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Due to the time-varying wind direction, yaw operation of wind turbines is a common state. Under yaw, the aerodynamic behavior of wind turbines is complicated, and also causes complex energy capture performance. To clarify some vague knowledge, a detailed investigation of yaw effect based on SCADA data is carried out. Firstly, a yaw coefficient definition and its specific calculation method are presented. Furthermore, to analyze the energy capture mechanism, the loss factor of energy capture (power coefficient) is subdivided into aerodynamic loss factor and inertia loss factor, which means both the effects of aerodynamic characteristic and mechanical inertia on energy capture are considered. According to this understanding, power coefficient is expanded as a function of four factors. Then, a single-valued processing method is employed to investigate the relationship between wind speed and output power. Subsequently, relationship between yaw coefficient and output power is investigated. Comparative investigations are carried out by two different methods, that is, least square fitting (LSF) method and kernel density estimation (KDE) method. Also, characteristics of power coefficient and rotor torque under yaw are investigated. Effect laws of yaw coefficient on wind turbine power, power coefficient, and rotor torque are obtained. Finally, the relationship between the internal control mechanism and external output of wind turbines is discussed. [ABSTRACT FROM AUTHOR]

Power coefficient C p is an important parameter for wind turbine design and operational control. Wind speed is the basic calculation parameter of the power coefficient. Since the anemometer is fixed on the nacelle, the measured wind speed is different from the wind speed in front of the wind rotor. Calculation error will produced if the directly measured wind speed is used to calculate the power coefficient. In this paper, a calculation model of the wind speed in front of the wind rotor is presented based on the SCADA data and the aerodynamic theory. Two power coefficient calculation methods are proposed. One is based on the statistical data and the other is based on the real-time data. An actual calculation result for a 2 MW wind turbine shows that the power coefficient is near or greater than 0.593 (the theoretical maximum value) if the directly measured wind speed is used during the maximum power point tracking (MPPT). After wind speed correction, the power coefficient is reduced to 0.397 that is more realistic. When using the real time data, the power coefficient is time-varying even in the region of MPPT, since wind speed is time-varying and the wind rotor rotational speed regulation is delayed due to the wind rotor moment of inertia. [ABSTRACT FROM AUTHOR]