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Hierarchical multi-spatial-temporal scale coordinated optimization of power-transportation interconnected system based on dynamic user equilibrium with point queue
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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16
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Sustainable Energy, Grids and Networks, Volume 45
Abstract
The rapid development of electric vehicles (EVs) has promoted the deep coupling of power distribution network (PDN) and traffic network (TN), which has brought great uncertainty and time coupling problems to the power-transportation interconnected system (PTIS). A hierarchical dynamic interaction optimization of PTIS considering both economic factors and uncertainty is constructed. First, in view of the time scale difference between PDN and TN, a hierarchical multi-spatial-temporal scale coordinated optimal framework of PTIS is constructed to coordinate the path selection of EVs and the dispatching strategy of PDN considering the uncertainty of renewable energy. Then, dynamic differential equations are adopted to describe the dynamic transmission process of traffic flow, and based on the queue problem within fast charging stations, a model considering the spatial-temporal dynamic traffic flow distribution based on dynamic user equilibrium with point queue is established. Furthermore, to address the issue of power distribution for charging of EVs under the same charging station, a model predictive control strategy is adopted to redistribute the power to meet the charging and discharging requirements of EVs with different demands. Finally, a simulation analysis is conducted to verify the effectiveness of the method proposed in this paper. Compared with SUE, the proposed dynamic queue update of FCS and DUE reduced the congestion degree of TN by 3.65% and the TN cost by 570,000 CNY.
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Publisher Copyright: © 2026 Elsevier Ltd.
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Hou, M, Liu, X, Fu, R, Wang, R, Li, Y, Li, Z & Sun, Q 2026, 'Hierarchical multi-spatial-temporal scale coordinated optimization of power-transportation interconnected system based on dynamic user equilibrium with point queue', Sustainable Energy, Grids and Networks, vol. 45, 102146. https://doi.org/10.1016/j.segan.2026.102146