Comparative Investigation of MPPT Controller For Grid Connected Photovoltaic System

被引：2

作者：

Sarhan, Amr A. ^{[1
]}

Kamel, Mohamed A. ^{[2
]}

Hafez, Ahmed T. ^{[1
]}

Givigi, Sidney ^{[3
]}

机构：

[1] Mil Tech Coll, Dept Elect Engn, Cairo 11766, Egypt

[2] Mil Tech Coll, Dept Mech Engn, Cairo 11766, Egypt

[3] Queens Univ, Sch Comp, Kingston, ON, Canada

来源：

2020 14TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON2020) | 2020年

关键词：

ANFIS; PSO; SMC; MPPT; POWER-POINT-TRACKING; SLIDING MODE CONTROL; CONTROL DESIGN; FUZZY-LOGIC; ALGORITHM;

D O I：

10.1109/SysCon47679.2020.9460985

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recently, global warming is attracting the attention of the whole world. One of the main reasons is the increase of CO2 causing high pollution levels due to the burning of fossil fuels. The promising performance of green energy encourages the use of solar energy instead of ordinary sources. Photovoltaic (PV) energy is a free energy that requires to reach its Maximum Power Point Tracking (MPPT) to guarantee sufficient power for a long Energy Payback Time (EPBT). In this paper, we introduce several control approaches- Adaptive Neuro Fuzzy Inference Systems (ANFIS), Particle Swarm Optimization (PSO) and Sliding Mode Control (SMC)- aiming at the maximum PV system output power with minimum EPBT. To prove the success of these, the results are compared with the results of PV system using Hill Climbing (HC) method, Incremental Conductance (INC) method and Perturb Observation (P & O) technique.

引用

页数：7

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