Artificial Neural Network-based Fault Location in Ehv Transmission Lines
نویسنده
چکیده
This paper deals with the application of artificial neural networks (ANNs) to the fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using one terminal line. The neural fault detector and locators have been trained with different sets of data available from a selected power network model and simulating different fault scenarios (fault types, fault locations, fault resistances and fault inception angles). A comparative study of the proposed fault locators has been carried out in order to determine which ANN fault locator structure leads to the best performance. The results show that the fault locator using current and voltage values is more accurate.
منابع مشابه
Fault Location in Ehv Transmission Lines Using Artificial Neural Networks
This paper deals with the application of artificial neural networks (ANNs) to fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using terminal line data. The proposed neural fault detector and locator were trained using various sets of data available from a selected power network model and simulating different fault scenarios (fault types, fau...
متن کاملFault Classification in EHV Transmission Lines Using Artificial Neural Networks
This paper investigates a new approach based on Artificial Neural Networks (ANNs) for real-time fault classification in power transmission lines which can be used in digital power system protection. The technique uses sampled current and voltage data of each phase at one terminal as inputs to the corresponding ANN. The ANN outputs indicate the type of the fault within a time less than 5 ms. The...
متن کاملDouble Circuit EHV Transmission Lines Fault Location with RBF Based Support Vector Machine and Reconstructed Input Scaled Conjugate Gradient Based Neural Network
A new algorithm is developed to enhance the solution for the problems associated with double circuit transmission lines for the mutual coupling between the two circuits under fault conditions and which is highly variable in nature. The algorithm depends on the three-line voltages and the six line currents of double circuit lines at one end. It relies on the application of Support Vector Machine...
متن کاملIdentification and Classification of Fault in an EHV Transmission line using S-Transform and Neural Network
This paper presents a technique for diagnosis of the type of fault and the faulty phase on overhead transmission line. The proposed method is based on the multiresolution S-transform and Parseval’s theorem. S-transform is used to produce instantaneous frequency vectors of the voltage signals of the three phases, and then the energies of these vectors, based on the Parseval’s theorem, are utiliz...
متن کاملComparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN
An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are...
متن کامل