Hierarchical and decentralized optimization method based on multi-agent system for multiple AC/DC hybrid microgrids

Abstract

AC/DC hybrid microgrids (MGs) have been developed rapidly in recent years due to their efficient integration and management of large-scale distributed energy resources. How to achieve the optimal operation and coordinated control of AC/DC hybrid MGs has become crucial. A multi-agent system (MAS) based hierarchical and decentralized method for coordination operation of multiple AC/DC hybrid MGs is proposed. First, a structure of AC/DC hybrid MGs including wind turbines, photovoltaics, micro-hydro, and biogas generators is designed, which aims at reducing the power conversion loss. Second, a three-level MAS including distribution network (DN) level, MG level, and distributed generation (DG) level is presented. At the DG level, the DG agents obtain the optimal results from the MG agent. At the MG level, the independent optimization is implemented based on the mixed integer linear programming, and the consensus algorithm is utilized to realize the coordination of MG with adjacent MGs through the communication among MG agents when there is imbalance power. At the DN level, the DN agent performs power exchange with AC/DC hybrid MGs to balance the load demand when needed. Finally, the distributed energy management platform is developed by the Java Agent Development Framework platform to simulate the optimal operation of AC/DC hybrid MGs. The results show the rationality and availability of the proposed optimization method.