A New Fuzzy-neural STATCOM Controller for Transient Stability Improvement in
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Abstract
In this paper a neuro-fuzzy controller is proposed to enhance transient stability and increase critical clearing time (CCT) in the static synchronous compensator (STATCOM). For achieving this idea, first the controller is designed based on the Lyapunov energy function. In order to avoid complexity of computation and overcome system uncertainty a neuro-fuzzy controller is proposed. In this controller, neural network determines the system rules and membership functions. In order to design a neural network and its training patterns, the energy function controller is used under various system conditions. This controller has learning abilities due to its robust fuzzy controller and neural network. Simulation results on the single-machine infinite-bus (SMIB) show that the neuro-fuzzy controller damps electromechanical oscillations and increases the critical clearing time.
