Hardware design for MAS power distribution restoration using neural networks

A state of the art power distribution systems is to demand a more accurate response. A multi-agent system design for power distribution has been developed using the change of current methodology to detect and locate any type of faults. This study also examines the role of Universal Asynchronous Receiver Transmitter (UART) buffer circuits in the laboratory experiment demonstration of the multi-agent system design. A recloser has been developed and improved for more sensitivity and faster response to detecting a fault where ever it occurs and lead the process of isolating and re-configuration. A Radial Basis Neural Network (RBNN) is designated at the feeder agent to implement the reconfiguration by analyzing the impedance and current values for each zone. The appropriate decision for the optimal reconfiguration case is a vector of activation signals associated with each switch to restore the power to the un-faulted zones of distribution feeder.