@inproceedings{aquino_evcharging_2024,
author={Aquino, Alejandro D. Owen and Talkington, Samuel and Molzahn, Daniel K.},
booktitle={2024 IEEE Texas Power and Energy Conference (TPEC)},
title={{Managing Vehicle Charging During Emergencies via Conservative Distribution System Modeling}},
year={2024},
volume={},
number={},
pages={1-6},
doi={10.1109/TPEC60005.2024.10472235}
}
Combinatorial distribution system optimization problems, such as scheduling electric vehicle (EV) charging during evacuations, present significant computational challenges. These challenges stem from the large numbers of constraints, continuous variables, and discrete variables, coupled with the unbalanced nature of distribution systems. In response to the escalating frequency of extreme events impacting electric power systems, this paper introduces a method that integrates sample-based conservative linear power flow approximations (CLAs) into an optimization framework. In particular, this integration aims to ameliorate the aforementioned challenges of distribution system optimization in the context of efficiently minimizing the charging time required for EVs in urban evacuation scenarios.
Admittance Matrix Concentration Inequalities for Understanding Uncertain Power Networks
Samuel Talkington, Cameron Khanpour, Rahul K. Gupta, Sergio A. Dorado-Rojas, Daniel Turizo, Hyeongon Park, Dmitrii M. Ostrovskii, and Daniel K. Molzahn