Energy Output. Outline. Characterizing Wind Variability. Characterizing Wind Variability 3/7/2015. for Wind Power Management

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Transcription:

Energy Output for Wind Power Management Spring 215 Variability in wind Distribution plotting Mean power of the wind Betz' law Power density Power curves The power coefficient Calculator guide The power calculator Annual energy output Outline Characterizing Wind Variability Characterizing Wind Variability Why is wind variability important? Suppose we know that the average annual wind speed is 6.3 m/s We could choose a turbine with the largest power production at 6.3 m/s This approach would have very different results depending on the site s wind variability around 6.3 m/s 1

Characterizing Wind Variability Wind turbine designers use wind variability to optimize turbine designs to minimize energy generation costs and handle mechanical stress Wind farm designers use wind variability to locate wind farms and select wind turbines Investors use wind variability to estimate revenue from electricity generation Characterizing Wind Variability Spatial Variability latitude topography surface roughness Temporal Variability inter-annual annual (seasonal) diurnal short-term Let s look at the long term temporal variability at one location Weibull Distribution Wind variability is typically described using a Weibull distribution Weibull distributions can be asymmetrical Low wind speeds are more common than high wind speeds in many locations Weibull Distribution Weibull distributions can be described by two parameters: is the scale parameter is the shape parameter ;, For k=3.4, the Weibull distribution is similar to the normal distribution For k=1, the Weibull distribution becomes the exponential distribution http://en.wikipedia.org/wiki/weibull_distribution 2

Weibull Distribution PDF Weibull Distribution CDF Median: Mode: Mean: ln 2 1 Γ 1 1 ;, 1 ;, http://en.wikipedia.org/wiki/weibull_distribution where the gamma function is: Γ http://en.wikipedia.org/wiki/weibull_distribution PDF and CDF Weibull Distribution Mean = 7 m/s Median = 6.6 m/s 5% of the time the wind speed is less than 6.6 m/s, 5% of the time the wind speed is greater than 6.6 m/s The median does not equal the mean due to the asymmetry of the pdf E. Hau (26) 3

Weibull Distribution Wind Speed Histogram 9 Mode = 5.5 m/s The mode is the most common wind speed which is located at the peak of the pdf curve The statistical distribution of wind speed varies by location and time scale The Weibull distribution is fit to a specific location using the shape and scale parameters Number of observations 8 7 6 5 4 3 2 1.4 2.83 5.26 7.69 1.12 12.55 14.98 1.615 4.45 6.475 8.95 11.335 13.765 16.195 Wind speed (m/s) Weibull Calculator Power Calculator http://www.wind-data.ch/tools/weibull.php?lng=en http://www.wind-data.ch/tools/powercalc.php?lng=en 4

Betz s Law Betz s Law 1 2 As kinetic energy is extracted from the wind, the wind slows down If all kinetic energy were extracted from the wind, the wind speed would reduce to zero and could not leave the turbine If the wind speed at the turbine was zero, new air could not enter the rotor and no energy could be extracted 1 2 An ideal wind turbine slows down the wind by of its original speed Betz s Law (1919) says that the theoretical maximum kinetic energy that can be converted into mechanical energy using an ideal wind turbine is or approximately 59.3% Commercial wind turbines can only achieve 7-8% of the Betz limit due to losses Power Density Function Power Density Function The y-axis represents power density at each wind speed for a particular site The gray area is the total power available:.5 The blue area is the theoretical power that can be extracted by Betz s Law The red area is the actual power a particular turbine can produce, determined by the power curve This more detailed power density function illustrates: where E=wind turbine system efficiency =rotor efficiency =gearbox efficiency =generator efficiency =power converter efficiency E. Hau (26) 5

Mechanical Power Summary Mechanical Power Summary.4.35 1 2 Rotor power P (W) 8 Power coefficient C p ().3.25.2.15.1.5 2 4 6 8 1 Tip speed ratio where =power produced by rotor =air density =rotor swept area =wind speed =tip speed ratio =power coefficient =rotor radius =rotor speed 6 4 2-2 2 4 6 8 Rotor speed (rad/s) 1 2 4 6 8 1 Wind speed V (m/s) Mechanical Power Summary Actual Power Curve A: B: Insufficient power to overcome friction and initial torque Turbine operates to maximize efficiency P (W) 8 6 C: Fixed rated power operation 4 2-2 2 4 6 8 Rotor speed (rad/s) 1 2 4 6 8 1 Wind speed V (m/s) 1 2 6

Actual Power Curve Validating Power Curves Power curves are constructed using measurements in areas with low turbulence intensity, and with the wind coming directly towards the front of the turbine Local turbulence and complex terrain (e.g., turbines placed on a rugged slope) may mean that wind gusts hit the rotor from varying directions It may therefore be difficult to reproduce the power curve exactly at any given location The Power Coefficient The power coefficient indicates how efficiently a turbine converts wind energy into electricity (turbine efficiency) Efficiency varies with wind speed The Power Coefficient This turbine was designed for the maximum efficiency of 44% at a wind speed of approximately 9 m/s The efficiency at low speeds is not as important because there is not much energy to harvest At wind speeds above the rated speed the turbine wastes excess energy Efficiency matters most in regions of wind speed where the most energy is found 7

The Capacity Factor Here the theoretical max energy output is defined as a turbine running at its maximum rated power for 8766 hours of the year (24 365.25 8766) The capacity factor could vary from to 1% but in practice is usually between 2% to 7% The Capacity Factor Paradox Although a large capacity factor is preferred, it may not always be the most profitable For example, in a very windy location, it may be an advantage to use a large generator for a given rotor diameter This would tend to lower the capacity factor (using less of the capacity of a relatively larger generator), but it may imply a substantially larger annual production Example: suppose a 6 kw turbine produced 1.5 million kwh in a year. The capacity factor is: 15.285 28.5% 24365.256 Comparison Acknowledgement The material included in the presentation comes largely from the Danish Wind Industry Association 8

Weibull and Power Calculators http://www.wind-data.ch/tools/weibull.php?lng=en http://www.wind-data.ch/tools/powercalc.php?lng=en 9