The effect of wind direction shear on turbine performance in a wind farm in central Iowa

Abstract

Abstract. Numerous studies have shown that atmospheric conditions affect wind turbine performance, however, some findings have exposed conflicting results for different locations and diverse analysis methodologies. In this study, we explore how the change in wind direction with height (direction wind shear), a site-differing factor between conflicting studies, affects wind turbine performance. We utilized lidar and turbine data collected from the 2013 Crop Wind Energy eXperiment (CWEX) project between June and September in a wind farm in north-central Iowa. Directional wind shear was found to follow a diurnal cycle and to monotonically decrease with increasing wind speeds. Using different thresholds to distinguish between high- and low-directional wind shear scenarios, we found that larger thresholds evidence statistically-significant effects on turbine power production for lower wind speeds. We further analyzed a threshold of 0.225 deg m−1 and found turbine underperformance in the order of 10 % for wind speed regimes below 8 m s−1. Considering a time period of ramping electricity demand (05:30–09:00 LT) exposed the fact that large direction shear occurs during this time and is undermining turbine performance by more than 10 %. A predominance of clockwise direction shear (wind veering) cases compared to counterclockwise (wind backing) was also observed throughout the campaign. Moreover, large veering was found to have greater detrimental effects on turbine performance compared to small backing values. This study shows that changes in wind direction with height should be considered when analyzing turbine performance, however, future work on segregating speed and direction shear should be pursued to quantify the effects of only one factor on turbine power production.

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

“…The "#$% distribution (Fig. 8e), divided between veering ( "#$% > 0) and backing ( "#$% ), shows a surprising prevalence of backing conditions, in contrast to other observations (Walter et al, 2009;Bodini et al, 2019b;Sanchez Gomez and Lundquist, 2019). Veer occurs 34.7% of the time while backing occurs 64.9% of the time.…”

“…Blade pitch angles greater than 6º were filtered out as well to remove data that could be affected by curtailments. Blade pitch angles were used to filter data in other studies (St. Martin et al, 2016;Sanchez Gomez and Lundquist, 2019). We discarded data with blade pitch angles exceeding 6º for this 1-Hz data set.…”

“…The curve that a yaw-misaligned turbine follows depends on the aeroelastic properties of a given turbine itself (Fleming et al, 2014). Note that although these theoretical power impacts are symmetric, some work (Wagner et al, 2010;Sanchez Gomez and Lundquist, 2019) suggests that veering and backing have nonsymmetric effects. This filter removed 4.1% of the data.…”

“…Although former studies used REWS and similar metrics to explore the impact of shear and atmospheric stability on the prediction of power production from megawatt-scale turbines (Elliott and Cadogan, 1990;Rohatgi and Barbezier, 1999;Pedersen, 2004;Sumner and Masson, 2006;Albers et al, 2007;Van den Berg, 2008;Antoniou et al, 2009;Walter et al, 2009;Belu and Koracin, 2012;Wharton and Lundquist, 2012b;Vanderwende and Lundquist, 2012;Sanchez Gomez and Lundquist, 2019;Vahidzadeh and Markfort, 2019), a more recent study (Sark et al 2019) concludes that turbines in regions with flat terrain do not benefit from using REWS rather than a hub-height wind speed. Here, we explore how different regimes of speed and directional veer across the turbine rotor disk affect power production of a megawatt-scale onshore turbine in a wind farm in the high plains of North America.…”

Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1

“…Here we expand upon and synthesize the work of Lee and Lundquist (2017a) generally flat terrain and a vegetated surface of corn and soybeans and featured an operating wind farm northeast of the city of Ames, Iowa. In the 2013 CWEX campaign, seven surface flux stations, a radiometer, three profiling lidars, and a scanning lidar were deployed within and around this wind farm to explore the interaction of multiple wakes in a range of atmospheric stability conditions (Vanderwende et al, 2015;Bodini et al, 2017;Sanchez Gomez and Lundquist, 2019).…”