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

页码：611 / 627

页数：17

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