The new maximum power point tracking algorithm using ANN-based solar PV systems Lee H.H., Phuong L.M., Dzung P.Q., Dan Vu N.T., Khoa L.D. School of Electrical Engineering, University of Ulsan, Ulsan, South Korea; HCMC University of Technology, Ho Chi Minh City, Viet Nam 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. © 2010 IEEE. Author Keywords: Artificial neural network (ANN); Incremental conductance (IncCond); Maximum power point tracking (MPPT); Photovoltaic (PV) Index Keywords: Artificial Neural Network; Combined method; D-space; Feedback voltages; Gridconnected photovoltaic system; Incremental conductance; Incremental conductance (IncCond); Maximum power point; Maximum power point tracking; Maximum Power Point Tracking algorithms; Model method; Photovoltaic (PV); PV arrays; Simulink; Solar PV systems; Algorithms; Energy efficiency; Optical flows; Photovoltaic cells; Photovoltaic effects; Pumps; Solar energy; Solar power generation; Neural networks Year: 2010 Source title: IEEE Region 10 Annual International Conference, Proceedings/TENCON Art. No.: 5686721 Page : 2179-2184 Link: Scorpus Link Correspondence Address: Lee, H. H.; School of Electrical Engineering, University of Ulsan, Ulsan, South Korea; email:
[email protected] Sponsors: IEEE Fukuoka Section;IEEE Region 10 Conference name: 2010 IEEE Region 10 Conference, TENCON 2010 Conference date: 21 November 2010 through 24 November 2010 Conference location: Fukuoka Conference code: 83758 ISBN: 9.78142E+12 CODEN: 85QXA DOI: 10.1109/TENCON.2010.5686721
Language of Original Document: English Abbreviated Source Title: IEEE Region 10 Annual International Conference, Proceedings/TENCON Document Type: Conference Paper Source: Scopus Authors with affiliations: 1. Lee, H.H., School of Electrical Engineering, University of Ulsan, Ulsan, South Korea 2. Phuong, L.M., HCMC University of Technology, Ho Chi Minh City, Viet Nam 3. Dzung, P.Q., HCMC University of Technology, Ho Chi Minh City, Viet Nam 4. Dan Vu, N.T., HCMC University of Technology, Ho Chi Minh City, Viet Nam 5. Khoa, L.D., HCMC University of Technology, Ho Chi Minh City, Viet Nam
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