Abstract
Predicting the extreme loads in power production for the preliminary-design of large-scale wind turbine blade is both important and time consuming. In this paper, a simplified method, called Particle Swarm Optimization-Extreme Load Prediction Model (PSO-ELPM), is developed to quickly assess the extreme loads. This method considers the extreme loads solution as an optimal problem. The rotor speed, wind speed, pitch angle, yaw angle, and azimuth angle are selected as design variables. The constraint conditions are obtained by considering the influence of the aeroelastic property and control system of the wind turbine. An improved PSO algorithm is applied. A 1.5 MW and a 2.0 MW wind turbine are chosen to validate the method. The results show that the extreme root load errors between PSO-ELPM and FOCUS are less than 10%, while PSO-ELPM needs much less computational cost than FOCUS. The distribution of flapwise bending moments are close to the results of FOCUS. By analyzing the loads, we find that the extreme flapwise bending moment of the blade root in chord coordinate (CMF_ROOT) is largely reduced because of the control system, with the extreme edgewise bending moment of the blade root in chord coordinate (CME_ROOT) almost unchanged. Furthermore, higher rotor speed and smaller pitch angle will generate larger extreme bending moments at the blade root.
Highlights
With the increased utilization of low wind speed, blade lengths are becoming increasingly longer, so as to capture more energy at low wind speed
The results show that the extreme root load errors between PSO-ELPM and FOCUS are less than 10%, while PSO-ELPM needs much less computational cost than FOCUS
We find that the extreme flapwise bending moment of the blade root in chord coordinate (CMF_ROOT) is largely reduced because of the control system, with the extreme edgewise bending moment of the blade root in chord coordinate (CME_ROOT) almost unchanged
Summary
With the increased utilization of low wind speed, blade lengths are becoming increasingly longer, so as to capture more energy at low wind speed. During the design of the blade, the discrete engineering method, has been widely adopted to obtain accurate results This method gives the extreme loads by simulating every load case according to the IEC or GL standard. Many research articles about the design methods regarding blade optimization design select parts of the design load cases (DLCs) to get the extreme load and run all the DLCs to verify the results to reduce the overall computational time [18,19,20,21,22] Even though this process has been used to save time, it takes about 65 h running on a workstation equipped with 40 logical processors [20].
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