DocumentCode :
2055543
Title :
The new maximum power point tracking algorithm using ANN-based solar PV systems
Author :
Lee, Hong Hee ; Phuong, Le Minh ; Dzung, Phan Quoc ; Vu, Nguyen Truong Dan ; Khoa, Le Dinh
Author_Institution :
Sch. of Electr. Eng., Univ. of Ulsan, Ulsan, South Korea
fYear :
2010
fDate :
21-24 Nov. 2010
Firstpage :
2179
Lastpage :
2184
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 Card DSPACE 1104.
Keywords :
maximum power point trackers; neural nets; photovoltaic power systems; power engineering computing; power grids; ANN-based solar PV array system; Card DSPACE 1104; IncCond method; MPPT algorithm; Matlab-Simulink simulation; artificial neural network; grid connected photovoltaic system; incremental conductance method; maximum power point tracking algorithm; artificial neural network (ANN); incremental conductance (IncCond); maximum power point tracking (MPPT); photovoltaic (PV);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2010 - 2010 IEEE Region 10 Conference
Conference_Location :
Fukuoka
ISSN :
pending
Print_ISBN :
978-1-4244-6889-8
Type :
conf
DOI :
10.1109/TENCON.2010.5686721
Filename :
5686721
Link To Document :
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