Greedy approach to assign EVs to EV charging stations and efficiently optimize pricing mechanism that benefits EV owners and charging station.
This repository addresses the Electric Vehicle (EV) charging allocation problem by providing both offline and online solutions. In this project, EV users are treated as self-interested agents seeking to maximize profit while minimizing schedule impact.
- Use of djkstra's algorithm to schedule EVs and pricing mechanisms for EV stations.
- Formulation of the optimal EV-to-charging station allocation as a Mixed Integer Programming (MIP) problem.
- Development of a solution that incrementally utilizes the MIP-based greedy algorithm to efficiently handle EV charging stations and pricing.
- Takes distance to station, fuel capacity, time, average EV speed, availability of stations, time taken to charge in consideration while scheduling EVs at their respective stations
- The algorithm is capable of handling and scheuling more than 1000 EVs with 91% efficiency.
- Clone the repository.
- Add the meta data related to the EVs in all_details.py file
- Execute djkstra.py
Contributions and feedback are welcome. Please follow the guidelines outlined in CONTRIBUTING.md.
This project is licensed under the MIT License.
Feel free to explore the codebase and contribute to the advancement of Electric Vehicle charging allocation solutions!