Cargando…
Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator
Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream G...
Autores principales: | Ghefiri, Khaoula, Bouallègue, Soufiene, Garrido, Izaskun, Garrido, Aitor J., Haggège, Joseph |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982424/ https://www.ncbi.nlm.nih.gov/pubmed/29695127 http://dx.doi.org/10.3390/s18051317 |
Ejemplares similares
-
Artificial Neural Networks in MPPT Algorithms for Optimization of Photovoltaic Power Systems: A Review
por: Villegas-Mier, César G., et al.
Publicado: (2021) -
Current Sensorless Based on PI MPPT Algorithms
por: de Brito, Moacyr A. G., et al.
Publicado: (2023) -
Tidal stream to mainstream: mechanical testing of composite tidal stream blades to de-risk operational design life
por: Glennon, Conor, et al.
Publicado: (2022) -
Recursive bit assignment with neural reference adaptive step (RNA) MPPT algorithm for photovoltaic system
por: Hegazy, Eman, et al.
Publicado: (2023) -
Cortical markers of auditory stream segregation revealed for streaming based on tonotopy but not pitch
por: Ruggles, Dorea R., et al.
Publicado: (2018)