An intelligent coordinated design for excitation and speed control of synchronous generators based on supervisory loops

This paper presents a co-ordinated scheme for excitation control of synchronous generator in a multi-machine environment based on intelligent supervisory loops. The main proposition is to provide optimal control of power with stable voltage profile at the generator terminals using two controllers. To this end, an implicit model adaptive controller (IMAC) in parallel with a radial basis function neural network (RBFNN) neuro-controller is designed to work in a hybrid coordinated control architecture. RBFNN based neuro-controller constantly monitors systems dynamics when the adaptive controller centrally controls the voltage while the system undergoes various trajectories. This is the basic idea of system supervision. The advantage of the proposed approach is that, the architecture is system centric in nature. This means, the hybrid controller constantly monitor system variations and augment the central controller at each time instant. Simulation results performed on multi-machine power system shows that the proposed architecture provides better performance as opposed to adaptive control counterpart acting alone.