Optimal Workload Allocation for Distributed Edge Clouds With Renewable Energy and Battery Storage

This repository contains the official implementation of the proposed model as well as its compared benchmark.

Pointers: arxiv ICNC 2024

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Prerequisites

• CVX: Matlab Software for Disciplined Convex Programming: CXV
• Gurobi solver (Free license for academic students): Gurobi solver

File

• Model_1.m - Model_3.m: Models \textbf{M1} - \textbf{M3} encompass all the benchmarks we will use for comparison. These models correspond to those detailed in the Appendix of our report.
• Model_0.m: proposed model with battery and ``sell-back-to-grid" option
• Model_1.m: This model lacks the capability for the ``sell-back-to-grid" option, and ECs do not have %come equipped with batteries.
• Model_2.m: This model exclusively focuses on using batteries to store energy and does not allow the operator to sell surplus energy back to the grid.
• Model_3.m: This model is designed to enable the selling of excess energy back to the grid, while ECs do not feature battery installations.
• ICNC_results. mat: all saved data.
• results.zip: All saved figures used in paper.
• init.m: initialization for parameter setting.
• ICNC_main.m: Experiments.

Citation and Acknowledgements

Bibtex. If you find our code useful for your research, please cite the arxiv:

@article{nguyen2023optimal,
  title={Optimal Workload Allocation for Distributed Edge Clouds With Renewable Energy and Battery Storage},
  author={Nguyen, Duong Thuy Anh and Cheng, Jiaming and Trieu, Ni and Nguyen, Duong Tung},
  journal={arXiv e-prints},
  pages={arXiv--2310},
  year={2023}
}

Acknowledgments and Disclosure of Funding. This work was funded, in part, by the Natural Sciences and Engineering Research Council of Canada (NSERC), Canada and National Science Foundation (NSF), USA.

Contact

Please submit a GitHub issue or contact [email protected] if you have any questions or find any bugs.