The temporal RL agent embeds temporal awareness to RL by integrating forecasts (e.g., load, PV, and wind generation) into decision-making through an attention-based temporal embedding module.
[1] A. H. Ardakani, J. Hurink, I. Gibson and E. Shirazi, Attention-Based Temporal Reinforcement Learning for Energy System Control, 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), Valletta, Malta, 2025, pp. 1-5, doi: 10.1109/ISGTEurope64741.2025.11305619.
[2] A. H. Ardakani, J. Hurink, I. Gibson and E. Shirazi, Embedding Temporal Awareness in Reinforcement Learning Models for Energy System Control, Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems (E-Energy '25). Association for Computing Machinery, New York, NY, USA, 2025, 1002–1004. https://doi.org/10.1145/3679240.3734686
Run the following notebook:
$ 6. attention_TRL.ipynb
| Data | Source |
|---|---|
PV & Wind Generation |
ENTSO-E Transparency Platform |
Load |
ENTSO-E Transparency Platform |
Electricity Price |
ENTSO-E Transparency Platform |
CO2 Emission |
Nationaal Energie Dashboard |