GWO Controlled SEPIC Converter for Maximum Power Point Tracking of Solar Panel

Ghozi Alif Kirana, Firilia Filiana, Happy Aprillia
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Abstract

The utilization of solar power using photovoltaic (PV) modules is highly disrupted by weather changes that affect irradiation exposure to the modules. This condition later reduces the amount of harvested power and financial benefit of the PV system. Thus, maximum power point tracking (MPPT) is researched to increase the performance of PV systems. The proposed MPPT consists of a Single-Ended Primary-Inductor Converter (SEPIC) converter and Grey Wolf Optimizer (GWO) algorithm. SEPIC converter is used to provide lower ripple-power output while GWO is used to optimized the duty cycle of the SEPIC converter. The performance of the proposed method is compared to the Particle Swarm Optimization algorithm. To yield optimal power, the proposed method is proven to have optimal efficiency of 95.21 % with a standard deviation of 0.182 after 50 iterations.
用于太阳能电池板最大功率跟踪的GWO控制SEPIC变换器
使用光伏(PV)组件的太阳能的利用受到天气变化的高度干扰,天气变化会影响组件的辐照暴露。这种情况后来减少了收获的电力和光伏系统的经济效益。因此,研究最大功率点跟踪(MPPT)以提高光伏系统的性能。所提出的MPPT由一个单端初级电感转换器(SEPIC)和灰狼优化器(GWO)算法组成。SEPIC变换器用于提供较低的纹波功率输出,GWO用于优化SEPIC变换器的占空比。将该方法的性能与粒子群算法进行了比较。为了获得最优功率,经过50次迭代,该方法的最优效率为95.21%,标准差为0.182。
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