Maximum Power Point Tracking of PV system Based Cuckoo Search Algorithm; review and comparison

被引：80

作者：

Mosaad, Mohamed I. ^{[1
]}

el-Raouf, M. Osama Abed ^{[2
]}

Al-Ahmar, Mahmoud A. ^{[3
]}

Banakher, Fahd A. ^{[1
]}

机构：

[1] Yanbu Ind Coll, Yanbu Al Sinaiyah 46452, Yanbu, Saudi Arabia

[2] Housing & Bldg Natl Res, Bldg Phys & Environm Res Inst, Cairo, Egypt

[3] Benha Univ, Fac Engn, Shoubra, Egypt

来源：

EMERGING AND RENEWABLE ENERGY: GENERATION AND AUTOMATION | 2019年 / 162卷

关键词：

PV; cuckoo search; MPPT; le'vy flight; PSO; DC-DC converter; PID controller; ADAPTIVE-CONTROL; PID CONTROLLER; SOLAR PV; PERFORMANCE; GENERATION; MPPT;

D O I：

10.1016/j.egypro.2019.04.013

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The article presents a review about Maximum Power Point Tracking (MPPT) of PV system based cuckoo search algorithm. Cuckoo search (CS) provides several advantages such as the process of tuning parameters is few with high efficiency beside fast convergence. Cuckoo search uses a random walk according to le'vy flight in searching process. MPPT by using cuckoo search is compared to other two methods, neural network method which needs training for data and the incremental conductance method. DC-DC converter is utilized with direct duty cycle control of PWM based PID controller. The PID controller parameters are tuned using particle swarm optimization (PSO) and compared with classical methods. The results show that CS can track MPP under different operating conditions with lower power losses compared to the other two methods. (C) 2019 The Authors. Published by Elsevier Ltd

引用

页码：117 / 126

页数：10

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