Project Grant 2431553

This federal Project Grant award, with a total funding amount of $199,999, was provided by the National Science Foundation (NSF) under its Computer and Information Science and Engineering (CFDA 47.070) program. The award supports the development of an "Interaction-Aware Management Framework to Improve the Efficiency and Sustainability of Electric Transportation and Power Systems." The key products and services to be delivered through this 3-year project (01/01/2025 - 12/31/2027) include:

1. A robust multi-agent reinforcement learning control model for power systems to dynamically adjust electricity prices and charging-power rates, integrating a human charging-behavior model.
2. A mean-field game-based control method for large-scale electric vehicles to autonomously select charging stations with awareness of potential charging rates.
3. An incentive-driven collaboration mechanism to facilitate socially optimal actions between the power grid and electric vehicle operators using graph-based multi-agent reinforcement learning and Shapley value.

The project aims to develop a collaborative framework that considers the interdependencies between the electric transportation and power grid systems, with the goal of enhancing efficiency and sustainability for both stakeholders. The research will leverage real-world data to validate the proposed approach and contribute to the development of a more sustainable transportation and power infrastructure.