预测模型与扰动观测算法相结合的MPPT技术

MPPT technology combining prediction model and disturbance observation algorithm

针对外界环境的多变性与随机性,光伏系统输出功率的最大点处总是出现功率震荡现象,增加了实现最大功率跟踪技术的复杂性。为了使光伏系统在外界复杂环境下能够准确跟踪最大功率点,提出了一种预测模型与扰动观测算法相结合的MPPT技术。该算法将扰动观测法与模型预测法相结合,实现了光伏发电系统在外界复杂多变环境情况下的快速跟踪。通过建立系统性能目标函数,评价与估算出未来控制变量的动作,预测出P-U曲线的方向。最后通过Simulink仿真表明了所提方法在外界光照强度发生突变时与单独使用扰动观测法相比较可以同时提高系统的跟踪速度和控制精度。

Due to the variability and randomness behavior of the external environment,the global maximum power point of the PV is always erratic.In order to make the PV system obtain the maximum power output under the complex environment,a MPPT optimization algorithm with the model predictive controller(MPC) based on perturbation observation method was proposed.The algorithm combined the perturbation observation method with the MPC to complete the fast track of the maximum power point of the PV system under complicated environment in the external environment.By establishing the system performance index function,the future behavior of the controlled variables were evaluated and estimated,and the direction of P-U curve was predicted.Finally,the simulink simulation shows that the presented method can improve the tracking speed and control accuracy of the PV system in the light intensity mutations compared with separate using of the traditional perturbation observation method.