# ev2gym
A realistic V2X Simulation Environment for large scale EV charging optimization!
<!-- Bullet points with all the benefits -->
## Features
* The simulator can be used to evaluate any type of algorithm to gain insights into its efficiency.
* The “gym environment” can readily support the development of RL algorithms.
* Uses only open-source data.
* Replays of simulations are saved and can be solved optimally using the Gurobi Solver.
* Easy to incorporate additional functionality for any use-case.
* Does not simulate the grid yet, but groups EV chargers at the level of the transformer/ parking lot, etc, so extra functionality can be easily added.
Focused on **realistic** parameters and **fully customizable**:
* Transformer models
* Max Current
* Charging Stations models
* Min and Max charge/discharge power/ Current
* Voltage and phases, AC or DC
* Charge and discharge efficiency
* List of connected transformers
* Electric Vehicles models
* Connected charging station and port
* Min and Max battery energy level
* Time of arrival and departure
* Energy at arrival/ desired energy at departure
* Min and Max current /power levels
* Constant-Current/ Constant-Voltage load-curve option
## Data sources
* The number and the topology of Transformers, Charging stations, and Electric Vehicles are parameterizable.
* Charging/ Discharging prices are based on historical day-ahead prices.
* EV spawn rate, time of stay, and energy required are based on realistic distributions ElaadNL,time, day, month and year.
* EV and Charger characteristics are based on real EVs and chargers existing in NL.
## File Structure
```bash
├── ev2gym
│ ├── __init__.py
│ ├── baselines
│ │ ├── __init__.py
│ │ ├── DDPG
│ │ ├── DT
│ │ ├── gurobi_models
```
## Citation
If you use this code in your research, please cite it using the following BibTeX entry:
```bibtex
@misc{ev2gym,
}
```
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
```
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"description": "# ev2gym\r\nA realistic V2X Simulation Environment for large scale EV charging optimization!\r\n\r\n<!-- Bullet points with all the benefits -->\r\n## Features\r\n\r\n* The simulator can be used to evaluate any type of algorithm to gain insights into its efficiency.\r\n* The \u201cgym environment\u201d can readily support the development of RL algorithms.\r\n* Uses only open-source data.\r\n* Replays of simulations are saved and can be solved optimally using the Gurobi Solver.\r\n* Easy to incorporate additional functionality for any use-case.\r\n* Does not simulate the grid yet, but groups EV chargers at the level of the transformer/ parking lot, etc, so extra functionality can be easily added.\r\n\r\n\r\nFocused on **realistic** parameters and **fully customizable**:\r\n* Transformer models\r\n * Max Current\r\n* Charging Stations models\r\n * Min and Max charge/discharge power/ Current\r\n * Voltage and phases, AC or DC\r\n * Charge and discharge efficiency\r\n * List of connected transformers\r\n* Electric Vehicles models\r\n * Connected charging station and port\r\n * Min and Max battery energy level\r\n * Time of arrival and departure\r\n * Energy at arrival/ desired energy at departure\r\n * Min and Max current /power levels\r\n * Constant-Current/ Constant-Voltage load-curve option \r\n\r\n\r\n## Data sources\r\n* The number and the topology of Transformers, Charging stations, and Electric Vehicles are parameterizable.\r\n* Charging/ Discharging prices are based on historical day-ahead prices.\r\n* EV spawn rate, time of stay, and energy required are based on realistic distributions ElaadNL,time, day, month and year.\r\n* EV and Charger characteristics are based on real EVs and chargers existing in NL.\r\n\r\n## File Structure\r\n```bash\r\n\u251c\u2500\u2500 ev2gym\r\n\u2502 \u251c\u2500\u2500 __init__.py\r\n\u2502 \u251c\u2500\u2500 baselines\r\n\u2502 \u2502 \u251c\u2500\u2500 __init__.py\r\n\u2502 \u2502 \u251c\u2500\u2500 DDPG\r\n\u2502 \u2502 \u251c\u2500\u2500 DT\r\n\u2502 \u2502 \u251c\u2500\u2500 gurobi_models\r\n\r\n```\r\n\r\n## Citation\r\nIf you use this code in your research, please cite it using the following BibTeX entry:\r\n```bibtex\r\n@misc{ev2gym,\r\n\r\n}\r\n```\r\n\r\n## License\r\nThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details\r\n```\r\n\r\n",
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