Abstract
Power curves are used to model power generation of wind turbines, which in turn is used for wind energy assessment and forecasting total wind farm power output of operating wind farms. Power curves are based on ideal uniform inflow conditions, however, as wind turbines are installed in regions of heterogeneous and complex terrain, the effect of non-ideal operating conditions resulting in variability of the inflow must be considered. We propose an approach to include turbulence, yaw error, air density, wind veer and shear in the prediction of turbine power by using high resolution wind measurements. In this study, two modified power curves using standard ten-minute wind speed and high resolution one-second data along with a derived power surface were tested and compared to the standard operating curve for a 2.5 MW horizontal axis wind turbine. Data from supervisory control and data acquisition (SCADA) system along with wind speed measurements from a nacelle-mounted sonic anemometer and wind speed measurements from a nearby meteorological tower are used in the models. The results show that all of the proposed models perform better than the standard power curve while the power surface results in the most accurate power prediction.
Highlights
As renewable energy becomes more prevalent, its integration into the power grid and the prediction of its energy contribution to the grid becomes more important
The developed models incorporate the effects of turbulence, density, wind shear, and wind veer into the standard power curves in order to achieve better accuracy
Quality checks were performed on the data from the met tower and supervisory control and data acquisition (SCADA) and only periods with acceptable quality based on strict criteria were used in the models
Summary
As renewable energy becomes more prevalent, its integration into the power grid and the prediction of its energy contribution to the grid becomes more important. There are a number of other atmospheric variables whose effect on power generation needs to be accounted for, including turbulence, density variation, wind shear and wind veer [2]. A physics-based approach in which the effect of atmospheric variables are added to standard power curves. The applicability of equivalent wind speed extends beyond power curves. We expand on the existing power curve models and incorporate yaw error and turbulence using an equivalent wind speed, an approach which was introduced by Wagner et al [3]. The equivalent wind speed combines the effect of turbulence and yaw error and represents them as a single variable at each height, which is integrated vertically. This rotor equivalent wind speed is used in a modified power curve the same way as hub height wind speed may be used in standard power curves
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