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Optimizing future cost and emissions of electric delivery vehicles

Dados Bibliográficos

ID19468142
AutoresMaxwell Woody (0000-0002-6610-2777, Center for Sustainable Systems, School for Environment and Sustainability University of Michigan Ann Arbor Michigan USA, autor correspondente), Michael Craig (0000-0002-3031-5041, Center for Sustainable Systems, School for Environment and Sustainability University of Michigan Ann Arbor Michigan USA), Parth Vaishnav (0000-0003-1582-4523, Center for Sustainable Systems, School for Environment and Sustainability University of Michigan Ann Arbor Michigan USA), Geoffrey Lewis (0000-0001-6426-6068, Center for Sustainable Systems, School for Environment and Sustainability University of Michigan Ann Arbor Michigan USA), Gregory A Keoleian (0000-0002-7096-1304, Center for Sustainable Systems, School for Environment and Sustainability University of Michigan Ann Arbor Michigan USA)
Ano2022
Volume26
Fascículo3
Páginas1108-1122
Data de publicação2022-06-01
Open AccessSim
TipoARTICLE
PeriódicoJournal of Industrial Ecology (JOURNAL)
Identificadores do periódicoISSN: 1088-1980 • E-ISSN: 1530-9290
EditoraSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1111/jiec.13263
OpenAlexW4220804321
IdiomaEN
Referências citadas57

Electrification of delivery vehicles will play an important role in decarbonizing the transportation sector. As electricity‐generating technologies vary regionally and temporally, where electric vehicles are deployed and when they are charged will determine the greenhouse gas (GHG) emissions and cost consequences of delivery vehicle electrification. We couple a vehicle charging model with a dataset that provides hourly projections of marginal electricity cost and marginal emissions factors across 134 electricity balancing areas in the United States. We calculate the cost and emissions of charging an electric delivery vehicle over a 10‐year service life (2021–2030) at different times of day and in different locations. Using a multiobjective optimization framework, we explore two potential goals—minimizing GHG emissions and minimizing cost—and investigate the tradeoffs between those goals. We show emissions ranging from 136 to 485 g CO 2 /mile, and costs ranging from 0.79 to 3.18 cents/mile depending on location and optimization weighting. We demonstrate the impact of charge time‐of‐day optimization frequency, showing emissions reductions of 19–62% by choosing the optimal charging time every day, rather than annually. We show that the benefits of electrification are reduced when potential charge times are constrained (e.g., if charging must take place overnight), and we calculate the carbon price needed to align cost‐optimized and emissions‐optimized charge timing in different regions. Our results highlight the opportunity to reduce cost and emissions by strategically charging at certain times of day and show the importance of accounting for spatial and temporal variability when developing effective carbon‐reduction strategies

Economics · Electric vehicle · Electrical engineering · Electricity · Electrification · Environmental economics · Greenhouse gas · Marginal cost · Microeconomics · Natural resource economics · Total cost · Total cost of ownership · Weighting · Advanced battery technologies research · Computer Science · Electric Vehicles and Infrastructure · Engineering · Environmental Science · Transportation and Mobility Innovations

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