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An optimization-based framework for energy management for low-income prepaid electricity customers

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Prepaid Energy Management

Maitreyee Marathe, Prof. Line Roald
University of Wisconsin-Madison

  • datasets - used to store data for experiments.
  • simple-experiments - to run experiments with simulation durations as a multiple of 1 day. Data present in files datasets/simple-experiment-data-1.csv, datasets/simple-experiment-data-2.csv, and datasets/simple-experiment-data-3.csv can be used.
  • monthly-experiments - to run experiments with simulation durations as a multiple of 1 month. Residential electricity usage data can be obtained from Pecan Street Dataport.
  • In each folder, run the file main.jl, supporting functions are present in functions.jl.

Links and citations for our publications:
Energy Management for Prepaid Customers: A Linear Optimization Approach

@article{marathe2024energy,
  title={Energy Management for Prepaid Customers: A Linear Optimization Approach},
  author={Marathe, Maitreyee and Roald, Line A},
  journal={arXiv preprint arXiv:2408.14703},
  year={2024}
}

Optimal Energy Rationing for Prepaid Electricity Customers

@inproceedings{marathe2023optimal,   
  title={Optimal Energy Rationing for Prepaid Electricity Customers},   
  author={Marathe, Maitreyee and Roald, Line A},   
  booktitle={2023 IEEE Belgrade PowerTech},   
  pages={01--06},   
  year={2023},   
  organization={IEEE}   
}

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