Wavelet fuzzy based fault location estimation in a three terminal transmission system

Fault location on a series-compensated three-terminal transmission line using deep neural networks

Abstract: In this study, discrete wavelet transform (DWT) and deep neural network (DNN) are utilised for fault location in a series-compensated three-terminal transmission line. The series compensation causes challenges in fault location schemes of the three-terminal transmission lines. The presented fault location method has been extensively tested using the SIMULINK model of a three-terminal transmission line. Features extracted from synchronous measurements of fault currents at the three terminals using DWT are fed to the DNN. Faulted section determination and fault distance calculation are carried out using a single intelligent network simultaneously. Faulted section is determined with 100% accuracy, and the efficiency of algorithm is validated for symmetrical and unsymmetrical faults, and different values of fault resistance, inception angle, and location. The accuracy of the algorithm is acceptable for large fault resistances (above 100 Ω) and fault inception angles near zero. Total mean error for test data is 0.0458% which is much improved with respect to other similar works.

Wavelet-alienation based protection scheme for multi-terminal transmission line

Abstract: This paper presents a wavelet-alienation based protection scheme for multi-terminal transmission system. The proposed algorithm makes use of wavelet transform based approximate coefficients of three-phase voltage and current signals, obtained over a quarter cycle to detect, classify and locate various faults. Detection and classification of faults are achieved with the help of approximate coefficients based alienation coefficients of current signals, measured from all the buses of system. The approximate coefficients of voltage and current signals, obtained over a quarter cycle, are fed to artificial neural network to locate the faults precisely, from respective buses. This algorithm has been tested successfully for all the types of faults with variations in location, inception angle and fault impedance. The proposed protection scheme is generalized for N-terminal system followed by successful testing on three-terminal and five-terminal systems.

Fault location estimation for series-compensated double-circuit transmission line using parameter optimized variational mode decomposition and weighted P-norm random vector functional link network

Abstract: In this paper, both the proposed parameter optimized variational mode decomposition (POVMD) and weighted P-norm random vector functional link network (WPRVFLN) are integrated for fault detection, location estimation, and classification in a series capacitor compensated double circuit transmission line (SCCDCTL). The required number of decomposition is determined from the magnitude spectrum of full-cycle current signals from the point of fault inception. An entropy index is used to obtain the optimum value of data-fidelity factor for extracting the most suitable band-limited intrinsic mode functions (BLIMFs). The four efficacious features namely standard deviation of the magnitude, energy, Renyi entropy and crest factor are computed from the Hilbert transformed array of the BLIMFs to construct the feature vector. A diagonal matrix W is computed based on zero sequence current of the original current signals as a weighting factor to categorize the ground fault accurately. Numerous faults are generated with a wide variation of the system conditions in MATLAB/Simulink simulation environment. An efficient WPRVFLN computational intelligence technique is proposed to recognize the fault by taking the extracted feature vector with weight factor, and its performances are compared with the recently developed classifiers in the MATLAB interface. The lesser computational complexity, faster learning speed, superior fault location estimation accuracy, and short event detection time prove that the proposed POVMD–WPRVFLN method can be implemented in the real power system for online fault recognition. Finally, the feasibility of the proposed method is tested and validated by using the fast FPGA digital circuitry in a loop.

Fuzzy Inference System Based Distance Estimation Approach for Multi Location and Transforming Phase to Ground Faults in Six Phase Transmission Line

Abstract: The faults occurring in different phases at multiple locations and different times are difficult to locate exact location using conventional techniques. This paper develops a fault location estimation approach using fuzzy inference system for multi location phase to ground faults and transforming phase to ground faults in six phase transmission (SPT) line. The six phase current data of SPT line are generated by MATLAB software and processed through butter worth filter, sampling and discrete fourier transform for distance locator. The proposed technique is dependent on single terminal data only. Mamdani fuzzy inference system is employed to make decision. Triangular membership functions are used to design input-output fuzzy sets. Fuzzy inference system has been deployed for the fault distance location using IF-THEN rules. The proposed technique is validated during different multi location and transforming phase to ground faults with wide variations in fault resistance and fault inception angle. Simulations and calculations with MATLAB prove that the fault location method is correct and accurate.

Fuzzy logic based fault detector and classifier for three phase transmission lines with STATCOM

Abstract: This paper presents the fault detection and classification for shunt faults on transmission lines with Static Synchronous Compensator (STATCOM) using fuzzy logic. The fuzzy logic is implemented by using the fuzzy logic toolbox in MATLAB. The 500kV, 60Hz system is simulated using simulink and simpower systems toolbox in MATLAB. The proposed method uses only the three phase currents for fault detection and classification of faulted phase. The system is simulated for various shunt faults with different fault resistances and with different fault locations between 10 percent and 90 percent of the transmission line. The results from the simulation show that fuzzy logic based fault detector and classifier accurately detects and classifies the faults on transmission system. The proposed method is able to detect and classify the faults for varying fault resistances and fault distances from the relaying point.

Combined fuzzy-logic wavelet-based fault classification technique for power system relaying

Abstract: This paper presents a new approach to real-time fault classification in power transmission systems using fuzzy-logic-based multicriteria approach Only the three line currents are utilized to detect fault types such as LG, LL, and LLG, and then to define the faulty line An online wavelet-based preprocessor stage is used with data window of ten samples (based on 45-kHz sampling rate and 50-Hz power frequency) The multicriteria algorithm is developed based on fuzzy sets for the decision-making part of the scheme Computer simulation has been conducted using EMTP programs Results are shown and they indicate that this approach can be used as an effective tool for high-speed digital relaying, as the correct detection is achieved in less than half a cycle and that computational burden is much simpler than the recently postulated fault classification techniques

A wavelet-fuzzy combined approach for classification and location of transmission line faults

Abstract: This paper presents a real-time wavelet-Fuzzy combined approach for digital relaying The algorithm for fault classification employs wavelet multi resolution analysis (MRA) to overcome the difficulties associated with conventional voltage and current based measurements due to effect of factors such as fault inception angle, fault impedance and fault distance The proposed algorithm for fault location, different from conventional algorithms that are based on deterministic computations on a well-defined model to be protected, employs wavelet transform together with fuzzy logic The wavelet transform captures the dynamic characteristics of the non-stationary transient fault signals using wavelet MRA coefficients The fuzzy logic is employed to incorporate expert evaluation through fuzzy inference system (FIS) so as to extract important features from wavelet MRA coefficients for obtaining coherent conclusions regarding fault location Computer simulations using MATLAB have been conducted for a 300 Km 400 KV line Simulation results indicate that both the classification and localization algorithms are immune from effects of faults inception angle, impedance and distance The most significant contribution of this paper is that the proposed location algorithm has a maximum error of 65% with a computational time of about one cycle Thus both classification and location algorithms can be used as effective tools for real-time digital relaying purpose

A Fault Classification and Localization Method for Three-Terminal Circuits Using Machine Learning

Abstract: This paper presents a traveling-wave-based method for fault classification and localization for three-terminal power transmission systems. In the proposed method, the discrete wavelet transform is utilized to extract transient information from the recorded voltages. Support-vector-machine classifiers are then used to classify the fault type and faulty line/half in the transmission networks. Bewley diagrams are observed for the traveling-wave patterns and the wavelet coefficients of the aerial mode voltage are used to locate the fault. Alternate Transients Program software is used for transients simulations. The performance of the method is tested for different fault inception angles, different fault resistances, nonlinear high impedance faults, and nontypical faults with satisfactory results.

Digital fault location for parallel double-circuit multi-terminal transmission lines

Abstract: Two new methods are proposed for fault point location in parallel double-circuit multi-terminal transmission lines by using voltages and currents information from CCVTs and CTs at all terminal. These algorithms take advantage of the fact that the sum of currents flowing into a fault section equals the sum of the currents at all terminals. Algorithm 1 employs an impedance calculation and algorithm 2 employs the current diversion ratio method. Computer simulations are carried out and applications of the proposed methods are discussed. Both algorithms can be applied to all types of fault such as phase-to-ground and phase-to-phase faults. As one equation can be used for all types of fault, classification of fault types and selection of faulted phase are not required. Phase components of the line impedance are used directly, so compensation of unbalanced line impedance is not required.

Development of a new fault location algorithm for multi-terminal two parallel transmission lines

Abstract: The authors propose a novel fault location algorithm for multiterminal parallel transmission lines. The proposed method uses the same AC inputs as protective relays and uses only the magnitude of the differential currents at each terminal. This makes it possible to simplify the H/W and S/W configurations of a fault locator since it is not required to synchronously collect the differential current data at each terminal. This algorithm consists of a basic three-terminal fault location algorithm and equivalent conversion to a three-terminal system from an n-terminal system. For a multifault occurring simultaneously at the same place on both lines as well as a single fault occurring at one place on one of the two lines, this algorithm is reasonably accurate. This was verified mathematically and examined by EMTP simulation. >