Distribution network fault section estimation using analytical database approach

Abstract

A fault in a power system may cause interruption of supply. The fault needs to he detected, located and cleared as soon as possible. In a distribution network, it is difficult to determine where the fault occurs. This is because there is lack of information on the distribution network status except a trip feeder. Therefore. in order to improve the customer minute loss, the fault section should be estimated so that the faulty section can be isolated and the rest of the sections in the feeder can be quickly restored. This thesis describes the development or a new fault section estimation algorithm in a distribution network. This is the main part of the research which investigates how the voltage sag can be used to estimate the fault section 111 the distribution network. The method IS based on an analytical database approach which uses a power flow and fault analysis program to establish analytical voltage sag databases for a typical studied distribution network topology. The databases contain voltage sag magnitude and phase shin information for all nodes on the distribution network under different fault types and load conditions. When a fault occurs, the method only needs to measure the fault generated voltage sag waveform at the network primary substation. This measured waveform is then compared to the analytical databases. Database search and comparison algorithms were developed to identify the faulty section fix the network. The proposed method was evaluated and tested on a typical distribution network by using voltage waveforms produced by PSCAD/EMTDC. n power system simulator. Prior to the fault section estimation process, the fault type has first to be classified. This is because different types of fault may cause different values of voltage sag, which leads lo having different databases for different types of fault. In this research. wavelet technique was adopted. The voltage signal was transformed to wavelets coefficients using the wavelet transform. Then the standard deviation of these coefficients was calculated. and an algorithm was developed to classify the fault type. using these standard deviation values. III In addition to the fault section estimation and fault type classification. this study also investigates how to transfer voltage waveforms efficiently from the substation to the central site. This is because a substation is usually situated far from the central site, and the waveform needs to be transferred to the central site so that the fault type classification and fault section estimation process can be done. The method proposed in this thesis is by data compression and reconstruction using wavelet transform.