This chapter investigates game-theoretic operational strategies for plug-in electric vehicles (PEVs) providing vehicle-to-grid (V2G) services in active power distribution systems, considering dynamic pricing and the integration of distributed energy resources. Three distinct game models are developed and analyzed. First, a non-cooperative game model is established where multiple EV users independently optimize their charging/discheduling schedules to minimize individual costs, leading to a Nash equilibrium. Second, a cooperative game model is formulated where EVs form a coalition through an aggregator to minimize the total charging cost, demonstrating superior economic benefits compared to the non-cooperative approach. Third, a Stackelberg master–slave game is proposed modeling the hierarchical interaction between the grid operator (leader) utilizing energy storage for peak shaving and EV aggregators (followers). The operator sets dynamic prices to minimize peak-shaving costs, while aggregators optimize EV schedules accordingly. The model is solved using Karush–Kuhn–Tucker (KKT) conditions. Numerical simulations based on a parking lot scenario with 150 EVs validate the proposed strategies. Results show that cooperative gaming reduces total EV charging costs compared to the scenarios with uncontrolled V2G, while the Stackelberg equilibrium achieves a win–win outcome, reducing both EV charging costs and grid operator storage operating costs, effectively flattening the load curve and improving renewable energy utilization.