Online estimation of the power coefficient versus tip-speed ratio curve of wind turbines

Wind turbines are one of the main sources of renewable energy worldwide. Although large wind turbines in the MW range are popular, small wind turbines of several kW can also have a valuable contribution since they can be installed in a more decentralized manner. However, the energy yield of these small wind turbines still needs improvement. The performance of the Maximum Power Point Tracker (MPPT) has a crucial impact on the energy yield. In order to design and set-up the MPPT, knowledge of the C_p(λ) curve of the turbine blades has an important added value. However, this curve is often not known as it requires a sufficiently large wind tunnel or complex computational fluid dynamics calculations. In this paper, a new alternative method is presented to estimate the C_p(λ) curve by measuring the wind speed, generator voltage and current. This method can be applied on any turbine, small or large, during normal operation and does not require an intervention in the turbine itself, e.g., for placement of additional sensors. The C_p(λ) estimation method is implemented on a lab-scale wind turbine emulator to obtain experimental validation.