Synchrophasor Assisted Efficient Fault Location Techniques In An Active Distribution Network

Reliability of an electrical system can be improved by an efficient fault location identification for the fast repair and remedial actions. This scenario changes when there are large penetrations of distributed generation (DG) which makes the distribution system an active distribution system. An efficient use of synchrophasors in the distribution network is studied with bidirectional power flow, harmonics and low angle difference consideration which are not prevalent in a transmission network. A synchrophasor estimation algorithm for the P class PMU is developed and applied to identify efficient fault location. A fault location technique using two ended synchronized measurement is derived from the principle of transmission line settings to work in a distribution network which is independent of line parameters. The distribution systems have less line length, harmonics and different sized line conductors, which affects the sensitivity of the synchronized measurements, Total Vector Error (TVE) and threshold for angular separation between different points in the network. A new signal processing method based on Discrete Fourier Transform (DFT) is utilized to work in a distribution network as specified in IEEE C37.118 (2011) standard for synchrophasor. A specific P and M classes of synchrophasor measurements are defined in the standard. A tradeoff between fast acting P class and detailed measurement M class is sought to work specifically in the distribution system settings which is subjected to large amount of penetrations from the renewable energy

Signature analysis of mechanical watch movements.

Su, Shuang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.Includes bibliographical references (leaves 100-106).Abstracts in English and Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Objective --- p.2Chapter 1.3 --- Methodology --- p.3Chapter Chapter 2 --- Literature Survey --- p.5Chapter 2.1 --- The Escapement --- p.5Chapter 2.2 --- Signature Analysis of Mechanical Watches -- Traditional Methods and Existing Systems --- p.10Chapter 2.2.1 --- Estimating Rate Deviation --- p.10Chapter 2.2.2 --- Measuring Beat Error --- p.11Chapter 2.2.3 --- Error Detection with a Graphical Diagram --- p.12Chapter 2.2.4 --- Analyzing Watch Ticks --- p.13Chapter 2.3 --- Time-Frequency Distributions and Reassignment --- p.14Chapter 2.3.1 --- Time-Frequency Distributions --- p.14Chapter 2.3.2 --- Reassignment Method --- p.18Chapter 2.4 --- Finite Element Analysis --- p.19Chapter Chapter 3 --- Signature Analysis of Mechanical Watch Movement --- p.21Chapter 3.1 --- Time-Domain Analysis: Endpoint Detection --- p.21Chapter 3.2 --- Time-Domain Analysis: Error Detection with a Graphical Chart --- p.27Chapter 3.3 --- Analyzing Ticks: from Time-Domain Analysis to Time-Frequency Analysis --- p.31Chapter Chapter 4 --- Reassigned Time-Frequency Distributions --- p.34Chapter 4.1 --- Spectrogram --- p.34Chapter 4.2 --- Morlet Scalogram --- p.35Chapter 4.3 --- Smoothed Pseudo-Wigner-Ville Distribution --- p.36Chapter 4.4 --- Reassignment principle --- p.37Chapter 4.5 --- Reassigned Spectrogram (RSP) --- p.39Chapter 4.6 --- Reassigned Morlet Scalogram --- p.40Chapter 4.7 --- Reassigned SPWV --- p.40Chapter 4.8 --- Performance Evaluation of Time-frequency Distributions --- p.41Chapter Chapter 5 --- Modal analysis and simulation results --- p.47Chapter 5.1 --- FEA Eigensystems --- p.47Chapter 5.2 --- Modal Analysis in ANSYS --- p.48Chapter 5.3 --- Transient Dynamic Analysis of Watch Parts in ANSYS --- p.50Chapter Chapter 6 --- Fault Detection Examples --- p.60Chapter 6.1 --- Example I --- p.60Chapter 6.2 --- Example II --- p.64Chapter Chapter 7 --- System Development --- p.69Chapter Chapter 8 --- Conclusions --- p.74Appendix I --- p.77Chapter 1. --- GUI Layout of the CUHK-IPE Watch Signature Analyzer (WTimer.fig) : --- p.77Chapter 2. --- Main Function of CUHK-IPE Watch Signature Analyzer (WTimer.m): --- p.78Chapter 3. --- Other Functions Called by the Main Function: --- p.85Chapter 3.1 --- Function for Split Signal up into (Overlapping) Frames (enframe.m):…… --- p.86Chapter 3.2 --- Function for Detecting BPH of the Watch (bph´ؤdetection.m): --- p.86Chapter 3.3 --- Function for Calculation the Rate Deviation and Beat Error of the Watch (rate4_6.m): --- p.89Chapter 3.4 --- Function for Calculating the RSP of the Signal (tfrrsp.m): --- p.95Chapter 3.5 --- Window Generation Function (tftb_window.m): --- p.97References --- p.10

Instantaneous Frequency Estimation Using Level-Crossing Information

In this paper, we discuss the problem of instantaneous frequency (IF) estimation of phase signals using their level-crossing (LC) instant information. We cast the problem to that of interpolating the instantaneous phase (IP), and hence finding the IF, from samples obtained at the level-crossing instants of the phase signal. These are inherently irregularly spaced and the problem essentially reduces to reconstructing a signal from the samples taken at irregularly sampled points for which we propose a ‘line plus sum of sines’ model. In the presence of noise, the temporal structure of the level-crossings can get distorted. To reduce the effects of noise, we use a short-time Fourier transform (STFT) based enhancement scheme. The performance of the proposed method is studied through Monte-Carlo simulations for a phase signal with composite IF for various SNRs. Different level-crossing based estimates are combined to obtain a new IFestimate. Simulation studies show that the estimates obtained using zero-crossing (ZC) and other very low level values perform better than those obtained with higher level values