The power curve reflects the electrical output of the wind turbine at different wind speeds, serving as a crucial basis for evaluating its power generation capacity. Measurement and analysis of
In this study, we conducted a measurement campaign for a period of 1 year at a fairly low wind speed site, and we used the measured data to investigate the effect of the averaging window width on wind resource
It is well known that wind energy over the world, especially in China, has grown very fast in the past two decades with a rapidly increasing fraction of electricity generation (Cannon et al.,
Wind turbine output data is for turbine R80721 sited at La Haute Borne, France and recorded every 10 min over the 5-year period from January 2013–December 2017. Fig. 12 provides a more in-depth analysis of the probability of a lower power limit being breached.
The assessment of wind energy requires data collection and the use of analytical methods and techniques to estimate the availability of winds for a wind turbine over its lifetime 7.
After removing some abnormal and unreasonable data such as the missing data by sensor fault, measurement error data and low temporal resolution data, a total of 47,084 wind data are collected. The statistical description of wind speed, its direction and wind power data for 1.8 MW wind turbine are shown in Table 1.
In wind energy, the general practice in assessing the wind resource of a site is to employ a 10-min averaging to measured wind data. However, small wind turbines (SWTs) with rotor diameters <15 m will have a shorter response time scale; thus, an averaging time window of 10 min is too long for accurate wind resource assessments.
Since the measurement was conducted for a 1-year period, the length of the duration curve is 8760 h. However, the total duration for which the wind turbine could have generated significant power is 457 h with 10-min averaged wind speeds and 675 h with 30-s averaged wind speeds.
In the following, the necessary elements for determining the wind conditions for wind energy purposes will be described: The local meteorological elements, the climatological data, the topographic data, the meteorological models, and the tools that finally enable the users to calculate what is described above under the seven items.
