Optimal energy management and control aspects of distributed microgrid using multi-agent systems

Abstract

Abstract At present, energy generation is evolving into a smart distribution system that assimilates several green energy resources at a distributed level assuring to generate clean energy without producing any harmful gases, to have consistent operational procedures, and to improve energy management and supervision arrangements. The renewable energy resources (RERs) are considered the best suitable approach to generate electrical power at the distributed level since they offer benefits to the power systems as well as to the environment. Therefore, this paper presents the recent research work on multi-agents-based coordination for the optimal management of electrical energy and its proper controlling at the distributed level exploiting RERs. The multi-agent system (MAS) technique is discussed in detail along with the storage and protection system that solve the microgrid (MG) control and management issues efficiently. Several platforms to develop the MASs are addressed including those that empower the MG to control its configuration, generation capacity, power flow, and fault control. There are several controlling approaches used on distributed generation systems to efficiently operate the whole system comprising of centralized, distributed, and hybrid control techniques are discussed. A comprehensive description about different optimization techniques applied to the energy system have also been highlighted, particularly to identify the most common and effective technique that is currently applied to hybrid energy system at the distributed level. The analysis shows that the particle swarm optimization (PSO) is the most useful and effective technique that has been applied since it can minimize the interruption costs, maximize the reliability, and optimize the operational schedules at the MG level.