Urban-Scale Control of School Bus Fleet Charging and Discharging Strategies Using Single and Multi-Stage Optimization

This paper presents a dual-strategy approach to optimizing charging and discharging schedules for school bus fleets, using the limited charging infrastructure effectively. We aim to ensure that each bus is fully charged for daily operations and aids in grid stability during peak demand. The first strategy utilizes linear programming to schedule overnight charging at available station sockets and strategic discharging during peak periods, efficiently coordinating limited resources. The second strategy employs metaheuristic techniques for continuous optimization, focusing on precise power requirements and offering greater flexibility than the linear model.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905691
Citations
2
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.41

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article

Urban-Scale Control of School Bus Fleet Charging and Discharging Strategies Using Single and Multi-Stage Optimization

Sunil Subedi, Junbo Zhao, Alaa Selim, Soroush Vahedi
2 citations
Transportation and Mobility Innovations
0.41
article

Urban-Scale Control of School Bus Fleet Charging and Discharging Strategies Using Single and Multi-Stage Optimization

Sunil Subedi, Junbo Zhao, Alaa Selim, Soroush Vahedi
article en
2 citations

Abstract

This paper presents a dual-strategy approach to optimizing charging and discharging schedules for school bus fleets, using the limited charging infrastructure effectively. We aim to ensure that each bus is fully charged for daily operations and aids in grid stability during peak demand. The first strategy utilizes linear programming to schedule overnight charging at available station sockets and strategic discharging during peak periods, efficiently coordinating limited resources. The second strategy employs metaheuristic techniques for continuous optimization, focusing on precise power requirements and offering greater flexibility than the linear model.

Oak Ridge National Laboratory (US), University of Connecticut (US)
U.S. Department of Energy, UT-Battelle, Office of Electricity, Office of Energy Efficiency
Sustainable cities and communities
Openalex Percentile: Top 37%
Transportation and Mobility Innovations
0.41
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