XII SIMPÓSIO DE ESPECIALISTAS EM PLANEJAMENTO DA OPERAÇÃO E EXPANSÃO ELÉTRICA XII SYMPOSIUM OF SPECIALISTS IN ELECTRIC OPERATIONAL AND EXPANSION PLANNING Coherency Based Partitioning of a Power System for Intelligent Wide-Area Damping Control

A variety of factors are causing an increase of slow frequency oscillations in power systems. These oscillations reduce the stability of the system, limit power transfers, and can potentially lead to loss of synchronism and widespread blackouts. These oscillations typically involve variables from distant areas accross the system; therefore, conventional local damping controllers such as power system stabilizers might lack the information needed to provide effective damping. Controllers that utilize wide-area measurements can overcome these limitations , but the techniques for developing those controllers are still under development. The use of computational intelligence for wide-area damping control of power systems has been demonstrated in small power system simulations. It has been shown that it is possible to develop intelligent controllers that adapt online to improve their performance and approach optimality over time and that are capable of dealing with the non-linear, stochastic, and time varying nature of power systems. However, the scalability of these algorithms needs to be evaluated and possibly improved if they are to be implemented in realistically sized power systems. Typically, the development of intelligent controllers begins with identifying an accurate and differentiable model of the system to be controlled. However, studies have shown that as the size of the system being identified grows, so does the model and the computational complexity of the algorithms required to tune that model. The shear size of real world power systems makes straightforward implementation of such system identification approaches intractable. The work presented in this paper explores the issue of scalability of intelligent system identification algorithms using simulations of a large portion of the Brazilian Sistema Interligado Nacional. A recently developed concept named the virtual generator is utilized to simplify the online identification of an input/output data driven dynamical model of a large portion of the power system. This model is based on dynamical artificial neural networks and can be used for intelligent online adaptation of controller parameters. Only the system identification methodology is presented.