Comparison of Swarm Optimization Methods for MPPT in Partially Shaded Photovoltaic Systems
| Autor: | Marcos Vinicios Gomes dos Reis, Guilherme Cerbatto Schmitt Prym, Elson Yoiti Sako, Hugo Soeiro Moreira, Marcelo Gradella Villalva, João Lucas de Souza Silva |
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| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
Maximum power principle Computer science business.industry 020209 energy 020208 electrical & electronic engineering Photovoltaic system Swarm behaviour Particle swarm optimization 02 engineering and technology Solar energy Maximum power point tracking 0202 electrical engineering electronic engineering information engineering Point (geometry) Electricity business |
| Zdroj: | 2019 International Conference on Smart Energy Systems and Technologies (SEST). |
| DOI: | 10.1109/sest.2019.8849145 |
| Popis: | The use of solar energy for electricity grows mainly due to environmental issues. However, several challenges arise for researchers, such as improving the efficiency of photovoltaic systems in shading situations. In this opportunity, several algorithms attempt to search for the point of maximum power in a photovoltaic system, among them the artificial intelligence algorithms. Thus, this paper investigates the use of artificial intelligence in maximum power tracking techniques for partially shaded systems. A review of different methods is done and performed simulations. As a highlight, the particle swarm optimization was the fastest algorithm and the most accurate was artificial bee colony. Therefore, the tested algorithms obtained good efficiency, being the role of the designer to choose the most suitable for each system. |
| Databáze: | OpenAIRE |
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