Title: An intelligent neuro-fuzzy logic controller for induction generator based wind generation to improve power system stability
Authors: N. Albert Singh, K.A. Muraleedharan, K. Gomathy
Addresses: Department of Electrical and Electronics Engineering, College of Engineering, Thiruvananthapuram, Kerala, India. ' Department of Electrical and Electronics Engineering, Noorul Islam College of Engineering, Kumaracoil, TN, India. ' Department of Electrical and Electronics Engineering, Noorul Islam College of Engineering, Kumaracoil, TN, India
Abstract: Power systems are non-linear and they are often subjected to random disturbances. This paper deals with the application of the intelligent neuro-fuzzy technique to the design of the robust power system stabiliser for power system oscillation damping enhancement in a wind turbine based power system network. The stabilising signal is computed in real time using suitable fuzzy membership functions depending upon the state of the generator on the speed-acceleration phase plane. These input signals are first characterised by a set of linguistic variables using fuzzy set notations. The fuzzy relation matrix, which gives the relationship between stabiliser inputs and stabiliser output, allows a set of fuzzy logic operations that are performed on stabiliser inputs to obtain the desired stabiliser output. The performance of the proposed controller is analysed in a single induction machine-infinite bus power system data subjected to various dynamic and transient disturbances. The proposed intelligent neuro-fuzzy control scheme exhibits a superior damping performance in comparison to the conventional controllers. Its simple architecture reduces the computational burden, thereby making it attractive for real-time implementation.
Keywords: induction machines; power system stabiliser; PSS; neuro-fuzzy controllers; fuzzy logic; dynamic stability; intelligent control; fuzzy control; induction generators; wind power; wind energy; oscillation damping; wind turbines.
International Journal of Modelling, Identification and Control, 2009 Vol.6 No.3, pp.188 - 195
Published online: 05 Apr 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article