HYBRID APPROACH TO MAXIMUM POWER POINT TRACKING IN PHOTOELECTRIC SYSTEMS
This paper explores a hybrid approach to maximum power point tracking (MPPT) in photovoltaic systems, focusing on improving the efficiency and stability of the methods. Various MPPT algorithms, such as Perturb and Observe (P&O), Incremental Conductance (INC), and Double Increment (DM), are d...
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| Datum: | 2025 |
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| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | Ukrainian |
| Veröffentlicht: |
Institute of Renewable Energy National Academy of Sciences of Ukraine
2025
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| Online Zugang: | https://ve.org.ua/index.php/journal/article/view/532 |
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| Назва журналу: | Vidnovluvana energetika |
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Vidnovluvana energetika| Zusammenfassung: | This paper explores a hybrid approach to maximum power point tracking (MPPT) in photovoltaic systems, focusing on improving the efficiency and stability of the methods. Various MPPT algorithms, such as Perturb and Observe (P&O), Incremental Conductance (INC), and Double Increment (DM), are discussed, in combination with artificial neural networks (ANN) and particle swarm optimization (PSO) algorithms. The use of real-world data from a solar power plant allowed computer simulations to optimize system parameters. The analysis results demonstrate that each method has its own characteristics, which allows choosing the optimal approach depending on criteria such as performance, stability, and response speed. The conclusions obtained can be useful for designing and tuning PV systems in real-world conditions, especially in variable weather conditions. |
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