ML-Energy Capstone 2022
The goal of this project is to develop a machine learning model that takes in different factors like demand, price, weather, pollutants, HILP events, and others and outputs a risk score for each individual generator on the electrical grid. To achieve this goal, we will spend the first semester collecting, validating, and visualizing the necessary data that is needed to train a model. Our team used Python, Jupyter Notebooks, pandas, matplotlib, and other tools to collect data from a multitude of different APIs, inspect and compare datasets, and create informative plots of data. As a team we hope that our risk scores will be able to help power venders and power buys make informed decisions about which generates should be used in a given day to maximize profit and minimize environmental impact.