959 resultados para Demand-Responsive Transportation Systems.
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Federal Highway Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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Transportation Department, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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Transportation Department, Washington, D.C.
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Transportation Department, Office of University Research, Washington, D.C.
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Mode of access: Internet.
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Transportation Systems Center, Cambridge, Mass.
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Transportation Department, Washington, D.C.
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Transportation Department, Washington, D.C.
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Mode of access: Internet.
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An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.