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Merge pull request #2 from chrisyeh96/journal
Nonlinear simulation merge
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README.md

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**California Institute of Technology and UC San Diego**
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## Getting started
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### Install packages
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1. Install [miniconda3](https://docs.conda.io/en/latest/miniconda.html).
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2. Install the `voltctrl` conda environment:
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```bash
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conda env update -f env.yml --prune
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```
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3. Request a Mosek license ([link](https://www.mosek.com/products/academic-licenses/)). Upon receiving the license file (`mosek.lic`) in an email, create a folder `~/mosek` and copy the license file into that folder.
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### Running voltage control experiments
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TODO
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## Data Files (in `/data`)
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The original data files were provided by the authors of the following paper:
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> Guannan Qu and Na Li. 2020. Optimal Distributed Feedback Voltage Control under Limited Reactive Power. _IEEE Transactions on Power Systems_ 35, 1 (Jan. 2020), 315–331. https://doi.org/10.1109/TPWRS.2019.2931685
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The original data files ("orig_data.zip") are attached to the [releases](https://github.com/chrisyeh96/voltctrl/releases/tag/v1.0). These original data files have been processed into the following files, which are the only files relevant for our experiments. See the inspect_matlab_data.ipynb notebook for details.
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The original data files ("orig_data.zip") are attached to the [releases](https://github.com/chrisyeh96/voltctrl/releases/tag/v1.0). These original data files have been processed into the following files, which are the main files relevant for our experiments. See the [inspect_matlab_data.ipynb](notebooks/inspect_data.ipynb) notebook for details.
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**PV.mat**
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- contains single key `'actual_PV_profile'`
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- 'branch': shape [55, 13], type float64
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- 'gen': shape [1, 21], type int16
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**nonlinear_voltage_baseline.npy**
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- float64 array, shape [14421, 56]
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- description: balanced AC nonlinear simulation voltages, generated by [nonlinear_no_control.py](nonlinear_no_control.py)
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- each column is the voltage of a bus, with column 0 being bus 0 (the substation)
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- units: p.u. voltage (multiply by 12 to get kV)
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See the attachment in [releases](https://github.com/chrisyeh96/voltctrl/releases/tag/v1.0) for Python `.pkl` files containing the results of running the various algorithms. These Pickle files are read by the various Jupyter notebooks for plotting and analysis.
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