UIC和PSC下光伏系统的GWO-P&O算法

Muyassar Muyassar, Tarmizi, Yuwaldy Away
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引用次数: 0

摘要

光伏系统的运行可能会经历均匀(UIC)和部分日照(PSC),这取决于其环境。文献中提出了许多MPPT算法,如P&O,以及许多元启发式算法,如PSO和GWO。这些算法只能在特定的环境条件下工作。P&O算法仅适用于UIC,但无法跟踪PSC的最大功率,从而降低了MPPT系统在经历UIC和PSC时的效率。GWO算法可以跟踪PSC处的最大功率,但当日照变为UIC时,功率输出可能会低于最大功率,从而降低MPPT系统的效率。在本文中,提出了另一种方法,通过将GWO的结果实现到P&O算法的输入,随后周期性地重置GWO以搜索新的最大功率点,从而预测任何环境变化。这种新方法被称为GWO-P&O算法。仿真结果表明,在光伏阵列模块经历UIC和PSC的情况下,与GWO或P&O算法相比,GWO-P&O算法产生了更好的效率。使用MATLAB/SIMULINK软件进行仿真。
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A GWO-P&O Algorithm MPPT for PV Systems Under UIC and PSC
The operation of PV systems can experience uniform (UIC) and partial insolation (PSC) that depends on its environment. Many MPPT algorithm has been proposed in literature such as P&O, and many metaheuristics algorithm such as PSO and GWO. Those algorithm only work at a certain environmental condition. The P&O algorithm only work at UIC but fail to track maximum power at PSC hence reducing efficiency of MPPT system when it is experiencing UIC and PSC. The GWO algorithm can track maximum power at PSC but when the change of insolation to UIC can shift power output below maximum power hence reducing efficiency of MPPT system. In this paper another method is proposed by implementing the result of GWO to the input of the P&O algorithm subsequently the GWO is reset periodically to search a new maximum power point to anticipate any environmental changes. This new method is called a GWO-P&O algorithm. Simulation results show that the GWO-P&O algorithm yields better efficiency compared to the GWO or the P&O algorithm in case the modules of PV array experiencing UIC and PSCs. Simulation is done using MATLAB/SIMULINK software.
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