AMRE Team | Schneider Electric
Shane Epstein-Petrullo ’24, Statistical & Data Sciences
Manan Shahi ’23, Computer Science
Tyusha Sarawagi ’23, Statistical & Data Sciences and Business Economics
Advisors: Drew Pasteur, Jillian Morrison
The team was tasked with finding the most important variables for forecasting energy demand in three specific Independent System Operators (ISO). ISOs are organizations that coordinate, control, and monitor the electric grid in a given region. The team tackled this problem by extensively evaluating calendar and weather-related variables in conjunction with various feature selection techniques and machine learning models to make predictions.
Posted in Comments Enabled, Experiential Learning Showcase 2022 on November 16, 2022.
2 responses to “AMRE Team | Schneider Electric”
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This is such a great example of bringing the theory from the classroom into practice. Nice job, team!
Thanks for sharing, team. We can really see how much the demand for the electric changes based on those variables.