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<p>With the rapid growth in EV adoption, eco-routing should not only reduce energy consumption but also follow the changing environmental rules and make it easier for the grid to connect. This work presents a hybrid approach which couples the Mixed Integer Linear Programming formulation with heuristics, such as Dijkstra’s algorithm, along with Ant Colony Optimization, that returns a practical and scalable solution for real-time EV routing. Our model features compliance with <i>GreenZone</i>, which automatically enforces environmental rules in various parts of the city, and Vehicle-to-Grid (V2G) incentives, which encourage energy discharge whenever the demand is high on the grid. Existing solutions optimize only static energy measures or neglect larger cyber-physical interactions. In contrast, our approach reacts to real-time conditions on the route, as well as to the level of the battery, charging station availability, and changes in V2G tariffs. It enables cooperation among EV owners, traffic management units, grid operators, and charging service providers. Besides the positive impact on the grid with respect to the environmental perspective, this approach reduces pollution in cities and contributes to making the grid function smoothly for a longer period of time. The simulation results demonstrate the efficacy of the proposed hybrid solution, and therefore, it can be deployed in a real smart city scenario. The proposed approach is of particular relevance for cyber-physical systems, where timely decision-making and coordination at the system level play a key role in achieving sustainable urban mobility. The proposed method works well for diverse types of vehicles, as it shows significant route cost and V2G incentive savings compared to baseline methods. The source code used for implementing and evaluating the proposed EV-GREEN framework is publicly available at: <a href="https://github.com/kripa-sindhu-007/ev-routing-green-v2g">https://github.com/kripa-sindhu-007/ev-routing-green-v2g</a>.</p>

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EV-GREEN: electric vehicle routing with GreenZone prioritization and vehicle-to-grid incentive integration

  • 期刊论文

  • 发表日期：

    2026年2月2日

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  • Sanjay Moulik,
  • Kripa Sindhu,
  • Richa Sarma

摘要

With the rapid growth in EV adoption, eco-routing should not only reduce energy consumption but also follow the changing environmental rules and make it easier for the grid to connect. This work presents a hybrid approach which couples the Mixed Integer Linear Programming formulation with heuristics, such as Dijkstra’s algorithm, along with Ant Colony Optimization, that returns a practical and scalable solution for real-time EV routing. Our model features compliance with GreenZone, which automatically enforces environmental rules in various parts of the city, and Vehicle-to-Grid (V2G) incentives, which encourage energy discharge whenever the demand is high on the grid. Existing solutions optimize only static energy measures or neglect larger cyber-physical interactions. In contrast, our approach reacts to real-time conditions on the route, as well as to the level of the battery, charging station availability, and changes in V2G tariffs. It enables cooperation among EV owners, traffic management units, grid operators, and charging service providers. Besides the positive impact on the grid with respect to the environmental perspective, this approach reduces pollution in cities and contributes to making the grid function smoothly for a longer period of time. The simulation results demonstrate the efficacy of the proposed hybrid solution, and therefore, it can be deployed in a real smart city scenario. The proposed approach is of particular relevance for cyber-physical systems, where timely decision-making and coordination at the system level play a key role in achieving sustainable urban mobility. The proposed method works well for diverse types of vehicles, as it shows significant route cost and V2G incentive savings compared to baseline methods. The source code used for implementing and evaluating the proposed EV-GREEN framework is publicly available at: https://github.com/kripa-sindhu-007/ev-routing-green-v2g.