IoT-based stochastic EMS using multi-agent system for coordination of grid-connected multi-microgrids

Abstract

A multi-microgrid system – containing various complementary energy sources – must coordinate the power flow among microgrids and the utility grid for stability and reliability enhancement, and also should obtain optimum energy management. Multi-agent-based optimization techniques are ideal for the management of interconnected microgrids, due to their decentralized nature and multifactorial approach in the decision-making process. In this paper, an optimization model is proposed for interconnected multi microgrids which considers the overall cost of the system. For optimum system operation, the hierarchical energy management system is utilized based on the multi-agent systems (MAS) theory. Each element of the system is considered an independent agent connected to others through the internet of things (IoT) platform. A key benefit of such a structure is its capability to be divided into numerous levels. Moreover, the communication burden of the system is reduced with different management layers.In this paper, efficient operation and management tools including the regulation power (for dispatchable DGs), independent DGs, and power exchange with the utility and adjacent microgrids are utilized for optimum operation. To obtain more realistic modeling, the uncertainty of renewables and demand is taken into account using decomposition-based modeling, which reduces the computational burden as well. Furthermore, demand response programs are also considered. Finally, a rule-based real-time corrective algorithm is presented to eliminate the mismatched power. The simulation and implementation results demonstrate the efficacy of the proposed MAS-based optimization model in decreasing the operational costs of the multi-microgrid system with minimal communication and computational burden.