Fuzzy neural network based voltage stability evaluation of power systems with SVC

Voltage stability has become of major concern for the power utilities. In this paper, multi input, single output fuzzy neural network is developed for voltage stability evaluation of the power systems with SVC by calculating the loadability margin. Uncertainties of real and reactive loads, real and reactive generations, bus voltages and SVC parameters are taken into account. All ac limits are considered. In the first stage, Kohonen self-organizing map is developed to cluster the real and reactive loads at all the buses to reduce the input features, thus limiting the size of the network and reducing computational burden. In the second stage, combination of different non-linear membership functions is proposed to transform the input variables into fuzzy domains. Then a three-layered feed forward neural network with fuzzy input variables is developed to evaluate the loadability margin. The proposed methodology is applied to IEEE-30 bus and IEEE-118 bus systems.