Tuning of PSS based on the System Model Diagnosis Using the PMU and Proposed Kalman Models

Disturbances and incidents with sudden light intensity cause oscillations in power networks. The main consequence of these disturbances is the low frequency oscillation (LFO). One way for eliminating these oscillations and damping them is to use power system stabilizer (PSS). These controllers must be adjusted in such a way that damping would reduce the interarea oscillations, i.e. the damping coefficient of the system would be increased. In this paper, according to the system model, the details including state variables, parameters, inputs and outputs, proposed methods such as EKF and UKF for estimating system state variables of synchronous generator are discussed. EKF is a local filter witch uses a linearization through Taylor development at the first order only, in the case of non-derivative non-linear function at a given estimate point, creating a singularity point and non-efficiency of the EKF; so, others estimators were introduced to solve these problems and the disadvantages of previous methods, as the Unscented Kalman Filter (UKF) is one of them. The implementation results have indicated the optimal performance of the proposed methods for estimating the system state variables.

Keywords:

power system stabilizer , PMU , synchronous machine , EKF , UKF