@inproceedings{c6af4fddcc184edfa48e078322234a04,
title = "Performance Evaluation of Deep Recurrent Neural Networks Architectures: Application to PV Power Forecasting",
abstract = "Smart grid systems require an accurate energy prediction from renewable sources to ensure high sustainability and power quality. For PV plants, a precise estimation of the generated PV power is crucial for the reduction of the production/demand unbalance. This essential need comes from the high variability of weather parameters during the PV electricity generation. Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) recurrent neural networks proved their high efficiency in forecasting applications. Thus, this paper proposes a comprehensive evaluation of the LSTM and GRU techniques for PV power estimation in the medium/long horizon. The evaluation is based on a fair assessment of the aforementioned architectures for one week and more than three months (98 days) periods.",
keywords = "Gated Recurrent Unit, GRU, Long Short Term Memory, LSTM, PV Power Forecasting, Smart Grids",
author = "Mohamed Massaoudi and Ines Chihi and Lilia Sidhom and Mohamed Trabelsi and Refaat, {Shady S.} and Oueslati, {Fakhreddine S.}",
note = "Funding Information: This publication was made possible by NPRP grant [NPRP10-0101-170082] from the Qatar National Research Fund (a member of Qatar Foundation) and the co-funding by IBERDROLA QSTP LLC. The statements made herein are solely the responsibility of the authors. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference on Smart Grid and Renewable Energy, SGRE 2019 ; Conference date: 19-11-2019 Through 21-11-2019",
year = "2019",
month = nov,
doi = "10.1109/SGRE46976.2019.9020965",
language = "English",
series = "2nd International Conference on Smart Grid and Renewable Energy, SGRE 2019 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2nd International Conference on Smart Grid and Renewable Energy, SGRE 2019 - Proceedings",
address = "United States",
}