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
收藏
页码：404 / 409
页数：6
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