Ahmad Keshavarz

Increasing demand of energy, has contributed to the development of power networks. Transmission line of electricity is one of the power network sections which transmit energy produced by the power plants to the consumers. Since short circuit is the most considerable disruption in the transmission lines therefore identifying the exact location of the fault in transmission lines and eliminating it immediately leads to a higher use of lines, service consistency, prevention of wasting energy sources and disruption in the equipment. After the removal of disrupted transmission line from the network, the most important issue is to precisely and immediately identify fault location in the transmission line. Then disrupted part must be fixed and returned to the network. In this study, a new method for identifying fault location in the transmission lines of electricity is presented which makes use of the online data bank. Then by using the data from the voltage signal measured at one-end, the flaw resistance is estimated by regression Gaussian process. Then an online data bank will be produced by using estimated resistance. Harmonics of the voltage signal would be produced when a discrete Forrier transform is applied. Harmonics of the voltage are given to regression Gaussian process for training after normalization. To simulate and test the proposed method, Matlab software is used moreover noise model will be added to the data of the taken voltage at one-end of the line based on the Gaussian distribution function.