DocumentCode
1646574
Title
The new MPPT algorithm using ANN-based PV
Author
Dzung, Phan Quoc ; Khoa, Le Dinh ; Lee, Hong Hee ; Phuong, Le Minh ; Dan Vu, Nguyen Truong
Author_Institution
HCMC Univ. of Technol., Ho Chi Minh City, Vietnam
fYear
2010
Firstpage
402
Lastpage
407
Abstract
In grid connected photovoltaic (PV) systems, maximum power point tracking (MPPT) algorithm plays an important role in optimizing the solar energy efficiency. In this paper, the new artificial neural network (ANN) based MPPT method has been proposed for searching maximum power point (MPP) fast and exactly. For the first time, the combined method is proposed, which is established on the ANN-based PV model method and incremental conductance (IncCond) method. The advantage of ANN-based PV model method is the fast MPP approximation base on the ability of ANN according the parameters of PV array that used. The advantage of IncCond method is the ability to search the exactly MPP based on the feedback voltage and current but don´t care the characteristic on PV array.. The effectiveness of proposed algorithm is validated by simulation using Matlab/ Simulink and experimental results using kit field programmable gate array (FPGA) Virtex II pro of Xilinx.
Keywords
mathematics computing; maximum power point trackers; neural nets; optimisation; photovoltaic power systems; power engineering computing; MPPT algorithm; Matlab-Simulink; PV array; Virtex II pro; artificial neural network; field programmable gate array; incremental conductance; maximum power point tracking; photovoltaic systems; solar energy efficiency; Approximation algorithms; Approximation methods; Arrays; Artificial neural networks; Virtex II pro; artificial neural network (ANN); incremental conductance (IncCond); maximum power point tracking (MPPT); photovoltaic (PV);
fLanguage
English
Publisher
ieee
Conference_Titel
Strategic Technology (IFOST), 2010 International Forum on
Conference_Location
Ulsan
Print_ISBN
978-1-4244-9038-7
Electronic_ISBN
978-1-4244-9036-3
Type
conf
DOI
10.1109/IFOST.2010.5668004
Filename
5668004
Link To Document