| Autor: |
Rekioua Djamila, Bentata Khadidja, Zerglaine Abdelaziz, Mebarki Nasser Eddine, Mohammedi Ahmed, Oubelaid Adel |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Advances in Green Energies and Materials Technology ISBN: 9789811603778 |
| Popis: |
Due to the nonlinear electrical characteristics of photovoltaic (PV) generators, the performance and efficiency of such systems can be improved by forcing it to operate at its maximum power point (MPP). In this article, we have proposed an adaptive strategy to achieve maximum power point tracking (MPPT) using an artificial neural network (ANN) approach. ANN control based on neural network learning database is used to control the boost converter fed by an autonomous photovoltaic generator (PVG). The obtained results show that the ANN-MPPT control provides low oscillations and shows good performances around the maximum power point of the PVG compared to the Classical MPPT algorithms such as perturb and observe (P&O). |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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