Abstract:
The transition to Battery Electric Buses (BEBs) presents both environmental benefits and operational challenges, particularly concerning grid capacity and cost-effective charging management. This study examines the deployment of BEBs by the Utah Transit Authority (UTA), utilizing real BEB charging data and analyzing simultaneous charging sessions across key stations in Salt Lake City and Ogden in Utah, US. A heuristic-based optimization framework is developed to integrate day-ahead simulation with real-time adjustments, ensuring efficient power allocation while minimizing costs and grid stress. The approach utilizes real-time energy prices and load data, along with synthetic day-ahead forecasted load data, to optimize charging schedules and improve the load factor. Additionally, power flow analysis using OpenDSS evaluates the impact of large-scale BEB integration on grid performance and is used to generate the operating envelope (OE) for the allowable charging power drawn from the grid. Results indicate that optimized charging reduces energy costs by up to 21% and 33% in Ogden and Salt Lake City, respectively, while improving load factor and minimizing peak demand. Furthermore, a 100 kWh Battery Energy Storage System (BESS) is introduced at on-route high demand charging stations to mitigate demand surges. Thus, this study highlights the importance of integrating real-time constraints with preemptive scheduling strategies and provides a scalable framework for managing BEB charging infrastructure under uncertainty.
See publication:
https://ieeexplore.ieee.org/document/11328062This publication pertains to:
Not surePublication Authors:
- Abdullah Al Mehadi
- Jackson Morgan
- Arifa Sultana
- Hongjie Wang
- Regan Zane