The National Science Foundation (NSF) awarded a $199,806 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Tennessee at Chattanooga (UTC). The grant supports a collaborative research project to develop an interaction-aware management framework to improve the efficiency and sustainability of electric transportation and power systems.
Specifically, the project will focus on three key technical components: (1) a multi-agent reinforcement learning control model for power systems to dynamically adjust electricity prices and charging 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; and (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 benefit both electric vehicle drivers and power grid operators by reducing costs and improving sustainability. No subawards are planned under this grant, which has an award date of January 1, 2025 and an ultimate completion date of December 31, 2027.
Generated 3/4/25, 4:11 AM