Metodología de diagnóstico de fallos para sistemas fotovoltaicos de conexión a red
The aim of the present research work is the design of a methodology of fault diagnosis as a contribution to the improvement of indicators about efficiency, maintenance and availability of Photovoltaic Systems of Network Connection (PVSNC). The network connection inverter and the mathematical model o...
- Autores:
-
Núñez Alvarez, José Ricardo
Benítez P., Israel F
Proenza Y., Roger
Vázquez S., Luis
Díaz M., David
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5425
- Acceso en línea:
- https://hdl.handle.net/11323/5425
https://repositorio.cuc.edu.co/
- Palabra clave:
- Detección
Aislamiento
Diagnóstico
Identificación
Estimación y acomodación de fallos
Sistemas fotovoltaicos
Monitorización y supervisión
Detection
Isolation
Diagnosis
Identification
Estimation and accommodation of faults
Photovoltaic systems
Monitoring and supervision
- Rights
- openAccess
- License
- CC0 1.0 Universal
Summary: | The aim of the present research work is the design of a methodology of fault diagnosis as a contribution to the improvement of indicators about efficiency, maintenance and availability of Photovoltaic Systems of Network Connection (PVSNC). The network connection inverter and the mathematical model of the Photovoltaic Generator were firstly analyzed. Afterwards, the existing operational losses of the Photovoltaic Generator were quantified, and the mathematical model was adapted to the real conditions of the System through a polynomial adjustment. A real network connection system of nominal power 7.5 kWp installed at the Research Center of Solar Energy, in the province of Santiago de Cuba, was used to assess the proposed methodology. The results obtained were validated to show that the proposed design successfully supervises the PVSNC.100% of the simulated faults were detected and identified with the designed methodology, whose usefulness was additionally shown when having a maximum rate of 0.22% of false alarm in all the tests done. |
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