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A novel maximum power point tracking method for PV systems using artificial neural network
| Content Provider | Semantic Scholar |
|---|---|
| Author | Noroozian, Reza Barzideh, Faraz Jalilvand, Ali |
| Copyright Year | 2013 |
| Abstract | This paper presents a novel maximum power point tracking method of a stand-alone photovoltaic system using artificial neural network. The proposed method estimates the maximum power of a solar module in different conditions. The main advantage of the proposed methodology, comparing to conventional methods is more accuracy. Also compared to other neural network based methods this model can be trained in less iteration and shows more stability based on different initial training points. Simulation and experimental results show that the model reaches a high fitness. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.researchgate.net/profile/Dr_Abolfazl_Jalilvand/publication/257526163_A_Novel_Maximum_Power_Point_Tracking_Method_for_PV_Systems_Using_Artificial_Neural_Network/links/0c9605304db46451c6000000.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
