A Quantum-Assisted Agentic Distributed Artificial Intelligence Framework for Deadline-Bounded Orchestration of Hybrid Renewable Microgrids

The paper presents a quantum-assisted distributed artificial intelligence framework for the real-time orchestration of hybrid renewable microgrids, addressing combinatorial dispatch and coalition formation under strict deadlines. Utilizing Belief-Desire-Intention extended agents, the dispatch problem is framed as a quadratic unconstrained binary optimization (QUBO) problem and solved using a combination of quantum, quantum-inspired, and classical solvers, with the Quantum Approximate Optimization Algorithm (QAOA) achieving optimal dispatch in a 24-hour simulation. The framework demonstrates zero missed deadlines, a daily operational cost of 146.24 EUR with 97.83% renewable utilization, and highlights the importance of a belief-shaped storage valuation mechanism in optimizing costs, which underscores the potential for integrating quantum computing in energy management systems for enhanced efficiency.