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- W4384788235 abstract "While vehicle electrification offers an opportune path to transportation decarbonization, current tariffs can make the transition cost prohibitive for commercial fleets. To this end, providing frequency regulation has been proposed as a means for fleets to generate revenues while parked. However, regulation dispatch uncertainty can make participation difficult for fleets with strict schedules, and assuming a deterministic dispatch profile tends to overestimate a fleet’s flexibility and underestimate the financial risk of its bids. Moreover, the most efficient retail rate and strategy for providing regulation, or simply charging alone, highly dependends on fleet schedule and demand relative to other loads a fleet owner may have. Thus, we pose a two-stage, stochastic model, informed by real-world data, to realistically determine optimal charging and regulation behavior under different tariffs. A case study demonstrates model utility in analyzing a last-mile delivery truck fleet housed at a large shipping warehouse." @default.
- W4384788235 created "2023-07-20" @default.
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- W4384788235 date "2023-01-01" @default.
- W4384788235 modified "2023-09-27" @default.
- W4384788235 title "Modeling Commercial Fleet Charging and Regulation Strategies via Data-driven Optimization" @default.
- W4384788235 cites W3114827269 @default.
- W4384788235 doi "https://doi.org/10.1016/b978-0-443-15274-0.50451-0" @default.
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