A multiagent design for self-healing in electric power distribution systems

The out-of-service area after fault should berestored by changing the distribution system configuration by means of switching actions on the feeders. This paper proposes an agent-based approach for service restoration in smart distribution systems with distributed generations (DG). The proposed multi agent has four different types of agents: feeder agents, zone agents, switch agents and DG agents. The agents can communicate and cooperate with each other in order to supply services to out-of-service customers. An artificial neural network has been considered within DG agent to predict the DG generation. The restoration plan is built based on local data considering system conditions, operational constraints and fault location. Different loading conditions have been considered under different scenarios and the result of proposed multi agent approach for each scenario with and without DG have been compared. Simulation results show the efficiency of proposed agent architecture.