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

doi:10.1109/ROPEC53248.2021.9668147

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

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

1 Cita (Scopus)

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 original	Inglés
Título de la publicación alojada	2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781665434270
DOI	https://doi.org/10.1109/ROPEC53248.2021.9668147
Estado	Publicada - 2021
Evento	23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 - Virtual, Ixtapa, México Duración: 10 nov. 2021 → 12 nov. 2021

Serie de la publicación

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

Conferencia

Conferencia	23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
País/Territorio	México
Ciudad	Virtual, Ixtapa
Período	10/11/21 → 12/11/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE.

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 7: Energía asequible y no contaminante

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10.1109/ROPEC53248.2021.9668147

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Toledo, M. A., Alvarez-Bel, C., Quizhpi, F. A., Figueroa, M. A., & Pintado, J. A. (2021). Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies. En 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 (2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROPEC53248.2021.9668147

Toledo, Marco A. ; Alvarez-Bel, Carlos ; Quizhpi, Flavio A. et al. / Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies. 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021).

@inproceedings{beaf9fdd6349434fbcc4f80314307a44,

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

abstract = "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. ",

keywords = "Artificial Neural Networks, Demand, Forecasting, Planning, Renewable Energy, Short -Medium Term",

author = "Toledo, \{Marco A.\} and Carlos Alvarez-Bel and Quizhpi, \{Flavio A.\} and Figueroa, \{Miguel A.\} and Pintado, \{Jordy A.\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 ; Conference date: 10-11-2021 Through 12-11-2021",

year = "2021",

doi = "10.1109/ROPEC53248.2021.9668147",

language = "English",

series = "2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021",

address = "United States",

}

Toledo, MA, Alvarez-Bel, C, Quizhpi, FA, Figueroa, MA & Pintado, JA 2021, Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies. En 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021. 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021, Institute of Electrical and Electronics Engineers Inc., 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021, Virtual, Ixtapa, México, 10/11/21. https://doi.org/10.1109/ROPEC53248.2021.9668147

Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies. / Toledo, Marco A.; Alvarez-Bel, Carlos; Quizhpi, Flavio A. et al.
2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies

AU - Toledo, Marco A.

AU - Alvarez-Bel, Carlos

AU - Quizhpi, Flavio A.

AU - Figueroa, Miguel A.

AU - Pintado, Jordy A.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Artificial Neural Networks

KW - Demand

KW - Forecasting

KW - Planning

KW - Renewable Energy

KW - Short -Medium Term

UR - https://www.scopus.com/pages/publications/85124942092

U2 - 10.1109/ROPEC53248.2021.9668147

DO - 10.1109/ROPEC53248.2021.9668147

M3 - Conference contribution

AN - SCOPUS:85124942092

T3 - 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021

Y2 - 10 November 2021 through 12 November 2021

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Toledo MA, Alvarez-Bel C, Quizhpi FA, Figueroa MA, Pintado JA. Model for the Forecast of the purchase of energy in a Utility through artificial neural networks with penetration of renewable energies. En 2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021). doi: 10.1109/ROPEC53248.2021.9668147