2 research outputs found
Dynamic State Estimation for Multi-Machine Power System by Unscented Kalman Filter with Enhanced Numerical Stability
In this paper, in order to enhance the numerical stability of the unscented
Kalman filter (UKF) used for power system dynamic state estimation, a new UKF
with guaranteed positive semidifinite estimation error covariance (UKF-GPS) is
proposed and compared with five existing approaches, including UKF-schol,
UKF-, UKF-modified, UKF-, and the square-root unscented
Kalman filter (SR-UKF). These methods and the extended Kalman filter (EKF) are
tested by performing dynamic state estimation on WSCC 3-machine 9-bus system
and NPCC 48-machine 140-bus system. For WSCC system, all methods obtain good
estimates. However, for NPCC system, both EKF and the classic UKF fail. It is
found that UKF-schol, UKF-, and UKF- do not work well in some
estimations while UKF-GPS works well in most cases. UKF-modified and SR-UKF can
always work well, indicating their better scalability mainly due to the
enhanced numerical stability.Comment: accepted by IEEE Transactions on Smart Gri
Risk Mitigation for Dynamic State Estimation Against Cyber Attacks and Unknown Inputs
Phasor measurement units (PMUs) can be effectively utilized for the
monitoring and control of the power grid. As the cyber-world becomes
increasingly embedded into power grids, the risks of this inevitable evolution
become serious. In this paper, we present a risk mitigation strategy, based on
dynamic state estimation, to eliminate threat levels from the grid's unknown
inputs and potential cyber-attacks. The strategy requires (a) the potentially
incomplete knowledge of power system models and parameters and (b) real-time
PMU measurements.
First, we utilize a dynamic state estimator for higher order depictions of
power system dynamics for simultaneous state and unknown inputs estimation.
Second, estimates of cyber-attacks are obtained through an attack detection
algorithm. Third, the estimation and detection components are seamlessly
utilized in an optimization framework to determine the most impacted PMU
measurements. Finally, a risk mitigation strategy is proposed to guarantee the
elimination of threats from attacks, ensuring the observability of the power
system through available, safe measurements. Case studies are included to
validate the proposed approach. Insightful suggestions, extensions, and open
problems are also posed