EV-Scheduling

Greedy approach to assign EVs to EV charging stations and efficiently optimize pricing mechanism that benefits EV owners and charging station.

Project Overview: Electric Vehicle Charging Allocation

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.

Key Features:

• 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

Online Algorithm Efficiency:

• The algorithm is capable of handling and scheuling more than 1000 EVs with 91% efficiency.

How to Use:

1. Clone the repository.
2. Add the meta data related to the EVs in all_details.py file
3. Execute djkstra.py

Contributing:

Contributions and feedback are welcome. Please follow the guidelines outlined in CONTRIBUTING.md.

License:

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!