Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies

Marco A. Toledo, Carlos Alvarez-Bel, Flavio A. Quizhpi, Miguel A. Figueroa, Jordy A. Pintado

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

Resumen

Research develops a planning model to carry out the prognosis of energy purchase that the distribution and marketing company is done through the use of energy demand information and with the penetration of renewable generation in the short and medium-term using a computational model of artificial neuronal networks in the MATLAB computational tool, the results obtained show the performance of this model with errors less than 1% both in training and prediction. For the respective testing of this algorithm, the historical data of 5 years of the 'Electric Regional Enterprise Sur Centro C. A.' was taken of the city of Cuenca in Ecuador.

Idioma originalInglés
Título de la publicación alojada2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665434270
DOI
EstadoPublicada - 2021
Evento23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 - Virtual, Ixtapa, México
Duración: 10 nov. 202112 nov. 2021

Serie de la publicación

Nombre2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021

Conferencia

Conferencia23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
País/TerritorioMéxico
CiudadVirtual, Ixtapa
Período10/11/2112/11/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE.

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