The EV2Gym simulator is designed to facilitate the development and evaluation of smart charging algorithms for electric vehicles (EVs). It provides a comprehensive and flexible simulation environment that incorporates detailed models of EVs, charging stations, and power transformers, as well as realistic EV behavior data.
The key features of EV2Gym include:
Flexible simulation environment: EV2Gym allows users to customize various simulation parameters, such as the charging topology, EV characteristics, and power network constraints, enabling the exploration of diverse smart charging scenarios.
Realistic modeling: The simulator is populated with validated models of EVs, charging stations, and power transformers, ensuring the simulation accurately reflects real-world conditions. This includes detailed battery degradation models and realistic EV behavior data based on empirical studies.
Support for various algorithms: EV2Gym supports the development and benchmarking of a wide range of smart charging algorithms, including rule-based heuristics, mathematical programming, model predictive control, and reinforcement learning. The simulator is integrated with the Gym API, streamlining the assessment of reinforcement learning algorithms.
Comprehensive evaluation: The simulator provides a suite of evaluation metrics, such as energy charged, user satisfaction, tracking performance, and transformer overloads, enabling a thorough assessment of the strengths and weaknesses of different charging strategies.
The paper showcases two case studies to demonstrate the capabilities of EV2Gym: power setpoint tracking and V2G profit maximization. The results highlight the performance of various baseline algorithms, including heuristics, mathematical programming, and reinforcement learning, in addressing these smart charging challenges.
By offering a unified and standardized platform, EV2Gym aims to provide researchers and practitioners with a robust environment for advancing and assessing smart charging algorithms, ultimately supporting the integration of EVs into the power grid.
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arxiv.org
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