Abstract
This paper presents an application of probabilistic theory to the selection of locations and parameters. The aim is to enhance the damping of multiple electromechanical modes in a multimachine system over a large and prespecified set of operating conditions. Conventional eigenvalue analysis is extended to the probabilistic environment in which the statistical nature of eigenvalues corresponding to different operating conditions is described by their expectations and variances. Probabilistic sensitivity indices to facilitate robust PSS site selection and a probabilistic eigenvalue-based objective function for coordinated synthesis of parameters are then proposed. The quasi-Newton technique of nonlinear programming is used to solve the objective function and its convergence properties are discussed and compared with the conventional steepest descent approach. The effectiveness of the proposed stabilizers, with a classical lead/lag structure, is demonstrated on an eight-machine system.
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