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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

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.

Original language	English
Title of host publication	2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665434270
DOIs	https://doi.org/10.1109/ROPEC53248.2021.9668147
State	Published - 2021
Event	23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 - Virtual, Ixtapa, Mexico Duration: 10 Nov 2021 → 12 Nov 2021

Publication series

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

Conference

Conference	23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
Country/Territory	Mexico
City	Virtual, Ixtapa
Period	10/11/21 → 12/11/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Artificial Neural Networks
Demand
Forecasting
Planning
Renewable Energy
Short -Medium Term

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ROPEC53248.2021.9668147

Cite this

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. In 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).

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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",

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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. in 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, Mexico, 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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M3 - Conference contribution

AN - SCOPUS:85124942092

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

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 10 November 2021 through 12 November 2021

ER -

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. In 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

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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