Abstract
This paper proposes a decentralized method for estimation of dynamic states of a power system. The method remains robust to time-synchronization errors and high noise levels in measurements. Robustness of the method has been achieved by incorporating internal angle in the dynamic model used for estimation and by decoupling the estimation process into two stages with continuous updation of measurement-noise variances. Additionally, the proposed estimation method does not need measurements obtained from phasor measurement units; instead, it just requires analog measurements of voltages and currents directly acquired from instrument transformers. This is achieved through statistical signal processing of analog voltages and currents to obtain their magnitudes and frequencies, followed by application of unscented Kalman filtering for nonlinear estimation. The robustness and feasibility of the method have been demonstrated on a benchmark power system model.
Highlights
INTRODUCTIONA disturbance in a power system (such as a fault) can initiate spontaneous oscillations in the power-flows in transmission lines
A disturbance in a power system can initiate spontaneous oscillations in the power-flows in transmission lines
In order to monitor and control such oscillations and related dynamics which cause instability, the operating state of the system needs to be estimated in real-time, with update rates which are in time scales of ten milliseconds or less, and this real-time estimation of operating state is known as dynamic state estimation (DSE) [3]-[12]
Summary
A disturbance in a power system (such as a fault) can initiate spontaneous oscillations in the power-flows in transmission lines. In order to estimate the rotor angle any DSE algorithm available in power system literature requires synchronized measurements obtained using PMUs [3]-[12]. The proposed method provides an algorithm for DSE which realizes the above idea This is done by modifying the estimation model to estimate a relative angle (which does not require synchronization) instead of rotor angle. The internal angle, rotor speed, voltages and fluxes can be estimated using the modified estimation model without requiring any synchronized measurements These dynamic states can be utilized for decentralized control of the generator [17], [18], [19], [20], [21].
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