MULTI-AGENT AI ORCHESTRATION OF GRID-FORMING VIRTUAL POWER PLANTS FOR BIDIRECTIONAL EV ENERGY NETWORKS

Abstract

This manuscript proposes a novel AI-based framework that combines Virtual Power Plants (VPPs) with a bidirectional Electric Vehicle (EV) energy network, along with decentralized Multi-Agent System (MAS) orchestration for the future of renewable energy-dominated smart grids. The study addresses important issues of intermittency, low-inertia grid operation, integration of large numbers of EVs, and distributed energy coordination. A holistic Cyber-Physical Smart Grid Architecture is proposed that integrates Renewable Energy Systems, Battery Energy Storage Systems (BESS), Vehicle-to-Grid (V2G) technology, decentralized grid-forming inverter control, and reinforcement learning-based Artificial Intelligence orchestration in a decentralized operational environment.  The framework uses autonomous intelligent agents to coordinate renewable generation and EV charging/discharging schedules, storage dispatch, and grid stabilization in real time. The simulation-based evaluation was performed under various operational conditions, including renewable variability stress, high EV penetration, and bidirectional V2G operation. Results show significant improvements in renewable energy use, operational Efficiency, voltage and frequency stability, peak demand reduction, and carbon emissions reduction over traditional central grid systems. The design framework resulted in a renewable utilization rate of>90%, reduced operational costs by up to 29%, and increased grid stability through adaptive grid-forming control mechanisms. In addition, coordinated EV fleets were effectively used as distributed mobile energy storage resources for peak shaving, ancillary services, and balancing renewable energy. The results validate the potential of AI-driven grid-forming VPPs as a scalable, resilient, and economically viable future option for low-carbon smart energy systems with significant renewable energy and EV uptake. The proposed framework offers valuable technical, operational, and policy lessons for utility operators, smart grid planners, and policymakers to support sustainable, intelligent energy transition strategies.