CINELDI example

To run the CINELDI example do the following:

$ cd examples/CINELDI
$ python run.py

This will produce a directory called “results” containing the simulation results. The directory has the following structure:

results
├── monte_carlo
│   ├── B1
│   ├── B2
│   ├── B3
│   ├── B4
│   ├── B5
│   │   └── EV1
│   ├── B6
│   ├── dist_network1
│   ├── M1
│   ├── M2
│   ├── M3
│   ├── microgrid1
│   ├── ps1
│   └── trans_network1
└── sequence
    ├── 1
    │   ├── battery
    │   ├── bus
    │   ├── circuitbreaker
    │   ├── disconnector
    │   ├── dist_network1
    │   ├── distribution_controllers
    │   ├── ev_parks
    │   ├── line
    │   ├── microgrid1
    │   ├── microgrid_controllers
    │   ├── ps1
    │   └── trans_network1
    └── 2
        ├── battery
        ├── bus
        ├── circuitbreaker
        ├── disconnector
        ├── dist_network1
        ├── distribution_controllers
        ├── ev_parks
        ├── line
        ├── microgrid1
        ├── microgrid_controllers
        ├── ps1
        └── trans_network1

As you can see, the results are divided into a Monte Carlo directory and a sequence directory. They contain Monte Carlo and sequential results respectively.

Below is an example of how to read and obtain some distribution metrics for the ENS (Energy Not Supplied) index of the power system (ps1) using pandas.

import os
import pandas as pd

path = os.path.join(
    "results",
    "monte_carlo",
    "ps1",
    "ENS.csv",
)

df = pd.read_csv(path, index_col=0)

print(df.describe())