Market-Incentivized Aggregation Modeling and Capacity from Distributed Electric Vehicles with AI-Enabled Evolutionary Peer-to-Peer Game

The aggregation of distributed electric vehicles (EVs) initiates a promising avenue for constructing a virtual energy storage system within the distribution electricity market. To unlock the latent storage capacity inside the large-scale electrified transportation system and reduce redundant investment in the traditional power plant, a market-incentivized aggregation framework is developed to integrate those inherently stochastic energy resources. To address the substantial computational complexity posed by large EV populations and align with their distributed operational nature, an artificial intelligence (AI)-enabled evolutionary peer-to-peer game with price-making and probabilistic policy is deployed to emulate market dynamics effectively. The proposed strategy minimizes overall energy demand and shifts peak loads, thereby enhancing system flexibility and enabling the formation of an aggregation-based capacity for grid management. In response to the varying energy dynamics across communities, the framework embeds a price-making scheme to reinforce economic incentives for participation. Through continuous, distributed dispatch enabled by the probabilistic policies, fine-grained management over large-scale energy integration is achieved. Experimental evaluations using real-world distribution system data validate the effectiveness of the proposed framework in stimulating EV participation and establishing a robust, aggregated energy storage system.