Main content area

Predicting the stochastic aerodynamic loads on blades of two yawed downwind hawts in uncontrolled conditions using a bem algorithm

Elgammi, Moutaz, Sant, Tonio, Alshaikh, Moftah
Renewable energy 2020 v.146 pp. 371-383
aerodynamics, algorithms, blades, kinematics, life cycle costing, models, momentum, physical phenomena, power plants, prediction, rotors, time series analysis, turbulent flow, wind power, wind speed, wind turbines
Accurate predictions of the cycle-to-cycle variations in aerodynamic loads on wind turbine blades are important for estimating the life cycle costs of new wind power plants. Physical modelling of wind turbine systems is usually based on the average values of the aerodynamic parameters in the design process which would eliminate some important physical phenomena associated with the unsteady flows over the rotating blades. This paper presents a new algorithm implemented in a Blade Element Momentum (BEM) model to predict the cycle-to-cycle variations in the aerodynamic loads over multiple rotor rotations (cycles) for yawed rotors operating in natural flow conditions. In this approach, simulation theory developed by the Pacific Northwest Laboratories (PNL) is used to generate input turbulent wind speed time series on the whole rotor disc of two three-bladed downwind horizontal axis wind turbine (NREL Phase II and III) rotors. The unsteady influences of the dynamic stall kinematics and tower shadow are also considered in the current algorithm along with the phenomenon of stall delay. Predictions from the unsteady BEM model are compared to measured results and conclusions are drawn about the ability of the model to accurately simulate blade response to turbulence.