Study The Influences Of The Phasor Measurement Unit In Dynamic State Estimation Of Power System

Monitoring and control of the power system have become very important functions, for achieving a high reliability in the system, and for improving the Energy Management System (EMS) functions. State estimation represents one of the fundamental EMS application functions, which provides a better estimate for the system state. The Dynamic State Estimation (DSE) technique based on the previous state of the system has the ability to predict the state of the system at the next period of time (one step ahead).Recently, Phasor Measurement Unit (PMU) has become one of the EMS applications for real time monitoring at the control center.This thesis studies the impacts of synchronized Phasor Measurement in Dynamic State Estimation and Robust Dynamic State Estimation (RDSE) of a power system under various scenarios, such as normal operation, bad data detection and sudden load change.For applying the PMU in DSE and RDSE, we proposed the Decoupled Current Measurement (DCM) technique, where the current measurement which is measured by PMU is decoupled into active and reactive measurement and added to the WLS state estimation decoupled formula. With IEEE 30-bus, two PMUs is used. One PMU is fixed at the reference bus, and the other is conducted to every bus at each experiment. The voltage angle at a bus with PMU is the angular deviation of the voltage vector at that busbar with PMU, to the voltage vector at the reference busbar.For Dynamic State Estimation Weighted Least Square (WLS) Estimator is used, and for Robust Dynamic State Estimation, the M-estimators Quadratic Linear (QL) and Square Root (SR) estimators are used. To obtain the solution of M-estimation problem, Iteratively Re-weighted Least Squares Estimation (IRLS) method is applied. For calculating the parameters of the DSE model to get the predicted state of the system at next instant of time, a Holt’s double exponential smoothing technique is used. Furthermore, the Extended Kaman Filter (EKF) has been applied for filtering state to minimize the optimization function of the system. The dynamics of the system is simulated by increasing the injections at all the buses of the system. Constant power factor is assumed. The simulated measurements were obtained by adding a normally distributed error function with zero mean and standard deviation. The weights of the SCADA and PMU are calculated according to the measurements.The proposed method is applied to the standard data IEEE 14-bus and IEEE 30-bus test system as the case study. The values of the measurement set are taken from the load flow program. The results are carried out using MATLAB/M-File.The influences of PMUs in dynamic state estimation and robust dynamic state estimation have been introduced, where the average error in the estimated state is reduced, and the wriggles and fluctuations of the estimated voltage magnitude and angle are removed in all scenarios. When the measurements have a bad data, the system will lose its operating points, but the PMU can return the system operating point. Also highest improvement is made with the M-estimator during the bad data conditions. A comparative study on the behavior of the DSE and RDSE algorithm with and without PMU is explained. The impact of PMU locations on the accuracy of estimation has been made, where a single PMU is added to every bus at each experiment for all scenarios, as well as the effect of multi PMU in the system also has been addressed. Furthermore, the study made on an impact of the varying weights which have been given to the Phasor measurement unit.