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”

  1. Pamela Pierce says:

    This is such a great example of bringing the theory from the classroom into practice. Nice job, team!

  2. Emily Armour says:

    Thanks for sharing, team. We can really see how much the demand for the electric changes based on those variables.

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