Date of Award:

8-2023

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Electrical and Computer Engineering

Committee Chair(s)

Jacob Gunther

Committee

Jacob Gunther

Committee

Todd Moon

Committee

Greg Droge

Committee

Kevin Moon

Committee

John Edwards

Abstract

Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects from uncontrolled loads, differences between daytime and overnight charging, and variable rate charging. We propose using mixed integer linear programs, to encode the charging action space, physical bus constraints, and battery state of charge dynamics. We also consider results for three scenarios: uncontested charging, which uses equal numbers of buses and chargers, contested charging, which has more buses than chargers, and variable charge rates. We desire to show that BEBs can be added to the fleet so that both the runtime of the planning framework and monthly cost increase linearly with the number of buses so that the charge planning framework is scalable.

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