On enhancing power systems PMU based data analysis and condition monitoring

This paper investigates two primary algorithms for estimating phasor information used in Phasor Measurement Units (PMU). Power systems behavior and responses are more complicated nowadays and subsequently their supervision, control and protection are more critical and challenging. Various supervisory systems should be employed for protective and control purposes. All these supervisory systems rely on PMU technology with data stamps synchronized by Global Positioning System (GPS). A PMU´s accuracy and performance in phasor estimation during different power system working conditions to track the actual signal has an impact on the system state estimation and subsequently in the ability in fault and disturbances diagnosis. Many algorithms are proposed recently to be employed for phasor estimation in PMU devices. It is showed that Discrete Fourier based algorithms are the best methods in digital world to implement in PMU devices. Such methods are Discrete Fourier Transform (DFT) and Smart DFT that are compared and investigated in this article. Simplicity and low computational burden of these methods resulted in attracting many literatures to employ them in phasor estimation algorithms. However, their accuracy in off-nominal frequency and performance during different working condition are controversial which are studied in this article. Extensive simulations are performed in MATLAB Simulink to study and compare DFT and SDFT algorithms under different system disturbances.