A Multi-Agent Flisr Model For Smart Grids

Resilient smart grids must guarantee fast service restoration during unexpected faults and natural disasters. This can be achieved by isolating the faults and forming microgrids around black-start generators. A self-sufficient microgrid (MG) can restore critical loads through optimal control of distributed energy resources (DERs) and remote switches by solving a mixed integer optimization problem. However, the implementation of the optimal solution may be infeasible, if the underlying transient response of the resulting power system is ignored. It is important to utilize transient results of electrical power flow to enforce dynamic stability after every restoration stage. In this research, transient analysis of the power system is used to quantify the disturbance experienced by the network elements including loads and generators. This feedback is used to limit the amount of load picked up in the next stage to maintain power system stability. Distributed multi-agent system (MAS) is implemented to solve challenges of information discovery, real-time task scheduling, communication network congestion and DER control during the restoration process. The importance of multi-agent coordination for power system healing from faults is analyzed by simulating network congestion of control and monitoring systems. The approach is validated over a modified IEEE-123 node test feeder and the results are presented to demonstrate the efficacy of the framework for multiple fault scenarios.