Decision Tree Based Fault Classification Scheme for Protection of Series Compensated Transmission Lines

2007 ◽  
Vol 8 (6) ◽  
Author(s):  
Urmil B. Parikh ◽  
Bhavesh R. Bhalja ◽  
Rudra Prakash Maheshwari ◽  
Biswarup Das
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Fault Classification ◽  
Phase Identification ◽  
Variable Loading ◽  
Data Set ◽  
Before And After ◽  
Zero Sequence ◽  
System Variables ◽  
Series Capacitor

Series compensation at the midpoint of a transmission line creates problems to conventional protection approaches. A new fault classification technique has been developed for a transmission line with a series capacitor at the midpoint, having different percentages of compensation varying from 25% to 75%. The proposed technique requires three line currents and voltages at each end and computes fundamental phasors of these quantities using a modified version of Full Cycle Discrete Fourier Transform. Using these phasors, the absolute values of three phase impedances are calculated for faulted phase identification. Moreover, the involvement of the ground in the fault is identified using a zero sequence component of the fault current. Using a PSCAD/EMTDC software package, a large test data (28,800) set has been generated with different types of faults and system variables, which includes fault resistances, fault inception angles, fault positions (before and after series capacitor) and variable loading conditions along with wide variations in the source impedances at both ends of a transmission line. The proposed scheme is tested on the said data set and the results are found to be promising. The results indicate that the proposed technique is fast, accurate and robust for a wide variation in system and fault conditions.

scholarly journals Combined DFT and Fuzzy Based Faulty Phase Selection and Classification in a Series Compensated Transmission Line

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Praveen Kumar Mishra ◽  
Anamika Yadav
Keyword(s):  
Transmission Line ◽  
Fault Location ◽  
Fault Classification ◽  
Testing Time ◽  
Heavy Load ◽  
Phase Selection ◽  
Protection Scheme ◽  
Fault Resistance ◽  
Zero Sequence ◽  
Series Capacitor

The conventional distance protection scheme malfunctions sometimes in case of a fixed series capacitor compensated transmission line due to the change in relaying impedance of the protected line during faulty conditions. In order to mitigate this problem, a combined discrete Fourier transform and fuzzy (CDFTF) based algorithm has been proposed in this paper. This method has been tested on a 400 km, 735 kV series compensated transmission line network and WSCC 3-machine 9-bus system for all fault types using MATLAB/Simulink and PSCAD platforms, respectively. A fixed series capacitor is located at the middle of the protected line. The fundamental components of phase currents, phase voltages, and zero-sequence current are fed as inputs to the proposed scheme. The fault detection, faulty phase selection, and fault classification are achieved within 1/2–1 cycle of power frequency. The proposed CDFTF-based scheme is less complex and is better than other data mining techniques which require huge training and testing time. Test results corroborate the proposed scheme reliability with wide variations in fault location, fault resistance, fault inception angle, evolving faults, compensation level, and heavy load interconnection. The results discussed in this work indicate that the proposed technique is resilient to wide variations in fault and system conditions.

scholarly journals Classification and direction discrimination of faults in transmission lines using 1D convolutional neural networks

2021 ◽  
Vol 12 (3) ◽  
pp. 1928
Author(s):  
Ahmed Thamer Radhi ◽  
Wael Hussein Zayer ◽  
Adel Manaa Dakhil
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Feature Extraction ◽  
Transmission Line ◽  
Convolutional Neural Networks ◽  
Transmission Lines ◽  
Fault Classification ◽  
Line System ◽  
Direction Discrimination ◽  
Conventional Methods

<span lang="EN-US">This paper presents a fast and accurate fault detection, classification and direction discrimination algorithm of transmission lines using one-dimensional convolutional neural networks (1D-CNNs) that have ingrained adaptive model to avoid the feature extraction difficulties and fault classification into one learning algorithm. A proposed algorithm is directly usable with raw data and this deletes the need of a discrete feature extraction method resulting in more effective protective system. The proposed approach based on the three-phase voltages and currents signals of one end at the relay location in the transmission line system are taken as input to the proposed 1D-CNN algorithm. A 132kV power transmission line is simulated by Matlab simulink to prepare the training and testing data for the proposed 1D- CNN algorithm. The testing accuracy of the proposed algorithm is compared with other two conventional methods which are neural network and fuzzy neural network. The results of test explain that the new proposed detection system is efficient and fast for classifying and direction discrimination of fault in transmission line with high accuracy as compared with other conventional methods under various conditions of faults.</span>

A rate-of-change-of-current based fault classification technique for thyristor-controlled series-compensated transmission lines

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Nishant H. Kothari ◽  
Bhavesh R. Bhalja ◽  
Vivek Pandya ◽  
Pushkar Tripathi
Keyword(s):  
Transmission Lines ◽  
Noise Signal ◽  
Current Transformer ◽  
Rate Of Change ◽  
Fault Classification ◽  
Support Vector ◽  
Svm Classifier ◽  
Classification Technique ◽  
Suggested Technique ◽  
Zero Sequence

Abstract This paper presents a new fault classification technique for Thyristor-Controlled Series-Compensated (TCSC) transmission lines using Support Vector Machine (SVM). The proposed technique is based on the utilization of post-fault magnitude of Rate-of-Change-of-Current (ROCC). Fault classification has been carried out by giving ROCC of three-phases and zero sequence current as inputs to SVM classifier. The performance of SVM as a binary-class, and multi-class classifier has been evaluated for the proposed feature. The validity of the suggested technique has been tested by modeling a TCSC based 400 kV, 300 km long transmission line using PSCAD/EMTDC software package. Based on the above model, a large number of diversified fault cases (41,220 cases) have been generated by varying fault and system parameters. The effect of window length, current transformer (CT) saturation, noise-signal, and sampling frequency have also been studied. It has been found that the proposed technique provides an accuracy of 99.98% for 37,620 test cases. Moreover, the performance of the suggested technique has also been found to be consistent upon evaluating in a 12-bus power system model consisting of a 365 kV, 60 Hz, 300 km long TCSC line. Comparative evaluation of the proposed SVM based technique with other recent techniques clearly indicates its superiority in terms of fault classification accuracy.

Optimal Series Capacitor Compensation for Transmission Lines

2019 ◽  
Vol 16 (8) ◽  
pp. 3455-3460
Author(s):  
Chun Lim Hiew ◽  
Jacqueline Lukose
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Voltage Stability ◽  
Optimization Technique ◽  
Stability Index ◽  
Test System ◽  
Total Power ◽  
Voltage Profile ◽  
Series Capacitor Compensation ◽  
Series Capacitor

Nowadays, voltage stability issues are the main problems around the world and therefore it is important that to maintain stable voltage stability. Series capacitor compensation plays an important role in the transmission line because it can improve the voltage stability as compared to shunt compensation. The Thyristor-Controlled Series Capacitor (TCSC) is selected in this project for providing capacitor compensation because its ability to control the amount of compensation in the transmission line, and operating in three different mode of region, which are resonance, capacitive, and inductive regions. The Fast Voltage Stability Index (FVSI) is used to determine the system’s stability and determine the weakest line in the system for TCSC placement. The TCSC sizing is optimized by using Differential Evolution (DE) optimization technique. All these processes are simulated on Institute of Electrical and Electronics Engineer (IEEE) 14-bus test system by using MATLAB. The proposed methodology was carried out in few tests, which are system contingency test, line outage test, power loss test, voltage profile improvement test and variable TCSC location. Based on the results, the overall voltage stability of the system was improved. The voltage magnitude for each bus had improved and the total power losses also reduced. Therefore, the optimization is successful and the study’s aim is achieved.

scholarly journals Non-Human-Machine Interaction for Power Transmission Lines Protection Design and Enhancement of Under Voltage Relay

2022 ◽  
Vol 05 (02) ◽  
pp. 26-40
Author(s):  
Abadal-Salam T. Hussain
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Fault Location ◽  
Short Circuit ◽  
Fault Classification ◽  
Design System ◽  
Human Machine Interaction ◽  
Matlab Simulink ◽  
Operation Conditions ◽  
Voltage Drops

The continuous monitoring of transmission line protection relay is desirable to ensure the system disturbance such as fault inception is detected in transmission line. Therefore, fault on transmission line needs to be detected, classified, and located accurately to maintain the stability of system. This project presents design enhancement and development under voltage relay in power system protection using MATLAB/Simulink. The under-voltage relay is a relay that has contacts that operate when voltage drops below a set voltage which is used for protection against voltage drops to detect short circuit and others. This study is carried out for all types of faults which only related with one of the parallel lines. For the overall of operation conditions, the sample data were generated for the system by varying the different fault types and fault location. This design system proposes the use of MATLAB/ Simulink based method for fast and reliable fault classification and location for a various type of fault.

scholarly journals Single-ended method to accurately calculate UHV AC transmission line frequency parameters

2018 ◽  
Vol 173 ◽  
pp. 02043
Author(s):  
GAN Fan ◽  
ZHANG Nana ◽  
LI Yun-ge ◽  
Fu Zhouxing
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Positive Sequence ◽  
Actual Measurement ◽  
Distribution Parameters ◽  
Zero Sequence ◽  
Power Frequency ◽  
Capacitive Reactance ◽  
Ac Transmission ◽  
Double Circuit Line

The power frequency parameter of transmission line is the basic parameter of line over-voltage calculation. It is necessary to get the parameters of 1000kV AC double-circuit line on the same tower in order to guide the operation of the project. In this paper, a method of accurately calculating UHV transmission line parameters is proposed. The length of the line is known, the voltage and current at the head of the line are measured, and the zero sequence, positive sequence total impedance and total capacitive reactance are obtained. Based on the distribution parameters Calculation formula, the line unit capacitance, resistance and inductance parameters can be obtained. The method of this paper is compared with the simulation of transmission line parameters in ATP simulation. And Through the actual measurement of the frequency parameters of Yu-heng 1000kV transmission line, it is verified that this method is suitable for the calculation of distribution parameters of UHV transmission lines.

scholarly journals Comparison and Analysis of the Influence of Different Data Transformation Methods on the Fault Identification of Flexible DC Transmission Lines by Convolutional Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Can Ding ◽  
Zhenyi Wang ◽  
Qingchang Ding ◽  
Taiping Nie
Keyword(s):  
Neural Network ◽  
Transmission Line ◽  
Convolutional Neural Network ◽  
Transmission Lines ◽  
Data Transformation ◽  
Transformation Method ◽  
Recall Rate ◽  
Fault Classification ◽  
Mode Decomposition ◽  
Transformation Methods

In the fault classification and identification of flexible DC transmission lines, it is inevitable to use the voltage and current characteristics of the transmission line. All kinds of data transformation methods can highlight the hidden characteristics of the original fault electrical quantity. Various artificial intelligence algorithms can further reduce the difficulty of transmission line fault classification. For such fault classification methods, this paper first builds a four-terminal flexible direct current transmission system model on PSCAD/EMTDC platform and obtains data by simulating different faults of transmission lines. Then, empirical mode decomposition (EMD), wavelet transform (WT), fast Fourier transform (FFT), and variational mode decomposition (VMD) are performed on the obtained data, respectively. Finally, the transformed data and original data are used as inputs to classify by convolutional neural network (CNN). The influence of one data transformation method and different combinations of two data transformation methods on CNN classification results is explored. The simulation results show that when only one data transformation method is used, CNN has the best classification effect for the data after VMD transformation. The classification accuracy and recall rate are both increased from 96.9% and 96.3% without data transformation to 99.88%. When VMD and FFT are combined, CNN classification results’ accuracy and recall rate are further improved to 99.96%.

scholarly journals Situational Awareness Enhancement in Transmission Lines using NI Based PMU

2020 ◽  
Vol 9 (3) ◽  
pp. 2987-2997
Keyword(s):  
Power System ◽  
Transmission Line ◽  
Transmission Lines ◽  
Situational Awareness ◽  
Vital Role ◽  
System Stability ◽  
Fault Classification ◽  
Wide Area ◽  
Support Vector ◽  
Power System Monitoring

Phasor Measurement Units (PMUs) are becoming prominent in enhancing the situational awareness in wide area power system monitoring, thereby playing a vital role in its protection and control. This paper focuses on enhancing the situational awareness of transmission line using National Instruments (NI) based PMU. The data measured by the virtual PMU is used for fault detection and fault classification. The detection and the classification in the LabVIEW platform are performed using the Fourier Transform and support vector machines (SVMs) respectively. The proposed methodology has been applied on a laboratory set up consisting of transmission line, three phase load and an NI based PMU. The enhanced situational awareness in the detection and classification of transmission line faults helps in restoration of the transmission line as quickly as possible and trigger wide area control actions to maintain power system stability against the disturbances created by a fault.

Composite right/left-handed transmission line with array of thermocouples for generating terahertz radiation

2020 ◽  
Vol 92 (2) ◽  
pp. 20502
Author(s):  
Behrokh Beiranvand ◽  
Alexander S. Sobolev ◽  
Anton V. Kudryashov
Keyword(s):  
Transmission Line ◽  
Terahertz Radiation ◽  
Transmission Lines ◽  
Software Package ◽  
Optical Pulses ◽  
Capacitively Coupled ◽  
Voltage Difference ◽  
Left Handed ◽  
Microwave Transmission ◽  
Commercial Software Package

We present a new concept of the thermoelectric structure that generates microwave and terahertz signals when illuminated by femtosecond optical pulses. The structure consists of a series array of capacitively coupled thermocouples. The array acts as a hybrid type microwave transmission line with anomalous dispersion and phase velocity higher than the velocity of light. This allows for adding up the responces from all the thermocouples in phase. The array is easily integrable with microstrip transmission lines. Dispersion curves obtained from both the lumped network scheme and numerical simulations are presented. The connection of the thermocouples is a composite right/left-handed transmission line, which can receive terahertz radiation from the transmission line ports. The radiation of the photon to the surface of the thermocouple structure causes a voltage difference with the bandwidth of terahertz. We examined a lossy composite right/left-handed transmission line to extract the circuit elements. The calculated properties of the design are extracted by employing commercial software package CST STUDIO SUITE.

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