Assessment of the energy efficiency estimation methods on induction motors considering real-time monitoring
Different methods have been developed to estimate the energy efficiency of induction motors. The accuracy of these methods vary with the load factor, the unbalanced voltage (UV) and harmonics. The feasibility of these methods for efficiency estimation in real-time were theoretically and experimental...
- Autores:
-
Sousa Santos, Vladimir
Cabello Eras, Juan Jose
Sagastume Gutierrez, Alexis
Cabello Ulloa, Mario Javier
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/1988
- Acceso en línea:
- https://hdl.handle.net/11323/1988
https://repositorio.cuc.edu.co/
- Palabra clave:
- Energy efficiency
Harmonics
Induction motors
Real-time monitoring
Voltage unbalance
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
Summary: | Different methods have been developed to estimate the energy efficiency of induction motors. The accuracy of these methods vary with the load factor, the unbalanced voltage (UV) and harmonics. The feasibility of these methods for efficiency estimation in real-time were theoretically and experimentally assessed during the operation under different operational conditions (i.e. balanced sinusoidal voltage (BSV), harmonics, UV and harmonics with UV). Results show that for load factors over 80%, the air-gap method is applicable under any condition, while the slip method is only applicable under BSV or balanced harmonic voltage. Moreover, for load factors over 40%, the nameplate method is applicable under BSV. Other methods result in errors over 8% and optimization methods are not applicable for real-time monitoring. Electric systems generally operates with some degree of UV and harmonics, while induction motors mostly operate with load factors below 60%, limiting the use of these methods for real-time measurement. |
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