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April 15, 2026Energies0 citationsOpen Access

EV Dynamic Charging and Discharging Strategy Considering Integrated Energy Station Congestion and Electricity Trading

XLXiang LiaoHWHaiwei WangYCYujie Cheng

Key Points

  • This research aims to develop a dynamic charging and discharging strategy for electric vehicles that optimizes discharge revenue while addressing integrated energy station congestion.
  • Developed a real-time collaborative simulation framework integrating transportation network and energy interactions.
  • Proposed an EV integrated energy station selection strategy focusing on multiple factors affecting discharge.
  • Designed a dynamic pricing model based on vehicle arrival patterns and electricity transactions.
  • EV selection strategy reduced average user waiting time by 5.36%.
  • Network time loss decreased by 3.86%.
  • EV discharge revenue increased by 6.79%.
  • Dynamic pricing further reduced waiting time by 3.46% and network time loss by 4.80%.

Abstract

As the electrification of transportation systems accelerates, incentivizing electric vehicle (EV) participation in vehicle-to-grid (V2G) operations is becoming increasingly crucial. This paper introduces a dynamic EV charging and discharging strategy that incorporates integrated energy station (IES) congestion and electricity purchase and sale scenarios. The proposed strategy seeks to facilitate orderly EV charging and discharging within a real-time simulation framework that integrates the transportation network (TN), IES, and the external grid (EG). First, we develop a real-time collaborative simulation framework that combines microscopic traffic flow (MTL) and IES–grid energy interaction models to account for mutual feedback among these components. Second, we propose an EV IES selection strategy aimed at maximizing discharge revenue, which takes into account various factors, including driving distance, time costs, battery degradation, discharge benefits, and government subsidies. Finally, we design a dynamic discharge pricing model based on real-time vehicle arrival patterns at the IES and the status of electricity purchases and sales. Simulation results show that the EV IES selection strategy, optimized for discharge revenue, reduces average user waiting time by 5.36%, decreases network time loss by 3.86%, and increases EV discharge revenue by 6.79%. Furthermore, the introduction of dynamic pricing leads to additional reductions in waiting time and network time loss by 3.46% and 4.80%, respectively. The proposed mechanism and pricing strategy effectively mitigate traffic congestion, enhance user discharge revenue, and provide flexible scheduling options for IES operations.

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Cite This Study

Liao et al. (2026) studied this question.

synapsesocial.com/papers/69df2bece4eeef8a2a6b0dc8https://doi.org/10.3390/en19081879
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1An Ordered Charging–Discharging Optimization Strategy for Electric Vehicles Considering Discharge Restraint and Carbon Emission Reduction2026
  2. 2Collaborative Optimization Scheduling of New Energy Vehicles and Integrated Energy Stations Based on Coupled Vehicle Routing and Charging Decisions2026 · 1 citations
  3. 3Optimization strategy of orderly charging for electric vehicles based on V2G technology2025
  4. 4A Grid-Aware Two-Stage Dynamic Routing and Charging Station Selection Framework for Electric Vehicles Under Traffic–Energy Coordination2026 · 1 citations
  5. 5Dynamic pricing strategy for efficient electric vehicle charging and discharging in microgrids using multi-objective jaya algorithm2024 · 11 citations