A new method for prediction of power coefficient and wake length of a horizontal axis wind turbine based on energy analysis

Abstract

Power coefficient and wake length are important indexes for wind farm design and operational control. Accurate estimation of this coefficient is of great significance for the design of wind energy conversion system. In the present study, new methods for estimating rotor power coefficient (Cp) and wake length (WL) of wind turbine from an energy-based perspective are proposed, and the corresponding prediction models are established. Large eddy simulation (LES) coupled with the Actuator Line Method (ALM) are used to simulate the flow field around the wind turbine, and then transient snapshot Proper Orthogonal Decomposition (POD) method is adopted to analyze the energy contained in each plane of the velocity field. Results show that the new model for power coefficient Cp prediction is effective and the maximum error between the estimated value and that obtained with the conventional method is 1.7%. Meanwhile, the wake lengths predicted with the new model are all about 28.5D for the studied tip speed ratios, and the velocity contours perpendicular to the center of wind turbine verify the good accuracy of the model. The POD analysis results also show that the first-order POD mode characterizing the large-scale turbulence structures maintains more than 99.5% energy of the inflow plane, and offers primarily the energy extracted by the wind turbine. This method can be used in the conditions of the transient velocity field easily obtained, and will rich the method of rotor power coefficient and wake length estimation.