A GNN-based Day Ahead Carbon Intensity Forecasting Model for Cross-Border Power Grids

Author:

Zhang Xiaoyang1ORCID,Wang Dan1ORCID

Affiliation:

1. The Hong Kong Polytechnic University, Hong Kong

Publisher

ACM

Reference47 articles.

1. Potential for reducing global carbon emissions from electricity production—A benchmarking analysis

2. Carbon emission intensity in electricity production: A global analysis

3. Lasse F Wolff Anthony , Benjamin Kanding , and Raghavendra Selvan . 2020 . Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051 (2020). Lasse F Wolff Anthony, Benjamin Kanding, and Raghavendra Selvan. 2020. Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051 (2020).

4. Life cycle assessment of electricity production from renewable energies: Review and results harmonization

5. Heymi Bahar and Jehan Sauvage. 2013. Cross-border trade in electricity and the development of renewables-based electric power: lessons from Europe. (2013). Heymi Bahar and Jehan Sauvage. 2013. Cross-border trade in electricity and the development of renewables-based electric power: lessons from Europe. (2013).

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