ec-data-analysis 0.3.0

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.

Example usage is provided in the main.py file:

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)
    capacities: np.ndarray = np.linspace(1e2, 1e3, 3)
    ecData.createReport(capacities)

The example compares the effect on the community of batteries of 3 different capacities (100kw/h, 550kh/h and 1000kw/h). The example report generated by this is in out/report.pdf based on the example dataset data/EC_EV_dataset.xlsx.

The code is annotated with type hints, and the provided Makefile typechecks with

Make typecheck

Run

Make all

to format the python files, typecheck and run main.py, or

Make run

to simply run main.py.