Powering Electricity Forecasting with Transfer Learning

Firuz Kamalov (), Hana Sulieman (), Sherif Moussa, Jorge Avante Reyes and Murodbek Safaraliev
Additional contact information
Firuz Kamalov: Department of Electrical Engineering, Canadian University Dubai, Dubai 117781, United Arab Emirates
Hana Sulieman: Department of Mathematics and Statistics, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Sherif Moussa: Department of Electrical Engineering, Canadian University Dubai, Dubai 117781, United Arab Emirates
Jorge Avante Reyes: Department of Electrical Engineering, Canadian University Dubai, Dubai 117781, United Arab Emirates
Murodbek Safaraliev: Department of Automated Electrical Systems, Ural Federal University, 620002 Yekaterinburg, Russia

Energies, 2024, vol. 17, issue 3, 1-13

Abstract: Accurate forecasting is one of the keys to the efficient use of the limited existing energy resources and plays an important role in sustainable development. While most of the current research has focused on energy price forecasting, very few studies have considered medium-term (monthly) electricity generation. This research aims to fill this gap by proposing a novel forecasting approach based on zero-shot transfer learning. Specifically, we train a Neural Basis Expansion Analysis for Time Series (NBEATS) model on a vast dataset comprising diverse time series data. Then, the trained model is applied to forecast electric power generation using zero-shot learning. The results show that the proposed method achieves a lower error than the benchmark deep learning and statistical methods, especially in backtesting. Furthermore, the proposed method provides vastly superior execution time as it does not require problem-specific training.

Keywords: electricity forecasting; transfer learning; electricity generation; NBEATS; deep learning; medium-term (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/3/626/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/3/626/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:3:p:626-:d:1328095

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().