by diesel generators. Therefore, to identify a renewable, sustainable, environmentally friendly and low-cost alternative, a 40-m-high anemometer tower was installed for wind resource assessment and to determine the possibility of generating electricity from wind energy. Based on mathematical models for electricity generation from wind energy, data were analyzed using the software Windographer and WAsP, to determine a long-term wind speed of 4.8 m/s and a mean wind power density of 272 W/m2. By simulating the use of a 3.3-MW wind turbine, we demonstrated that as much as 800 kWh could be generated during the hours when the wind reaches its highest speed. In addition to demonstrating the technical feasibility of meeting the electricity demands of Puná Island through wind power, this study exemplifies a method that can be used for wind resource assessment in any location.

scholarly journals A new formulation for rotor equivalent wind speed for wind resource assessment and wind power forecasting

Wind Energy ◽  
2015 ◽  
Vol 19 (8) ◽  
pp. 1439-1452 ◽  
Author(s):  
Aditya Choukulkar ◽  
Yelena Pichugina ◽  
Christopher T. M. Clack ◽  
Ronald Calhoun ◽  
Robert Banta ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Resource Assessment ◽  
Wind Power Forecasting ◽  
Wind Resource Assessment ◽  
New Formulation ◽  
Wind Resource ◽  
Power Forecasting

On the wind resource in Algeria: Probability distributions evaluation

2020 ◽  
pp. 095765092097588
Author(s):  
Houdayfa Ounis ◽  
Nawel Aries
Keyword(s):  
Wind Speed ◽  
Probability Distribution ◽  
Probability Distributions ◽  
Resource Assessment ◽  
Descriptive Statistics ◽  
The Other ◽  
Wind Speeds ◽  
Wind Resource Assessment ◽  
The Mean ◽  
Wind Resource

The present study aims to present a contribution to the wind resource assessment in Algeria using ERA-Interim reanalysis. Firstly, the ERA-Interim reanalysis 10 m wind speed data are considered for the elaboration of the mean annual 10 m wind speed map for a period starting from 01-01-2000 to 31-12-2017. Moreover, the present study intends to highlight the importance of the descriptive statistics other than the mean in wind resource assessment. On the other hand, this study aims also to select the proper probability distribution for the wind resource assessment in Algeria. Therefore, nine probability distributions were considered, namely: Weibull, Gamma, Inverse Gaussian, Log Normal, Gumbel, Generalized Extreme Value (GEV), Nakagami, Generalized Logistic and Pearson III. Furthermore, in combination with the distribution, three parameter estimation methods were considered, namely, Method of Moment, Maximum Likelihood Method and L-Moment Method. The study showed that Algeria has several wind behaviours due to the diversified topographic, geographic and climatic properties. Moreover, the annual mean 10 m wind speed map showed that the wind speed varies from 2.3 to 5.3 m/s, where 73% of the wind speeds are above 3 m/s. The map also showed that the Algerian Sahara is windiest region, while, the northern fringe envelopes the lowest wind speeds. In addition, it has been shown that the study of the mean wind speeds for the evaluation of the wind potential alone is not enough, and other descriptive statistics must be considered. On the other hand, among the nine considered distribution, it appears that the GEV is the most appropriate probability distribution. Whereas, the Weibull distribution showed its performance only in regions with high wind speeds, which, implies that this probability distribution should not be generalized in the study of the wind speed in Algeria.

Wind Resource Assessment for the Kingdom of Bahrain

2008 ◽  
Vol 32 (5) ◽  
pp. 439-448 ◽  
Author(s):  
Hanan Al Buflasa ◽  
David Infield ◽  
Simon Watson ◽  
Murray Thomson
Keyword(s):  
Wind Speed ◽  
Energy Production ◽  
Resource Assessment ◽  
Measured Data ◽  
Shape Parameters ◽  
Main Island ◽  
Wind Resource Assessment ◽  
Mean Wind Speed ◽  
Wind Resource ◽  
Hourly Basis

The geographical distribution of wind speed (the wind atlas) for the kingdom of Bahrain is presented, based on measured data and on calculations undertaken using WAsP,. The data used were recorded by the Meteorological Directorate at a weather station situated at Bahrain International Airport, taken on an hourly basis for a period of time extended for ten years. These data indicate an annual mean wind speed of 4.6 m/s at 10 m height and mean Weibull scale and shape parameters C and k of 5.2 m/s and 1.9 respectively. At a typical wind turbine hub height of sixty metres, these values are extrapolated to 6.9 m/s, 7.8 m/s and 1.8 respectively, which suggests that the area has a good wind resource. The wind atlas shows that several locations in the less populated central and southern regions of the main island of the archipelago of Bahrain are potentially suitable for wind energy production.

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