TY - GEN
T1 - Long-short term memory applied to energy management systems in microgrids
AU - Uribe, David
AU - Ramirez, Victor
AU - Polanco, Luis
AU - Cuervo, Victor
AU - Marin, Luis
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In this research paper, we implemented a Long-Short Term Memory neural network for climate variable prediction and employed the interior point method to optimize the energy management of a microgrid. Our objective was to reduce the dependence on diesel generators and minimize the associated costs. By prioritizing technological alternatives over exclusive reliance on diesel generators, we achieved a substantial 10% reduction in diesel generator costs in comparison to the energy management-free model.
AB - In this research paper, we implemented a Long-Short Term Memory neural network for climate variable prediction and employed the interior point method to optimize the energy management of a microgrid. Our objective was to reduce the dependence on diesel generators and minimize the associated costs. By prioritizing technological alternatives over exclusive reliance on diesel generators, we achieved a substantial 10% reduction in diesel generator costs in comparison to the energy management-free model.
KW - Energy Management System
KW - Interior Point Method
KW - Long-Short Term Memory
KW - Microgrid
UR - http://www.scopus.com/inward/record.url?scp=85188420238&partnerID=8YFLogxK
U2 - 10.1109/ISCMI59957.2023.10458611
DO - 10.1109/ISCMI59957.2023.10458611
M3 - Conference contribution
AN - SCOPUS:85188420238
T3 - 2023 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023
SP - 222
EP - 226
BT - 2023 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023
Y2 - 25 November 2023 through 26 November 2023
ER -