Effect of averaging time windows on wind resource assessment of small wind turbines. Issue 7 (1st March 2022)

• Record Type: Journal Article
• Authors: Goit, Jay Prakash; Taguchi, Masakage; Tatsuno, Junya; Kameda, Takatsugu
• Is Part Of: Wind energy. Volume 25:Issue 7(2022)
• Page Start: 1222
• Page End: 1237
• Publication Date: 2022-03-01
• Subjects: averaging time window -- small wind turbine -- turbine response -- turbulence intensity -- wind resource assessment; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2723
• Languages: English
• ISSNs: 1095-4244

Abstract

Abstract: 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. The current study investigates the effect of averaging time windows on wind resource assessment and power estimation of SWTs. To that end, wind data from a 1‐year measurement campaign is analysed using two short‐term averaging windows of 30 and 60 s and two long‐term averaging windows of 5 and 10 min. Although the average wind speed over the 1‐year period is 1.3 m/s with all four windows, when wind speeds higher than 3 m/s are considered, the average wind speed obtained using a 30‐s averaging window is 8% higher than that obtained using a 10‐min window. Power prediction using the 10 kW SWT shows that the predicted power using a 30‐s window is almost twice as large compared to that estimated using a 10‐min window. Finally, the rotational speed of the SWT obtained with short‐term averaging shows better agreement with that computed by direct modelling of the turbine with the measured wind speed as the input to the model. The study thus shows that the performance of SWTs will be better predicted if short‐term averaging windows are used.