Architectural Invariants for Designing Multi-Agent Energy Management Systems in Microgrids

Abstract

The growing integration of distributed renewable energy sources into microgrids increases the complexity of energy management systems (EMS) due to resource variability, demand uncertainty, and energy asset heterogeneity. Traditional EMS, which are mostly centralized and deterministic, have significant limitations in terms of flexibility, resilience, and scalability in these variable environments. This paper aims to design an intelligent hierarchical EMS architecture based on an intelligent multi-agent technique. It is an architecture based on intelligent agent ensuring distributed coordination and global orchestration of energy decisions in microgrids. The proposed architecture is centered on an explicit separation between agent-to-agent (A2A) coordination, dedicated to negotiation, cooperation, and event management mechanisms. The standardized access to data and services is provided by the Model Context Protocol (MCP), used for the integration of supervision, forecasting, and optimization tools. Each subsystem of the microgrid (generation, storage, loads, and network interface) is represented by a specialized autonomous agent, while a supervisor agent ensures the overall consistency of decisions. The study focuses on a detailed description of the proposed architecture and interaction flows, of the EMS. Also, properties of the proposed architecture are qualitatively examined in terms of modularity, robustness, and extensibility. Prospects for quantitative validation and experimental deployment are identified as future work.