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[en] This article reports all the wind farms that have been carried out or are in project in France at the date of may 2015. All these installations represent an installed capacity of 13.817 MW including 3.524 MW that are in project (they are expected to enter into service during the next 3 years) and 434 MW that have been carried out during the first 5 months of 2015. A total of 1148 wind farms are reported. For each wind farm the following information is given: the name of the operator, the power output, the number of turbines, the name of the turbine manufacturer and the commissioning date. (A.C.)
[en] In the present study an evaluation of the potential for bend-twist coupling effects in wind turbine blades is addressed. A method for evaluation of the coupling magnitude based on the results of finite element modeling and full-field displacement measurements obtained by experiments is developed and tested on small-scale coupled composite beams. In the proposed method the coupling coefficient for a generic beam is introduced based on the Euler-Bernoulli beam formulation. By applying the developed method for analysis of a commercial wind turbine blade structure it is demonstrated that a bend-twist coupling magnitude of up to 0.2 is feasible to achieve in the baseline blade structure made of glass-fiber reinforced plastics. Further, by substituting the glass-fibers with carbon-fibers the coupling effect can be increased to 0.4. Additionally, the effect of introduction of bend-twist coupling into a blade on such important blade structural properties as bending and torsional stiffness is demonstrated
[en] Wind turbine manufacturers publish and certify power curves for their turbines. These turbine power curves are used for planning purposes and estimating total wind power production. When a wind plant consisting of many turbines connects to the utility grid and starts operation, the focus shifts to the entire plant's performance. An equivalent wind plant power-curve becomes highly desirable and useful in predicting plant output for a given wind forecast. For the purposes of this paper detailed data have been collected from a wind power plant to develop such an equivalent power curve. The method is evaluated using data from operational wind farms and the methods are compared to a modified IEC 61400-12 bin method. This paper will summarize available data, methodology, discuss the validation process and explore the applicability of such an approach on other wind power plants without detailed data. (author)
BackgroundThe development of wind energy in western Oklahoma has expanded dramatically in recent years, as the amount of installed capacity has gone from 0 in 2002 to enough turbines to generate approximately 20% of Oklahoma’s electrical needs in 2016. Associated with that development has been an increase in tax revenue and support for local schools, including many in struggling areas. This paper examines and quantifies the overall impact of the increased wind-industry related tax revenue in western Oklahoma.
MethodsVariables collected and analyzed for this study include: percentage of revenue from local and county sources, student-teacher ratios, and per-student expenditures. This information was obtained for each school district from 1997 to 2015. The data then mapped and analyzed using both statistical and inferential analysis. T tests and Mann Whitney U tests were utilized identify statistically meaningful differences between school districts with and without wind turbines. In addition, a longitudinal temporal analysis was undertaken for selected locations to further illustrate the impact of the wind farms on the region.
ResultsThe spatial patterns of local school revenue and related variables have been analyzed and compared to available socioeconomic and demographic information. Spatial and multivariate analysis has been undertaken to highlight differences in characteristics of public school districts with and without wind turbines. Results show significant differences in revenue from local and county sources between school districts with and without wind farms. However, school districts with wind farms did not have higher per-student expenditures or lower student-teacher ratios than surrounding districts. The significant change in percentage of revenue from local and county sources illustrates the relative importance of the industry, especially during challenging economic times and particularly in those areas with fewer other revenue sources.
ConclusionsThough school districts with wind farms did not differ from surrounding districts in terms of per-student expenditures or student-teacher ratios, the significant difference in revenue from local and county sources suggests these districts may be less susceptible to changes in funding from state and federal sources.
[en] Quantification of long-term wind-speed variability is a critical component in wind resource assessment, and effective wind-farm operations require proper assessment of this variability. Yet, wind-speed variations differ across averaging temporal scales because hourly mean wind speeds fluctuate more than yearly averages. In this study, we quantify the influence of averaging timescale to the resultant variability. We assess three spread metrics (standard deviation, coefficient of variation, and robust coefficient of variation) and two distribution measures (skewness and kurtosis) based on 38 years of wind speeds from the National Aeronautics and Space Administration's MERRA-2 reanalysis data set over the contiguous United States. The spatial distributions of wind-speed variability differ with metrics and timescales: wind speeds of fine temporal resolution generate strong variabilities that dilute spatial contrasts; small sample size becomes a constraint in calculating interannual variabilities via annual means and leads to inaccurate results. Overall, we find that metrics based on monthly data portray the largest spatial differences of wind-speed variability. Although standard deviation yields consistent geographical projections, none of the wind-speed data of any time frame are perfectly Gaussian. Furthermore, the robust coefficient of variation, a statistically robust and resistant approach, appears to be the ideal metric for quantifying wind-speed variabilities based on monthly mean data.
[en] A novel method for sizing power cables that connect offshore wind parks to the grid is presented. The followed methodology consists of two different and independent tasks: The stochastic wind power generation of the wind park is estimated based on historical data and, then, the cooling effect of high wind speeds on the temperature of the cable's aerial part is evaluated. In contrast to the IEC60287 standard, the effect of the variable heat transfer coefficient (h) caused by the variable wind speeds, is taken into account following a Finite Element Method approach which leads to a different thermal behavior than the expected one. Higher h values are caused by high wind speeds increasing, therefore, the current carrying capacity of the cable. The results of this study lead to a more efficient way of sizing power cables, avoiding power curtailment in periods with particularly high wind speeds, leading to a more cost efficient cable design. - Highlights: • Thermal behavior of a submarine cable connecting an offshore wind farm to the coast. • Estimation of the variable load due to wind's variability. • Estimation of the variable heat transfer coefficient. • The effect of the wind speed on the cable's temperature.
[en] The amount of wind power that allow an electric network without losing his stability as known as wind power limit. The wind power limit fundamentally depends on the wind turbine technology and the weakness level of the system. To know the system behaviors in dynamic performance having into account the worst disturbance is a very important matter, a short circuit in one of the most power transference line or the loss of a large generation unit was a large disturbance that can affect system stability. The wind power limit may change with the nature of the disturbance. To know the wind power limit considering this conditions allow use the wind at maximum level. In the present paper the behavior of fixed speed wind turbine for different fault types is analyzed, at those conditions, the wind power is increasing until the system become voltage unstable. For the analysis the IEEE 14 Bus Test Case is used. The Power System Analysis Toolbox (PSAT) package is used for the simulation. (author)
[en] In this study, the results of the analysis made about the costs of production of the kW h of wind energy that can be obtained in Cuba are shown. For the realization of the same one the data of wind of six meteorological stations are processed, selecting for the study the stations with the maximum value of annual mean wind speed. A technical assessment has been made of electricity generation from four wind turbines having capacity of (800 kW, 900 kW, 2000 kW and 2300 kW). The yearly energy output for the four different turbines were calculated for the station with the maximum value of annual mean wind speed. It is determined the cost of production of the kW h of wind energy generated with the different machines, taking 1400 dollars per kW installed like inversion cost. (author)
[en] The Republic of Kazakhstan in terms of geography is in a wind zone of the northern hemisphere, and large parts of Kazakhstan there are enough strong air currents, especially the northeast, southwest directions. In some areas of Kazakhstan annual average wind speed is greater than 6 m/s, making these areas attractive for wind power development. In times of greatest need for heat and power generation of wind turbines can be damaged due to wet snow drifts, followed by a sharp decrease in air temperature and the formation of heavy ice on them. One possible way to protect the outer surface of the operating wind turbines from sticking of wet snow is heated by warm air flowing through the internal channels of the device. Thermal protection is a more radical way. This paper discusses the method of calculating the flow of heat through the wall of the air of the real device. Using this methodology, complete consumption were determined amount of heat to the walls of a specific channel. Key words: wind turbine, Reynolds number, total amount of heat, warm air, wind speed, blade