Anomaly Detection in the U.S Electricity Grid data
Jiaqi Ding jd2269
Lewis Tian zt89
Prabhat Koutha pk454
This project aims to identify anomalies in the U.S. electricity grid data to help mitigate the impact of data quality issues for electricity traders, among others. The project uses a dataset from EIA that contains hourly electric grid data for the NW region with over 66000 hourly observations. We will implement various semi-supervised/supervised algorithms and compare their performance. Additionally, we will perform time series analysis to replace the anomalous values.
Video link: https://youtu.be/MeOx_AH-L7I