“Redes neuronales artificiales aplicada al estudio de perfiles de carga eléctrica en alimentadores primarios de una arquitectura de distribución”
The forecast of electrical demand is an important task in the management of electrical energy, since it allows forecasting the amount of energy that will be required in the near future. This is essential to plan the production and distribution of electrical energy, and to ensure that users' dem...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | Ecuador |
| Institución: | Universidad Técnica de Cotopaxi |
| Repositorio: | Repositorio Universidad Técnica de Cotopaxi |
| Idioma: | español |
| OAI Identifier: | oai:oai:repositorio.utc.edu.ec:27000:27000/10338 |
| Acceso en línea: | http://repositorio.utc.edu.ec/handle/27000/10338 |
| Access Level: | acceso abierto |
| Palabra clave: | REDES NEURONALES ARTIFICIALES RED DE DISTRIBUCIÓN ELÉCTRICA PERFIL DE CARGA ELÉCTRICA ALIMENTADOR PRIMARIO ELECTRICIDAD |
| Sumario: | The forecast of electrical demand is an important task in the management of electrical energy, since it allows forecasting the amount of energy that will be required in the near future. This is essential to plan the production and distribution of electrical energy, and to ensure that users' demand for energy is met. In this work, the use of artificial intelligence through the use of artificial neural networks was proposed for the development of a prediction model focused on the study of load profiles in electric power networks, using the Python software. |
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