ec-data-analysis 0.9.1

Manages Energy Community Datasets with support for computing optimal energy distribution, visualization and key statistics.

Wrapper for datasets about Energy Communities providing the ability to immediately extract key stats such as the breakdown of covered energy (self-coverage, trading over market, and discharged from community battery) and automatically generate a report. The market is implicit and computed optimally at each timestep using a max-flow algorithm.

The functionality is provided by the ECDataset class. For its construction, provide it with two 2D Pandas DataFrames production and consumption, where production[i][j] is the production of community member j at timestep i and consumption[i][j] is the consumption of community member j at timestep i. Also, pass the timestep used in the dataset as a fraction/multiple of one hour as a parameter.

Installation

To use in your own projects, pip install in a console first:

pip install ec-data-analysis

Then, simply import the ECDataset class:

from ec_data_analysis import ECDataset

Example Usage

Example usage is provided in the main.py file:

from ec_data_analysis import ECDataset

...

def main() -> None:
    data: pd.DataFrame = pd.read_excel("data/EC_EV_dataset.xlsx", sheet_name=None)
    production: pd.DataFrame = getSheet("PV", data)
    consumption: pd.DataFrame = getSheet("Load", data)

    ecData: ECDataset = ECDataset(production, consumption, 0.25)
    ecData.createReport()

The example report generated by this is in out/report.pdf based on the example dataset data/EC_EV_dataset.xlsx.

Develop

In case want to play with the code yourself to add more plots or metrics, the project is provided with a formating tool (black) and typechecker (mypy). The code is almost fully annotated with type hints, and the provided Makefile typechecks with:

Make typecheck

To format, typecheck and then run main.py, run:

Make all

Or to simply run main.py:

Make run