Optimal charging scheduling and management for a fast-charging battery electric bus system

Journal Article · Thu Aug 13 00:00:00 EDT 2020 · Transportation Research Part E: Logistics and Transportation Review

DOI:https://doi.org/10.1016/j.tre.2020.102056· OSTI ID:1848663

He, Yi ^[1]; Liu, Zhaocai ^[2]; Song, Ziqi ^[2]

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1. Utah State Univ., Logan, UT (United States). Dept. of Civil and Environmental Engineering; Utah State Univ., Logan, UT (United States)
2. Utah State Univ., Logan, UT (United States). Dept. of Civil and Environmental Engineering

Herein we discuss how battery electric buses (BEBs) are rapidly being embraced by public transit agencies because of their environmental and economic benefits. To address the problems of limited driving range and time-consuming charging for BEBs, manufacturers have developed rapid on-route charging technology that utilizes typical layovers at terminals to charge buses in operation using high power. With on-route fast-charging, BEBs are as capable as their diesel counterparts in terms of range and operating time. However, on-route fast-charging makes it more challenging to schedule and manage charging events for a BEB system. First, on-route fast-charging may lead to high electricity power demand charges. Second, it may increase electricity energy charges because of charging that occurs during on-peak hours. Without careful charging scheduling and management, on-route fast-charging may significantly increase fuel costs and reduce the economic attractiveness of BEBs. The present study proposes a network modeling framework to optimize the charging scheduling and management for a fast-charging BEB system, effectively minimizing total charging costs. The charging schedule determines when to charge a BEB, while the charging management strategically controls the actual charging power. Charging costs include both electricity demand charges and energy charges. The charging scheduling and management problem is first formulated as a nonlinear nonconvex program with time-continuous variables. A discretizing method and a linear reformulation technique are then adopted to reformulate the model as a linear program, which can be easily solved using off-the-shelf solvers, even for large-scale problems. Finally, the model is demonstrated with extensive numerical studies based on two real-world bus networks. The results demonstrate that the proposed model can effectively determine the optimal charging scheduling and management for a fast-charging BEB system, which carries the potential for use in large-scale real-world bus networks.

• Research Organization: PacifiCorp, Portland, OR (United States)
• Sponsoring Organization: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• Grant/Contract Number: EE0007997
• OSTI ID: 1848663
• Alternate ID(s): OSTI ID: 1647394
• Journal Information: Transportation Research Part E: Logistics and Transportation Review, Journal Name: Transportation Research Part E: Logistics and Transportation Review Journal Issue: C Vol. 142; ISSN 1366-5545
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
Battery electric buses
Business & Economics
Charging scheduling and management
Demand charges
Engineering
Fast-charging
Operations Research & Management Science
Time-of-use rate structure
Transportation