Aplicación de redes neuronales artificiales en el pronóstico de la demanada eléctrica a corto plazo en el SNI
In this thesis provides a solution to the forecasting of electricity demand in the short SNI using neural network models. With the application of Artificial Neural Networks, the problem of the complexity of traditional prediction models is solved, from factors that actually affect energy consumptio...
| Autor Principal: | Ortíz Parra, David Andrés |
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| Formato: | bachelorThesis |
| Idioma: | spa |
| Publicado: |
2014
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| Materias: | |
| Acceso en línea: |
http://dspace.ups.edu.ec/handle/123456789/6672 |
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| Sumario: |
In this thesis provides a solution to the forecasting of electricity demand in the short SNI using neural network models.
With the application of Artificial Neural Networks, the problem of the complexity of traditional prediction models is solved, from factors that actually affect energy consumption, aspects that were considered in this study are particularly: i) historical data daily electrical demand, ii) climate data; and, iii) weather such as time and date. With the developed solution algorithm analysis is performed in two cases, the first case perform the prediction on the SNI including only the behavior of the application and the second case takes the prediction of electricity demand in the SNI taking into account the previous case and variable climate also included |
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