Improved self-tuning control for power system stability

A simplified multivariable self-tuning control scheme for improved system stability through excitation control is presented. The controller possesses the properties of a multivariable self-tuner with the simplicity of a single-variable one due to the use of an artificial output signal constructed by a weighted sum of the real output signals of a generator. A single-input-single output autoregressive moving average model is used to represent the individual generating unit dynamics. Both the generalized minimum variance technique and the linear quadratic Gaussian technique are investigated for the controller synthesis. Extensive simulations are carried out on the New England ten-machine test system. The results demonstrate that the proposed self-tuning control provides effective damping characteristics and behaves much better than the conventional power system stabilizer