climatechange-ai-tutorials/zevi

This tutorial surveys different methods to formulate electric vehicle (EV) charging and energy dispatch as an optimization problem, using tools such as convex optimization, Markov decision process (MDP), and reinforcement learning (RL).

Zero-Emission Vehicle Intelligence (ZEVi): Effectively Charging Electric Vehicles at Scale Without Breaking Power Systems (or the Bank)

This tutorial surveys different methods to formulate electric vehicle (EV) charging and energy dispatch as an optimization problem, using tools such as convex optimization, Markov decision process (MDP), and reinforcement learning (RL).

Author(s):

• Shasha Lin, NextEra Mobility, sl4964@nyu.edu / shasha.lin@nexteraenergy.com
• Tamara Monge, NextEra Mobility, tamara.monge@nexteraenergy.com
• Jonathan Brophy, NextEra Mobility, jonathan.brophy@nexteraenergy.com
• Jamie Hussman, NextEra Mobility, jamie.hussman@nexteraenergy.com
• Michelle Lee, NextEra Mobility, michelle.lee@nexteraenergy.com
• Sam Penrose, NextEra Mobility, samuel.penrose@nexteraenergy.com

Originally presented at NeurIPS 2023

Access this tutorial

We recommend executing this notebook in a Colab environment to gain access to GPUs and to manage all necessary dependencies.

Estimated time to execute end-to-end: 10 minutes

Contribute to this tutorial

Please refer to these GitHub instructions to open a pull request via the "fork and pull request" workflow.

Pull requests will be reviewed by members of the Climate Change AI Tutorials team for relevance, accuracy, and conciseness.

Climate Change AI Tutorials

Check out the tutorials page on our website for a full list of tutorials demonstrating how AI can be used to tackle problems related to climate change.

License

Usage of this tutorial is subject to the MIT License.

Cite

Plain Text

Lin, S., Monge, T., Brophy, J., Hussman, J., Lee, M., & Penrose, S. (2023). Zero-Emission Vehicle Intelligence (ZEVi): Effectively Charging Electric Vehicles at Scale Without Breaking Power Systems (or the Bank) [Tutorial]. In Conference on Neural Information Processing Systems. Climate Change AI. https://doi.org/10.5281/zenodo.11624883

BibTeX

@misc{lin2023zero-emission,
  title={Zero-Emission Vehicle Intelligence (ZEVi): Effectively Charging Electric Vehicles at Scale Without Breaking Power Systems (or the Bank)},
  author={Lin, Shasha and Monge, Tamara and Brophy, Jonathan and Hussman, Jamie and Lee, Michelle and Penrose, Sam},
  year={2023},
  organization={Climate Change AI},
  type={Tutorial},
  doi={https://doi.org/10.5281/zenodo.11624883},
  booktitle={Conference on Neural Information Processing Systems},
  howpublished={\url{https://github.com/climatechange-ai-tutorials/zevi}}
}