Learning coordinated control of synchronous machines in multi-machine power systems

This paper is concerned with application of interconnected learning automata to learning coordinated control (LCC) of synchronous machines in multi-machine power systems. The interconnected learning automata with variable subsets of control actions are used to optimize parameters of distributed local controllers to improve power system stability based on an integrated performance index. Results obtained from simulation studies are presented to show a potential of applications of the method to power system control and operation