PowNet Refactored

PyPowNet: A Python Library for PowNet Model Optimization

PowNet is a least-cost optimization model for simulating the Unit Commitment and Economic Dispatch of large-scale power systems. It has been applied to model Cambodian, Laotian, and Thai power systems. PyPowNetR improves the original implementation of PowNet and simplifies the model specification process. It aims to help researchers to import their own power system data on the PowNet model and and serve as a benchmark for optimization solvers. Ultimately, we hope that our effort will encourage more regions to adopt renewable energy sources in the power system.

Requirements

PyPowNetR is written in Python 3.6. It requires the following Python packages: (i) Pyomo, (ii) NumPy, and (iii) Pandas. It also requires an optimization solver (e.g. CPLEX). PyPowNetR has been tested in Anaconda on Windows 10.

Installation

You can perform a minimal install of pypownetr with:

    git clone https://github.com/pacowong/pypownet.git
    cd pypownet
    pip install -e .

How to run

python pypownetr/solver.py datasets/kamal0013/camb_2016 2016 1 2 1 glpk

If you have installed [glpk], this will execute the model using the data on Cambodian power system. The script also generates .csv files containing the values of each decision variable.

Citation

If you use PyPowNetR for your research, please cite the following papers (mainly from the original authors):

@article{chowdhury2020pownet,
  title={{PowNet: A Network-Constrained Unit Commitment/Economic Dispatch Model for Large-Scale Power Systems Analysis}},
  author={Chowdhury, AFM Kamal and Kern, Jordan and Dang, Thanh Duc and Galelli, Stefano},
  journal={Journal of Open Research Software},
  volume={8},
  number={1},
  year={2020},
  publisher={Ubiquity Press}
}

@article{chowdhury2020expected,
  title={{Expected Benefits of Laos' Hydropower Development Curbed by Hydroclimatic Variability and Limited Transmission Capacity: Opportunities to Reform}},
  author={Chowdhury, AFM Kamal and Dang, Thanh Duc and Bagchi, Arijit and Galelli, Stefano},
  journal={Journal of Water Resources Planning and Management},
  volume={146},
  number={10},
  pages={05020019},
  year={2020},
  publisher={American Society of Civil Engineers}
}

@article{chowdhury2020greater,
  title={{The Greater Mekong's climate-water-energy nexus: how ENSO-triggered regional droughts affect power supply and CO2 emissions}},
  author={Chowdhury, Kamal AFM and Dang, Thanh Duc and Nguyen, Hung TT and Koh, Rachel and Galelli, Stefano},
  journal={Earth and Space Science Open Archive ESSOAr},
  year={2020},
  publisher={American Geophysical Union}
}

@misc{pypownetr,
    author = {Pak-Kan Wong},
    title = {{PyPowNetR: A Python Library for Refactored PowNet Model Optimization}},
    year = {2020},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/pacowong/pypownet}},
}

License

PyPowNetR is released under the MIT license.