An Intelligent MPPT Approach based on Neural-Network Voltage Estimator and Fuzzy Controller, Applied to a Stand-alone PV System

被引：0

作者：

Bendib, B. ^{[1
,2
]}

Krim, F. ^{[2
]}

Belmili, H. ^{[1
]}

Almi, M. F. ^{[1
]}

Bolouma, S. ^{[1
]}

机构：

[1] EPST CDER, UDES, Bou Ismail 42415, W Tipaza, Algeria

[2] Univ Setif 1, Power Elect & Ind control Iab LEPCI, Setif, Algeria

来源：

2014 IEEE 23RD INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2014年

关键词：

PV system; DC-DC converter MPPT; artificial neural network (ANN); fuzzy logic controller (FLC); IncCond; POWER POINT TRACKING; PHOTOVOLTAIC ARRAYS; LOGIC CONTROLLER; MAXIMUM; ALGORITHM; SIMULATION;

D O I：

暂无

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 paper presents an intelligent maximum power point tracking (MPPT) method for a stand-alone photovoltaic (PV) system using artificial neural networks (ANN) modelling and a fuzzy logic controller (FLC). The ANN is trained for various conditions of solar irradiance and temperature to estimate the MPP voltage. This voltage is then used by the FLC as a reference voltage to generate the appropriate control signal for the DC-DC converter. The proposed technique is implemented in Matlab/Simulink and compared with the conventional method of incremental conductance (IncCond). Simulation results show a good performance of the ANN based fuzzy MPPT controller.

引用

页码：404 / 409

页数：6

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