基于粒子群优化的风电机组最大功率点跟踪算法

K. Das, M. Buragohain
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引用次数: 6

摘要

由于风速不可预测的性质,确定风力发电机组的最佳转速,以在任何风速下提取最大可用风力是至关重要的。通过控制风力机叶片的俯仰角,可以控制风力机的转速和输出功率。为了在较低风速下获得最大输出功率,并在较高风速下保持稳定的额定输出功率,必须采用适当的方法。本文采用基于粒子群优化(PSO)的最大功率点跟踪(MPPT)算法,在风速小于额定风速时跟踪最大功率,在风速大于额定风速时获得合适的俯仰角来限制输出功率。在MATLAB/Simulink上进行的仿真结果显示了风力发电机输出功率、转子转速、转矩、风机叶片俯仰角和风速在这些时刻的变化情况。
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An Algorithmic Approach for Maximum Power Point Tracking of Wind Turbine using Particle Swarm Optimization
Due to the nature of unpredicted wind speed, determining the optimal speed of wind turbine generator to extract the maximum available wind power at any wind speed is essential. By controlling the pitch angle of the wind turbine blades we can control the rotational speed and the output power. To get the maximum output power under lower wind speed and to maintain the stable rated output power under higher wind speed, the proper method must be used. In this paper, particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm is used to trace the maximum power when wind speed is lower than the rated speed and to get the proper pitch angle to limit the output power when the wind speed is greater than the rated speed. The simulation results performed on MATLAB/Simulink show the variations of the wind turbine generator output power, rotor speed, torque, pitch angle of wind turbine blades and wind velocities at those instants.
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