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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kuei-Hsiang Chao Meng-Huei Wang Yu-Hsu Lee |
| Copyright Year | 2011 |
| Description | Author affiliation: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan, R.O.C. (Kuei-Hsiang Chao; Meng-Huei Wang; Yu-Hsu Lee) |
| Abstract | In this paper, a novel incremental conductance (INC) maximum power point tracking (MPPT) method based on extension neural network (ENN) is developed to make full use of photovoltaic (PV) array output power. The proposed method can adjust the step size to track the PV array's maximum power point (MPP) automatically. Compared with the conventional fixed step size INC and variable step size INC methods, the presented approach is able to effectively improve the dynamic response and steady state performance of a PV system simultaneously. A theoretical analysis and the design principle of the proposed method are described in detail. Some simulation results are performed to verify the effectiveness of the proposed ENN MPPT method. |
| Starting Page | 654 |
| Ending Page | 660 |
| File Size | 451993 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781457703058 |
| ISSN | 21601348 |
| e-ISBN | 9781457703089 |
| DOI | 10.1109/ICMLC.2011.6016761 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-10 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Arrays Machine learning Tuning Clustering algorithms Equations Steady-state Training Extension neural network (ENN) Incremental conductance (INC) method Maximum power point tracking (MPPT) Photovoltaic (PV) system |
| Content Type | Text |
| Resource Type | Article |
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