A methodology to reveal terrain effects from wind farm SCADA data using a wind signature concept

Terrain features can deviate wind, causing heterogeneity in wind power distribution that varies with oncoming wind direction. An opportunity to review a wind farm layout, and improve its performance, arises with the need to replace end-of-life turbines. A methodology that adds value to wind data recorded over time by a supervisory control and data acquisition (SCADA) system is proposed. Time series portions, i.e., “time bands”, with steady wind are identified and validated to compute a proposed index, SB, that quantifies the significance of the directional distribution of these “time bands” number. SB polar plots bring out terrain effects. Additionally, a wind signature concept is introduced, which is a convenient way of graphically displaying, over the topographic map of the wind farm, wind speed, direction, and turbulence at the location of a given turbine, providing an expeditious assessment of the wind pattern at a turbine-level scale. The proposed methodology is applied to the case study of four turbines in complex terrain in northern Portugal, revealing some effects of terrain features for various directions of oncoming wind.