Optimizing Energy Use in Buildings

Presenter

Andrew Austin Egan

Campus

UMass Amherst

Sponsor

Hernan D. Bejarano, Department of Resource Economics, UMass Amherst

Schedule

Session 2, 11:30 AM - 12:15 PM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board A93, Campus Center Auditorium, Row 5 (A81-A100) [Poster Location Map]

Abstract

The energy used in powering buildings currently accounts for around 40% of total demand in the US, a massive amount that needs to be reduced looking towards the future. The focus of this thesis revolves around optimizing energy usage in a building to minimize carbon dioxide emissions. The specific building under study is the proposed “green” Sustainable Engineering Laboratory at the University of Massachusetts Amherst. To establish this building as a model of green building practices, it is imperative to efficiently utilize its battery energy storage and solar power to minimize its environmental impact from fossil fuels. This optimization is pursued through a model considering three primary parameters: building energy demand, solar production, and marginal carbon emissions throughout the day, coming together to minimize cumulative CO2 emissions. Leveraging Gurobi optimization software, we have computed the optimal schedule for battery charge and discharge given known parameters like battery size. Initial results showed the best times for charge and discharge, typically overnight and early afternoon. There are some limitations involved, namely sourcing data that lines up on the same days. Planned future steps include switching the minimizing to electricity cost as well as varying the battery sizes, solar emissions, and other factors. This model holds promise for application across various building types or optimization objectives, be it greenhouse gas reduction, energy cost management, or similar studies involving similar parameters. Through this optimization approach, we aim to significantly alleviate the environmental footprint of buildings, thus contributing to a more sustainable future.

Keywords

Energy, Engineering, Green

Research Area

Engineering

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