Abstract
Large interconnected power systems are usually subjected to natural oscillation (NO) and forced oscillation (FO). NO occurs due to system transient response and is characterized by several oscillation modes, while FO occurs due to external perturbations driving generation sources. Compared to NO, FO is considered a more severe threat to the safe and reliable operation of power systems. Therefore, it is important to locate the source of FO so corrective actions can be taken to ensure stable power system operation. In this paper, a novel approach based on two-step signal processing is proposed to characterize FO in terms of its frequency components, duration, nature, and the location of the source. Data recorded by the Phasor Measurement Units (PMUs) in a Wide Area Monitoring System (WAMS) is utilized for analysis. As PMU data usually contains white noise and appears as multi-frequency oscillatory signal, the first step is to de-noise the raw PMU data by decomposing it into a series of intrinsic mode functions (IMF) using Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) technique. The most appropriate IMF containing the vital information is selected using the correlation technique. The second step involves various signal processing and statistical analysis tools such as segmented Power Spectrum Density (PSD), excess kurtosis, cross PSD etc. to achieve the desired objectives. The analysis performed on the simulated two-area four-machine system, reduced WECC-179 bus 29 machine system, and the real-time power system PMU data set from ISO New England, demonstrates the accuracy of the proposed method. The proposed approach is independent of complex network topologies and their characteristics, and is also robust against measurement noise usually contained in PMU data.
Highlights
With the rapid deployment of Phasor Measurement Units (PMUs) in modern power systems, both natural oscillation (NO) and forced oscillation (FO) are commonly observed
The first stage involves de-noising of raw PMU data using mode decomposition based on ICEEMDAN algorithm that transforms the signal into a series of intrinsic mode functions (IMF) known as decomposed modes after preprocessing (DMAPs)
6 Conclusion This paper has proposed a systematic two-step approach to locate the source of FO in power system using PMU measurements
Summary
With the rapid deployment of Phasor Measurement Units (PMUs) in modern power systems, both natural oscillation (NO) and forced oscillation (FO) are commonly observed. Reference [20] discusses a novel method based on the development of frequency response function for a particular generator set using PMU data and detection of oscillation source depends on the difference between the actual and estimated current spectra. An equivalent power system model in the frequency domain considering noisy PMU data and uncertain generator parameters is developed in [21] and a numerical procedure based on Bayesian framework is adopted to identify the source of FO. Reference [22] proposes a double stage mode decomposition technique, while [23] discusses an unknown input observer (UIO) based method to locate the source of FO. The comparison between the model responses generated by UIOs and recorded responses establishes a strong relationship between the residual and oscillation sources It can identify prime mover/excitation system of the generator set that gives rise to FO.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
