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Global Maximum Power Point Tracking of PV Arrays Under Partial Shading Conditions Using Improved PSO and PID Algorithm

机译:使用改进的PSO和PID算法,局部阴影条件下PV阵列的全局最大功率点跟踪

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Under the condition of partial shading, the output characteristic curve of the PV system will show a global maximum power peak(GMPP) and multiple local maximum power peaks(LMPP). Since the traditional method can only track GMPP, the traditional method will not be suitable for partial occlusion. Under the dynamic partial shadowing conditions (PSCs), using traditional methods to track dynamic GMPP will become more difficult. This paper proposes a compound control algorithm that combines improved particle swarm optimization (PSO) algorithm with PID algorithm. Based on the traditional PSO, this paper uses adaptive inertia weight to make the algorithm jump out of the LMPP and search for the GMPP quickly and accurately. Meanwhile, PID controller is used to reduce system overshoot and make the system more stable. Compared with the traditional PSO algorithm, the proposed method has better tracking effect under static and dynamic PSCs.
机译:在部分着色的条件下,PV系统的输出特性曲线将显示全局最大功率峰值(GMPP)和多个局部最大功率峰值(LMPP)。由于传统方法只能跟踪GMPP,传统方法不适合部分闭塞。在动态部分阴影条件(PSCS)下,使用传统方法跟踪动态GMPP将变得更加困难。本文提出了一种复合控制算法,将改进的粒子群优化(PSO)算法与PID算法结合起来。基于传统的PSO,本文采用自适应惯性重量使算法跳出LMPP并快速准确地搜索GMPP。同时,PID控制器用于减少系统过冲并使系统更稳定。与传统的PSO算法相比,该方法在静态和动态PSC下具有更好的跟踪效果。

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