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GE Vernova

Battery Scheduling for Carbon Reduction

This student team worked to research load + solar + storage systems and the ways to best schedule energy storage for minimum greenhouse gas emissions. Using historical grid carbon intensity data from https://www.watttime.org/ or other sources, students attempted to first determine net carbon emissions for a typical residential or commercial load over the course of a month. Next, students worked to assess the impact of installing a PV system, assuming a system size and output profile using historical weather data and information and a basic PV production model. Finally, the students worked to design a battery energy storage system and controller that couples with the solar installation to minimize the net carbon footprint. The student team attempted to design the battery controller (rule-based, PID, LP, etc.) to steer battery charging/discharging during day-to-day operations towards a least carbon objective, taking into account load, grid carbon intensity data and solar output.

Faculty Adviser(s)

Payman Arabshahi, Electrical & Computer Engineering

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