Manufacturers
develop power curves for their wind turbines. Customers use these wind turbine
power curves for wind farm planning and estimating nearly total production of
planned plant. When wind farm is installed and connected to the grid, these
power curves are not useful. In literacy, researchers proposed wind turbine
power curve measurement methods to obtain an accurate power curve for turbine
on site. But it is not easy to develop power curves for clusters of wind
turbines. Developing a single power curve for a wind farm slightly simplifies
this problem. Accurate wind farm power curve is a very useful tool for
converting wind speed forecasts to power. Also plant owner can use this tool to
detect anomalous operations. In this study we developed and tested wind farm
power curves by using real site measurements. Two different methods are used to
develop power curves. They are polynomial curve fitting and mean bins method.
Wind speed and power output relation is investigated. A method is proposed to
add effect of air density on power curve. Developed power curve has two inputs.
They are hourly mean wind speed and air density values. This approach uses
variable air density in calculation of wind farm power output. Results of this
study showed that performance of mean bins method is better than polynomial
curve fitting. Also proposed air density effect adding method improves
performances of obtained power curves.
Journal Section | Articles |
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Authors | |
Publication Date | June 30, 2017 |
Published in Issue | Year 2017 |
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