TY - GEN
T1 - Forecasting the Behavior of Electric Power Supply at Yucatan, Mexico, Using a Recurrent Neural Network
AU - Ancona-Osalde, R. A.
AU - Orozco-del-Castillo, M. G.
AU - Hernández-Gómez, J. J.
AU - Moreno-Sabido, M. R.
AU - López-Puerto, K.
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The forecast of electric power generation and supply with respect to an expected demand is a matter of national strategy for countries around the world as well as of vital importance for the assurance and viability of current societies. In the state of Yucatan, Mexico, power generation authorities often experience overproduction due to estimations that are done based on historical data in an statistical manner. In this work, we propose the implementation of a long short-term memory recurrent neural network to predict the consumption of electrical power in the aforementioned state. The main outcome shows that this approach implies a reduction in the error of the estimations of 39.53% provided by the neural network forecast with respect to previous estimations by local power generation experts.
AB - The forecast of electric power generation and supply with respect to an expected demand is a matter of national strategy for countries around the world as well as of vital importance for the assurance and viability of current societies. In the state of Yucatan, Mexico, power generation authorities often experience overproduction due to estimations that are done based on historical data in an statistical manner. In this work, we propose the implementation of a long short-term memory recurrent neural network to predict the consumption of electrical power in the aforementioned state. The main outcome shows that this approach implies a reduction in the error of the estimations of 39.53% provided by the neural network forecast with respect to previous estimations by local power generation experts.
KW - ANN
KW - Artificial neural networks
KW - Electric power supply forecasting
KW - Mexico
KW - México
KW - RNN
KW - Recurrent neural networks
KW - Yucatan
KW - Yucatán
UR - http://www.scopus.com/inward/record.url?scp=85119865755&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-89586-0_10
DO - 10.1007/978-3-030-89586-0_10
M3 - Contribución a la conferencia
AN - SCOPUS:85119865755
SN - 9783030895853
T3 - Communications in Computer and Information Science
SP - 127
EP - 137
BT - Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings
A2 - Mata-Rivera, Miguel Félix
A2 - Zagal-Flores, Roberto
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th International Congress on Telematics and Computing, WITCOM 2021
Y2 - 8 November 2021 through 12 November 2021
ER -