A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

被引：6
|
作者：
Mostafa, Hazem H. [1 ]
Ibrahim, Amr M. [2 ]
Anis, Wagdi R. [3 ]
机构：
[1] Egyptian Chinese Univ, Fac Engn, Energy & Renewable Energy Dept, Cairo 11724, Egypt
[2] Ain Shams Univ, Elect Power & Machines Dept, Fac Engn, Cairo, Egypt
[3] Ain Shams Univ, Fac Engn, Elect & Commun Dept, Cairo, Egypt
来源：
ARCHIVES OF ELECTRICAL ENGINEERING | 2019年 / 68卷 / 03期
关键词：
hybrid optimization; golden sections search; multi-verse optimization algorithm; maximum power point tracking; perturb and observe; photovoltaic (PV); DC-DC CONVERTER; GAIN;
D O I：
10.24425/aee.2019.129345
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.
引用
收藏
页码：611 / 627
页数：17
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