Plug-in electric vehicles are widely acknowledged as an effective tool for numerous environmental and economic concerns. In this article, a novel model for the planning of fast-charging stations is established based on a data-driven distributionally robust optimization approach, which aims to minimize the expected planning cost for both transportation network and distribution network. $\phi $ -divergence, a statistical measure, is utilized to establish the serviceability constraints. On the other hand, a modified capacitated flow refueling location model is employed to develop the location constraints. In addition, ac power flow constraints are developed to model the operation of DN with the penetrations of PEVs. Finally, a case study is illustrated to validate the proposed planning model.
Planning PEV Fast-Charging Stations Using Data-Driven Distributionally Robust Optimization Approach Based on ϕ-Divergence
IEEE Transactions on Transportation Electrification ; 6 , 1 ; 170-180
2020-03-01
2113880 byte
Article (Journal)
Electronic Resource
English
ROBUST OPTIMIZATION OF CHARGING OPERATIONS OF ELECTRIC VEHICLE CHARGING STATIONS
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