Multi-Agent Based Distributed Computing for Photovoltaic Systems Economic Dispatch Using Modified Exact Diffusion Strategy

With the rapid deployment of photovoltaic (PV) systems and the transition toward decentralized energy infrastructures, traditional centralized economic dispatch methods are increasingly challenged by scalability bottlenecks, communication overhead, and vulnerability to single-point failures. These issues are further exacerbated by the dynamic and distributed nature of PV-based microgrids, where plug-and-play devices, intermittent generation, and privacy constraints demand localized decision-making and coordination. To address these challenges, this paper proposes a fully distributed economic dispatch framework based on a multi-agent system and a Modified Exact Diffusion Algorithm (MEDA). The framework models PV units, battery storage, flexible loads, and grid interfaces as autonomous agents that interact through peer-to-peer communication, collaboratively achieving global optimality without centralized supervision. A SOC-aware battery cost model, dynamic electricity pricing, and quadratic line loss modeling are integrated to enhance practical realism. Simulation results on a modified IEEE 33-bus microgrid show that the proposed approach significantly outperforms centralized and existing distributed methods in terms of cost reduction, convergence speed, resilience to communication failures, and adaptability to agent dynamics.