Machine learning applications for photovoltaic system optimization in zero green energy buildings
In this paper, the energy supply of a zero-energy building with 220 square meters is considered using optimized nanocomposite solar panels with respect to maximum efficiency. An optimized hybrid machine learning method plays a key role in presenting solar panel modeling with over 0.99% accuracy. Pre...
- Autores:
-
Liu, Wei
Shen, Yedan
Aungkulanon, Pasura
Ghalandari, Mohammad
Le, Binh Nguyen
Alviz Meza, Anibal
Cardenas Escorcia, Yulineth
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/10379
- Acceso en línea:
- https://hdl.handle.net/11323/10379
https://repositorio.cuc.edu.co/
- Palabra clave:
- Zero energy buildings
Machine learning
Optimization
Photovoltaic systems
Solar panel
Nano-composite material
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)