@inproceedings{e255a4d4742e4b5a8f434176d8c480b2,
title = "Long-short term memory applied to energy management systems in microgrids",
abstract = "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.",
keywords = "Energy Management System, Interior Point Method, Long-Short Term Memory, Microgrid",
author = "David Uribe and Victor Ramirez and Luis Polanco and Victor Cuervo and Luis Marin",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023 ; Conference date: 25-11-2023 Through 26-11-2023",
year = "2023",
doi = "10.1109/ISCMI59957.2023.10458611",
language = "English",
series = "2023 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "222--226",
booktitle = "2023 10th International Conference on Soft Computing and Machine Intelligence, ISCMI 2023",
address = "United States",
}