Sistema inteligente para la detección de fallas en sistemas fotovoltaicos
Currently, the number of photovoltaic systems has increased rapidly worldwide, however this broad development has not been supported by improvements in the field of photovoltaic monitoring, which is why this type of systems is still subject to the possibility of failures during its operation. The tr...
- Autores:
-
Trujillo Zucchini, Gabriel De Jesus
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad del Norte
- Repositorio:
- Repositorio Uninorte
- Idioma:
- spa
- OAI Identifier:
- oai:manglar.uninorte.edu.co:10584/8000
- Acceso en línea:
- http://hdl.handle.net/10584/8000
- Palabra clave:
- Lógica Difusa, Sombreado, Cortocircuito, Sobrecarga, Funciones de Membresía
Fuzzy Logic, Shading, Short Circuit, Overload, Membership Functions
- Rights
- License
- Universidad del Norte
| Summary: | Currently, the number of photovoltaic systems has increased rapidly worldwide, however this broad development has not been supported by improvements in the field of photovoltaic monitoring, which is why this type of systems is still subject to the possibility of failures during its operation. The traditional techniques for the detection of faults in this type of systems are not working properly due to the working conditions when there is low irradiation and the power mppt. Due to the fact that within these photovoltaic systems this type of inconveniences is being presented, the need to investigate new methods that improve the performance, efficiency, reliability and increase the life time of the equipment is relevant. Given this problem, the development of an intelligent system using the fuzzy logic method is considered, there will not be a hardware prototype and the model will only be able to detect shading, short circuit and overload faults within the photovoltaic system. The proposed design is based on a diffuse Mamdani type system, it receives four input variables: irradiation, module temperature, current and voltage. The climate variables were read from the Weather Underground database and the calculation of the module temperature, current and voltage was carried out using mathematical models. Through a series of proposed rules, the three types of faults mentioned above are detected and diagnosed. Through a graphical interface, the behavior of the system is recorded around the clock and the behavior of the I-V and P-V curves is analyzed under normal conditions and during a fault in the operation. The results obtained show that the intelligent system is able to identify 90% accuracy between the types of failure and normal operating situations. |
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