An intelligent training agent for power system restoration

Abstract

Total blackouts, though rare in a modern power system, could cause huge direct and indirect financial losses. Power system operators should be trained to restore their system from a total or a partial blackout condition in a relatively short period of time. A case-based reasoning approach has been utilized to develop a training simulator for the SaskPower network. System operators can use the simulator in an interactive manner to simulate a restoration process. The simulator can guide system operators through the steps of a restoration process and displays the outcome(s) of a restoration action in terms of system states. The interaction between the simulator and an operator has been achieved through an object-oriented graphical interface.