Volume 43 Issue 11
Nov.  2022
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YAN Haoyuan, ZHAO Tianyang, LIU Xiaochuan, DING Zhaohao. Modeling of Electric Vehicles as Mobile Energy Storage Systems Considering Multiple Congestions[J]. Applied Mathematics and Mechanics, 2022, 43(11): 1214-1226. doi: 10.21656/1000-0887.430303
Citation: YAN Haoyuan, ZHAO Tianyang, LIU Xiaochuan, DING Zhaohao. Modeling of Electric Vehicles as Mobile Energy Storage Systems Considering Multiple Congestions[J]. Applied Mathematics and Mechanics, 2022, 43(11): 1214-1226. doi: 10.21656/1000-0887.430303

Modeling of Electric Vehicles as Mobile Energy Storage Systems Considering Multiple Congestions

doi: 10.21656/1000-0887.430303
  • Received Date: 2022-10-04
  • Accepted Date: 2022-12-05
  • Rev Recd Date: 2022-11-23
  • Available Online: 2022-12-06
  • Publish Date: 2022-11-30
  • To realize the optimal operation of urban coupled transportation power systems underthe road, charging facilities, and transmission line congestions, a dynamic optimal traffic power flow (DOTPF) model was formulated under congestions. Based on the time space network (TSN) approach, a novel TSN with queues was proposed, considering the moving, parking, charging, and queueing state transitions. A vehicle routing problem was formulated for electric vehicles (EVs) and further incorporated into the dynamic traffic assignment problem (DTAP), reducing the traffic demand losses. With security and reserve constraints, a dynamic security-constrained carbon dioxide-oriented optimal power flow (OPF) problem was formulated to reduce the carbon emission and generation cost, by optimizing the scheduling of thermal units and energy storage systems. A multi-objective DOTPF problem was formulated, and further reformulated into a convex mixed-integer quadratic programming problem. The effectiveness of the proposed DOTPF was verified based on the simulation results on coupled IEEE-30 and Sioux Falls system.

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