Wind Data Collection and Analyses at Masdar City for Wind Turbine Assessment

Abstract

Wind turbine technology has improved dramatically in the last two decades and their deployment and implementation increased by 20-25% annually. Wind is neither chaotically generated nor is based on random phenomenon. Wind is predictable to greater extend. Current predictive models lack the validation against collected historical data. In this work a 50m meteorological tower was installed at Masdar City for continuous collection of annual wind data records. Data is sampled at 10 minutes sampling rate using Campbell 1000 data logger connected to cup vane anemometry at 5 different heights to estimate the boundary layer profile. Collected and estimated wind energy density was below 120Watt/m 2 suggesting low wind area and undermining the feasibility of wind turbine implementation in the city. Data is analyzed for their first (mean and standard deviation) and second moments (correlation and spectrum) and found to vary considerably in scale and time suggesting simultaneous time and scale analysis. Wavelet analysis is used to study the intermittency of the wind data and quantify their intermittency factor.