Application of Dynamic State and Parameter Estimation Techniques on Real-World Data

The objective of this paper is to apply two dynamic state and parameter estimation techniques to real-world data. Dynamic state and parameter estimation can estimate equivalent generator internal voltages and rotor angles (dynamic states) during electromechanical dynamics. In addition, parameters such as the transient reactances and inertia can be estimated. A set of real world data recorded by Eastern Interconnection Phasor Measurement Units (PMU) regarding a generator trip event is analyzed in this paper. An estimation algorithm developed by Chow was applied to estimate the states and parameters of a transfer path. An alternative estimation method based on the classic generator model and swing equation is presented in this paper and applied to the real world PMU data with the aid of digital filtering technology. Challenges in real-world data applications are identified in this paper.