Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 14, Issue 3, Pages 2140-2151Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2022.3206511
Keywords
Electric vehicle charging; Costs; Indexes; Routing; Renewable energy sources; Batteries; Load flow; Generalized user equilibrium; coupled power-transportation networks; electric vehicles; charging station; decomposition algorithm; traffic assignment
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This paper proposes the generalized user equilibrium (GUE) method for the coupled power-transportation network (CPTN) operation, which tightens the interaction between the urban power distribution network (PDN) and transportation network (TN). The GUE concept is introduced to describe the steady traffic flow distribution under the constraints placed by PDN operation on TN. A GUE-based coordination model is established for CPTN with PDN generation scheduled and TN traffic assigned simultaneously. The effectiveness of the proposed model and method is verified through case studies on a real-world network, demonstrating the necessity of GUE and its potential in improving the CPTN operation.
The increasing proliferation of electric vehicles (EVs) tightens the interaction between urban power distribution network (PDN) and transportation network (TN). This paper proposes the generalized user equilibrium (GUE) method for the coupled power-transportation network (CPTN) operation. First, the GUE concept is proposed to describe the steady traffic flow distribution as an extension of user equilibrium (UE), which could no longer exist due to the constraints placed by PDN operation on TN. Second, the GUE-based coordination model is established for CPTN with PDN generation scheduled and TN traffic assigned simultaneously. Finally, a decomposition method is developed to solve the model efficiently, which is converted into a master problem and a series of feasible/optimal path generation sub-problems for individual origin-destination (O-D) pairs. The case studies on a real-world network have verified the effectiveness of the proposed model and method. The results demonstrate the necessity of GUE and its potential in improving the CPTN operation.
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