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Although it is well known that Fourier analysis is in reality only accurately applicable to steady state waveforms, it is a widely used tool to study and monitor time-varying signals, which are commonplace in electrical power systems. The disadvantages of Fourier analysis, such as frequency spillover or problems due to sampling (data window) truncation can often be minimized by various windowing techniques, but they nevertheless exist. This paper demonstrates that it is possible to track and visualize amplitude and time-varying power systems harmonics, without frequency spillover caused by time-frequency techniques. This new tool allows for a clear visualization of timevarying harmonics which can lead to better ways to track harmonic distortion and understand time-dependent power quality parameters. It also has the potential to assist with control and protection applications.

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a b s t r a c tAlthough it is well known that Fourier analysis is in reality only accurately applicable to steady state waveforms, it is a widely used tool to study and monitor time-varying signals, such as are commonplace in electrical power systems. The disadvantages of Fourier analysis, such as frequency spillover or problems due to sampling (data window) truncation can often be minimized by various windowing techniques, but they nevertheless exist. This paper demonstrates that it is possible to track and visualize amplitude and time-varying power systems harmonics, without frequency spillover caused by time-frequency techniques. This new tool allows for a clear visualization of time-varying harmonics, which can lead to better ways to track harmonic distortion and understand time-dependent power quality parameters. It also has the potential to assist with control, protection and power quality applications.

High impedance faults (HIFs) present great difficulty of identification and location in distribution networks (DN) due to their characteristics of low current magnitude. Advances in smart grids and distribution automation allow the detection of disturbances that were previously unnoticeable in DN. This work aims to present a new method for detection and location of HIFs from smart meters placed at strategic points in the feeder, using a voltage unbalance based approach. The methodology was evaluated through simulations in MATLAB / Simulink, focusing on the detection of high impedance series faults. The results showed that the algorithm effectively identifies broken conductors, with or without ground faults, located either at the load or source side. Once technical and economic feasibility is proven, these methods can assist energy distribution utilities in restoring the normal operating conditions of the distribution network.

The trend towards the implementation of Smart Grids results in a higher complexity of power signals and their voltage quality implication. Thus the need for more advanced signal processing techniques is required. A number of techniques have been recently developed and proposed in order to analyze the new environment and phenomena. Among these techniques this paper discusses different time-frequency methods used in power systems disturbance analysis. Filter Banks, Sliding-Window Recursive-DFT (SWR-DFT) and Wavelet Packet Transform (WPT) are compared. The methods are discussed based on their advantages and disadvantages. Signals with harmonic and inter-harmonics distortion are used in order to compare performance of the methods related to fundamental frequency variations, fast magnitude oscillations and interharmonics. The results presented in this work should assist quality expert to select the appropriate method according to application.

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