/DRO_DCOPF_CONTEXTUAL

GNU General Public License v3.0GPL-3.0

Numerical Experiments Data from the paper entitled "Distributionally Robust Optimal Power Flow with Contextual Information"

Goals

The purpose of this repository is to provide the details of the numerical experiments coded in the Python programming language used in the paper [1]. This paper has been developed by some members of the OASYS group through funding from the project Flexanalytics. We encourage you visit the related links to know more about our research.

Contents

This repository includes the data about the two test problems used in the paper:

  • A 118-bus case study:

    • [118bus_case: This folder contains the data and codes (medium and high wind penetration case) used in the numerical experiment corresponding to the 118-bus case study with contextual information considered in [1].
  • Illustrative example (3-bus system) at the Appendix.

    • [3bus_case]: This folder contains the data and codes used in the numerical experiment corresponding to the Illustrative example (3-bus system) used at the Appendix of [1].

References 📚

[1] Esteban-Pérez, A., & Morales, J. M. (2021). Distributionally Robust Optimal Power Flow with Contextual Information. arXiv preprint arXiv:2109.07896.

Do you want to contribute? 👨🏾‍🔬

Any feedback is welcome ✨ so please feel free to ask about or comment on anything you want via a Pull Request in this repo. If you need more help, you can ask Adrián Esteban-Pérez (adrianesteban@uma.es) 📧.

Contributors

Developed by 👨🏾‍💻

License 📝

Copyright 2021 Optimization and Analytics for Sustainable energY Systems (OASYS)

Licensed under the GNU General Public License, Version 3 (the "License");
you may not use this file except in compliance with the License.
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