Wind tunnel testing of wind turbines can provide valuable insights into wind turbine performance and provides a simple process to test and improve existing designs. However, the scale of most wind turbines is significantly larger than most existing wind tunnels, thus, the scaling required for testing in a typical wind tunnel presents multiple challenges. When wind turbines are scaled, often only geometric similarity and tip speed ratio matching are employed. Scaling in this manner can result in impractical rotational velocities. For wind tunnel tests that involve Reynolds numbers less than approximately 500,000, Reynolds number matching is necessary. When including Reynolds number matching in the scaling process, keeping rotational velocities realistic becomes even more challenging and preventing impractical freestream velocities becomes difficult. Turbine models of 0.5, 0.4, and 0.3 m diameter, resulting in wind tunnel blockages up to 52.8%, were tested in order to demonstrate scaling using Reynolds number matching and to validate blockage corrections found in the literature. Reynolds numbers over the blades ranged from 20,000 to 150,000 and the tip speed ratio ranged from 3 to 4 at the maximum power point for each wind speed tested.

Wind turbines are often designed using some form of Blade Element Model (BEM). However, different models can produce significantly different results when optimizing the angle of twist for power production. This paper compares the theoretical result of optimizing the angle of twist using Blade Element Theory (BET) and Blade Element Momentum Theory (BEMT) with a tip-loss correction for a 3-bladed, 1.15-m diameter wind turbine with a design tip speed ratio (TSR) of 5. These two theories have been chosen because they are readily available to small-scale designers. Additionally, the turbine was scaled for experimental testing in the Baylor Subsonic Wind Tunnel. Angle of twist distributions differed by as much as 15 degrees near the hub, and the coefficient of power differed as much as 0.08 for the wind speeds tested.

Wind turbines have become a significant part of the world’s energy equation and are expected to become even more important in the years to come. A much-neglected area within wind turbine research is small-scale, fixed-pitch wind turbines with typical power outputs in the 1–10 kW range. This size wind system would be ideal for residential and small commercial applications. The adoption of these systems could reduce dependence on the aging U.S. power grid. It is possible to optimize a small-scale system to operate more efficiently at lower wind speeds, which will make wind generation possible in areas where current wind technology is not feasible. This investigation examines the use of the S818 airfoil, a typical blade root airfoil designed by the National Renewable Energy Laboratory (NREL), as a basis for the design of low Reynolds number (less than 200,000) systems. The literature shows that many of the airfoils proposed for wind turbine applications, including the S818, only have lift and drag data generated by numerical simulations. In previous research at Baylor, 2-D simulations published by NREL have been shown to predict an optimal design angle of attack (which is the angle at which L/D is maximized) up to 2.25° different from actual wind tunnel data. In this study, the lift and drag generated by the S818 airfoil has been measured experimentally at a Reynolds number of approximately 150,000 and compared with NREL simulation data, showing a discrepancy of 1.0°. Using the S818 airfoil, a set of wind turbine blades has been designed to collect wind turbine power data in wind tunnel testing. Design parameters investigated include the effect of design tip speed ratios (TSR) (1, 3, and 7) and the influence of the number of blades (2, 3 and 4) on power generated. At the low Reynolds numbers tested (ranging from 14,000–43,200 along the blade for a design TSR of 3 and a wind speed of 10 mph), the effect of roughness was explored as a performance enhancing technique and was seen to increase power output by delaying separation. Under these low Reynolds number conditions, separation typically occurs on smooth blades. However, the roughness acted as a passive flow control, keeping the flow attached and increasing power output. Preliminary data suggest that as much as a 50% improvement can be realized with the addition of roughness elements for a TSR of 3. Additionally, the increase in power output due to roughness is comparable with the increase in power due to adding another smooth blade.

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A crucial step in evaluating a potential location for a wind turbine, especially small-scale wind turbines, is a proper wind site survey. Eventually the wind site survey is used to calculate the annual energy production (AEP) of the wind turbine and determine if this location will be profitable. Generally, a wind classification of 3 or above is recommended for any wind turbine site, according to the U.S. Department of Energy. Wind Classes of 1–2 are not considered suitable; however, data suggests that a wind site with Class of 2 wind has the potential to be more cost effective than even the least expensive offshore wind and deserves consideration. Wind data usually exists at locations such as local airports; however, the height at which this data are taken is not representative of the heights at which wind turbines will be installed and thus, airport wind data should not be used. Also, with the variability in wind from location to location, the airport data are generally not near the potential site for the wind turbine and thus, are not useful. A local wind site survey generally entails a two year study of the site using a meteorological (MET) tower. Waco, TX is being studied for the application of small-scale wind turbines. Waco is in a Class 2 wind area; however, no proper wind survey had ever been accomplished. Such a study was undertaken using a MET tower of 100 ft with two anemometers at 100 ft, one anemometer at 75 ft and one anemometer at 50 ft. This paper will describe the potential of Class 2 wind as an energy source, the erection of the MET tower, collection of the data and analysis of the data for the potential of locating a small-scale wind turbine at the site. Techniques for analyzing data when two anemometers are present will be discussed. Focus will be on identifying invalid data with an emphasis on correcting this invalid data. The data from two anemometers was then used in a novel way to identify and correct the invalid data found at both the 75 ft and 50 ft elevations. A filtering technique has also been developed to help identify invalid data. Based on the results of the wind survey, it will be shown that it is feasible to purposely design wind turbine blades for Class 2 wind which will perform better than commercially available small-scale wind turbines.