andrew-fryer/cec-2021

New Brunswick's Renewable Energy

New Brunswick contains many different energy sources, both renewable and non-renewable. The goal of this projects was to predict the future energy requirements of the province based on past data, and use these predictions to maximize the renewable energy use while minimizng the power generation costs.

Getting Started

Clone the repository with "git clone https://github.com/CEC2021Programming-ProgrammationCCI2021/hammond-hammond.git"

(Optional) Setup Virtual Environment

python3 -m venv venv && source venv/bin/activate

Installing

pip install -r requirements.txt

Running

python3 hammond_programmingDriver.py

Presentation

Please see hammond_programming.pdf

Structure

hammond_programmingDriver.py

Runs main project & generates output .csv files

parse.py

Loads in data from excel files

power_consumption_predict.py

Predicts the future energy consumption of each New Brunswick zone per month

visualize.py

Creates the visualization of the past and predicted data

greedy_algorithm.py (deprecated)

Simple greedy algorithm implementation for cost analysis (this approach is no longer used)

clean_energy_types.py

Shows which energies are emissive and non-emissive

algorithm.py

Contains the function which runs the optimizing algorithm on a year of energy data for New Brunswick

zone-scoring.py (deprecated)

Initial file with thought process notes for algorithm

Built With

python -> pandas, numpy, plotly

Authors

Andrew Fryer Kyle Singer Joe Grosso Andrew Farley

Acknowledgments

CEC 2021 for the project idea and input data