Wind speed description and power density in northern Spain

Herrero-Novoa, Cristina; Pérez, Isidro A.; Sánchez, M. Luisa; García, M. Ángeles; Pardo, Núria; Fernández-Duque, Beatriz

doi:10.1016/j.energy.2017.07.127

Cited by 32 publications

(14 citation statements)

References 62 publications

(64 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The location with the highest wind speed was Yuc2 (v m = 4.56 m/s, c = 5.10 m/s, and k = 3.07), and the lowest location, Yuc17, was inside a rainforest, which reduced the magnitude of the wind speed (v m = 2.67 m/s, c = 2.99, and k = 3.10). These results are in agreement with the study developed by Herrero-Novoa [30], where it was established that dividing an average year into two periods (spring-summer and fall-winter) provides more accuracy regarding wind characterization; in a similar fashion, for the current study, an average year was divided into four periods of time (seasons) where even more accurate wind periods were established. This allowed us to determine the wind characteristics, specifically its WPD, in the most relevant period.…”

Section: Seasonal Weibull Parameters and Wpdsupporting

confidence: 92%

“…Katinas et al [29] performed a study in Lithuania where the WPD was calculated after determining the Weibull parameters. In Spain, an evaluation of the WPD was done using the moment method for calculating the Weibull parameters [30]. Faghani et al [31] extrapolated data at high altitudes, calculated the Weibull parameters, and found out that variation of power density with time was significant; therefore, they divided the year in two periods, period I (spring and summer) and period II (autumn and winter).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Seasonal Wind Energy Characterization in the Gulf of Mexico

2019

View full text Add to dashboard Cite

In line with Mexico’s interest in determining its wind resources, in this paper, 141 locations along the states of the Gulf of Mexico have been analyzed by calculating the main wind characteristics, such as the Weibull shape (c) and scale (k) parameters, and wind power density (WPD), by using re-analysis MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications version 2) data with hourly records from 1980–2017 at a 50-m height. The analysis has been carried out using the R free software, whose its principal function is for statistical computing and graphics, to characterize the wind speed and determine its annual and seasonal (spring, summer, autumn, and winter) behavior for each state. As a result, the analysis determined two different wind seasons along the Gulf of Mexico;, it was found that in the states of Tamaulipas, Veracruz, and Tabasco wind season took place during autumn, winter, and spring, while for the states of Campeche and Yucatan, the only two states that shared its coast with the Caribbean Sea and the Gulf of Mexico, the wind season occurred only in winter and spring. In addition, it was found that by considering a seasonal analysis, more accurate information on wind characteristics could be generated; thus, by applying the Weibull distribution function, optimal zones for determining wind as a resource of energy can be established. Furthermore, a k-means algorithm was applied to the wind data, obtaining three clusters that can be seen by month; these results and using the Weibull parameter c allow for selecting the optimum wind turbine based on its power coefficient or efficiency.

show abstract

Section: Seasonal Weibull Parameters and Wpdsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Seasonal Wind Energy Characterization in the Gulf of Mexico

2019

View full text Add to dashboard Cite

show abstract

“…Thus, the ON1 location presents values of 5.459 m/s and 1.831 for the scale (c) and shape (k) parameters, respectively. In Herrero-Novoa et al [52], values for these Weibull distribution characteristic parameters are obtained based on field measurements, reported at 2, 10, and 50 m height from the meteorological stations distributed throughout Navarra region (42 • N, −1 • E). Since the values of the two parameters corresponding to the Weibull distribution are 4.98 m/s and 2.07 for c and k, respectively, when considering a 50 m height.…”

Section: Discussionmentioning

confidence: 99%

An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore

2020

View full text Add to dashboard Cite

The main objective of the present work is to provide a comprehensive picture of the wind conditions in the Spanish continental nearshore considering a state-of-the-art wind dataset. In order to do this, the ERA5 wind data, covering the 20-year time interval from 1999 to 2018, was processed and evaluated. ERA stands for ’ECMWF Re-Analysis’ and refers to a series of research projects at ECMWF (European Centre for Medium-Range Weather Forecasts) which produced various datasets. In addition to the analysis of the wind resources (reported for a 100 m height), the performances of several wind turbines, ranging from 3 to 9.5 MW, were evaluated. From the analysis of the spatial maps it was observed that the Northern part of this region presents significant wind resources, the mean wind speed values exceeding 9 m/s in some locations. On the other hand, in regard to the Southern sector, more energetic conditions are visible close to the Strait of Gibraltar and to the Gulf of Lion. Nevertheless, from the analysis of the data corresponding to these two Southern nearshore points it was observed that the average wind speed was lower than 8 m/s in both summer and winter months. Regarding the considered wind turbines, the capacity factor did in general not exceed 20%—however, we did observe some peaks that could reach to 30%. Finally, it can be highlighted that the Northern part of the Spanish continental nearshore is significant from the perspective of extracting offshore wind energy, especially considering the technologies based on floating platforms. Furthermore, because of the clear synergy between wind and wave energy, which are characteristic to this coastal environment, an important conclusion of the present work is that the implementation of joint wind–wave projects might be effective in the Northwestern side of the Iberian nearshore.

show abstract

“…They discussed some methods of estimating the Weibull parameters, but used the Empirical method of Justus in their work. This method was also used by Herrero-Novoa et al (2017) for studying the wind characteristics and power density in northern Spain. Nine different methods of estimating Weibull parameters were employed by Chaurasiya et al (2018) for the wind data at Kayathar in India.…”

Section: Introductionmentioning

confidence: 99%

Wind energy resource assessment for Vanuatu with accurate estimation of Weibull parameters

Singh

Bule

Khan

et al. 2019

Energy Exploration & Exploitation

View full text Add to dashboard Cite

Wind energy resource assessments for Pentecost Island and Epi Island in Vanuatu were carried out using one year of wind data. The wind data were used to calculate the daily average wind speed, diurnal variation of wind speed and monthly average wind speed. The diurnal variation of wind shear coefficient of the site was also studied and it correlated well with the temperature variation. Ten methods were used to determine the Weibull parameters and the wind power density of the site. The best method was determined using the goodness of fit test/error where the correlation coefficient, coefficient of efficiency, root mean square error, maximum absolute error and maximum absolute percentage error for the 10 methods were compared. It was found that the moments method was the best method for obtaining the shape parameter (k), the scale parameter (A) and the correct wind power density for the Pentecost Island site, whereas for the Epi site, the median and quartiles method performed the best. The mean wind speed for the Pentecost site was 5.60 m/s, while that for the Epi site was 5.86 m/s. The Weibull parameters were also estimated for the two seasons for both the islands. The wind resource maps showing the wind power density were also obtained. The annual energy production from 10 Vergnet 275 kW wind turbines, positioned at good locations on the digital wind map, was estimated. Finally, an economic analysis of the turbines was carried out, which indicated a payback period of 4.85 years.

show abstract

Wind speed description and power density in northern Spain

Cited by 32 publications

References 62 publications

Seasonal Wind Energy Characterization in the Gulf of Mexico

Seasonal Wind Energy Characterization in the Gulf of Mexico

An Evaluation of the Wind Energy Resources along the Spanish Continental Nearshore

Wind energy resource assessment for Vanuatu with accurate estimation of Weibull parameters

Contact Info

Product

Resources

About