Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs Article Swipe

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Sijia Geng , Thomas C. M. Lee , Dharik S. Mallapragada , Audun Botterud ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2506.09388

Electrified transportation leads to a tighter integration between transportation and energy distribution systems. In this work, we develop scalable optimization models to co-design hydrogen and battery electric vehicle (EV) fleets, distributed energy resources, and fast-charging and hydrogen-fueling infrastructure to efficiently meet transportation demands. A novel integer-clustering formulation is used for optimizing fleet-level EV operation while maintaining accurate individual vehicle dispatch, which significantly improves the computation efficiency with guaranteed performance. We apply the optimization model to Boston's public transit bus network using real geospatial data and cost parameters. Realistic insights are provided into the future evolution of coupled electricity-transportation-hydrogen systems, including the effects of electricity price structure, hydrogen fuel cost, carbon emission constraint, temperature effects on EV range, and distribution system upgrade cost.

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2506.09388
PDF: https://arxiv.org/pdf/2506.09388
OA Status: green
OpenAlex ID: https://openalex.org/W4417308189

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OpenAlex ID: https://openalex.org/W4417308189

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DOI: https://doi.org/10.48550/arxiv.2506.09388

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Title: Integer-Clustering Optimization of Hydrogen and Battery EV Fleets Considering DERs

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Type: preprint

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Language: en

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Publication year: 2025

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Publication date: 2025-06-11

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Authors: Sijia Geng, Thomas C. M. Lee, Dharik S. Mallapragada, Audun Botterud

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Landing page: https://arxiv.org/abs/2506.09388

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PDF URL: https://arxiv.org/pdf/2506.09388

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Open access: Yes

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OA status: green

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Cited by: 0

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