This paper presents a single-ended traveling wave -based fault location and distance protection method for a hybrid transmission line: an overhead line combined with an underground cable. Dis-crete wavelet transformation (DWT) is used to extract transient information from the measured voltages. Support vector machine (SVM) classifiers are utilized to identify the faulty-section and faulty-half. Bewley diagrams are observed for the traveling wave patterns and the wavelet coeffi cients of the aerial mode voltage are used to locate the fault. The transient simulation for different fault types and locations are obtained by ATP using frequency - de-pendent line and cable models. MATLAB is used to process the simulated transients and apply the proposed method. The perfor-mance of the method is tested for different fault inception angles (FIA), different fault resistances, non-linear high impedance faults (NLHIF), and non-ideal faults with satisfactory results. The impact of cable aging on the proposed method accuracy is also investigated.
This document presents a technique for locating faults on double circuit transmission lines using wavelet transform and wavelet modulus maxima. The technique uses traveling wave theory and modal decomposition to transform coupled three-phase voltages and currents into independent modal components. Wavelet analysis is then used to obtain the wavelet transform coefficients of each modal component. The time difference between wavelet modulus maxima peaks of the modal components indicates the fault location. Simulation results demonstrate the validity of the technique for various fault types, locations, resistances, and inception angles. The technique can accurately locate faults using data from a single line terminal.
- This paper proposes a new technique of using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) based on Clarke’s transformation for fault classification and detection on a single circuit transmission line. Simulation and training process for the neural network are done by using PSCAD / EMTDC and MATLAB. Daubechies4 mother wavelet (DB4) is used to decompose the high frequency components of these signals. The wavelet transform coefficients (WTC) and wavelet energy coefficients (WEC) for classification fault and detect patterns used as input for neural network training back-propagation (BPNN). This information is then fed into a neural network to classify the fault condition. A DWT with quasi optimal performance for preprocessing stage are presented. This study also includes a comparison of the results of training BPPN and DWT with and without Clarke’s transformation, where the results show that using Clarke transformation in training will give in a smaller mean square error (MSE) and mean absolute error (MAE). The simulation also shows that the new algorithm is more reliable and accurate.
"Use of PMU data for locating faults and mitigating cascading outage"Power System Operation
This document summarizes two methods presented in the paper: 1) A fault location method that uses sparse PMU data and electromechanical wave propagation to detect faults on transmission lines. It introduces a decision tree classifier to analyze voltage measurements and locate faults with high accuracy. 2) A controlled islanding scheme to predict and mitigate cascading outages. It uses spectral clustering to partition the system and suggest switching actions to create stable islands with minimum load shedding. The methods were tested on simulated systems and show potential to improve grid monitoring, fault response and prevention of blackouts.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document describes a new method for locating faults in transmission cable lines. It begins by introducing the need for improved cable fault detection technologies. It then describes the development of a novel noncontact sensor (NCS) that can detect electric fields and has adjustable sensitivity through theoretical calculation and simulation. Next, it proposes a new method called FVMD + WVD that uses feedback variational mode decomposition and the Wigner-Ville distribution to more accurately identify the arrival time of fault waves compared to existing methods. Simulations and experiments show that the NCS performs reliably and the new method reduces error in fault location to only 0.48%. The findings demonstrate an improved system for detecting and locating cable faults.
Double Circuit Transmission Line Protection using Line Trap & Artificial Neur...IRJET Journal
This document presents a technique for protecting double circuit transmission lines using line traps and artificial neural networks. Line traps are placed at the terminals of the protected line to detect faults based on high frequency transients. An artificial neural network is trained using the RMS voltage and current signals to classify fault types. MATLAB simulation studies were conducted to model a 300km, 25kV, 50Hz transmission system with three zones. RMS measurements from one end were used to train the neural network to classify faults. The neural network approach provides fast, secure and reliable protection for double circuit transmission lines.
Wavelet based detection and location of faults in 400kv, 50km Underground Po...ijceronline
This document presents a method for detecting and locating faults in underground power cables using wavelet transforms. A 400kV, 50km underground cable system is modeled in MATLAB Simulink. Various single-phase, two-phase, and three-phase faults are simulated at distances of 25km and 50km from the measurement point. Voltage and current signals are analyzed using continuous wavelet transforms to detect and locate faults. Simulation results show the method can accurately estimate fault locations, with errors generally under 7%. The method is capable of determining fault type and location for both transmission and distribution cables.
This document presents a technique for locating faults on double circuit transmission lines using wavelet transform and wavelet modulus maxima. The technique uses traveling wave theory and modal decomposition to transform coupled three-phase voltages and currents into independent modal components. Wavelet analysis is then used to obtain the wavelet transform coefficients of each modal component. The time difference between wavelet modulus maxima peaks of the modal components indicates the fault location. Simulation results demonstrate the validity of the technique for various fault types, locations, resistances, and inception angles. The technique can accurately locate faults using data from a single line terminal.
- This paper proposes a new technique of using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) based on Clarke’s transformation for fault classification and detection on a single circuit transmission line. Simulation and training process for the neural network are done by using PSCAD / EMTDC and MATLAB. Daubechies4 mother wavelet (DB4) is used to decompose the high frequency components of these signals. The wavelet transform coefficients (WTC) and wavelet energy coefficients (WEC) for classification fault and detect patterns used as input for neural network training back-propagation (BPNN). This information is then fed into a neural network to classify the fault condition. A DWT with quasi optimal performance for preprocessing stage are presented. This study also includes a comparison of the results of training BPPN and DWT with and without Clarke’s transformation, where the results show that using Clarke transformation in training will give in a smaller mean square error (MSE) and mean absolute error (MAE). The simulation also shows that the new algorithm is more reliable and accurate.
"Use of PMU data for locating faults and mitigating cascading outage"Power System Operation
This document summarizes two methods presented in the paper: 1) A fault location method that uses sparse PMU data and electromechanical wave propagation to detect faults on transmission lines. It introduces a decision tree classifier to analyze voltage measurements and locate faults with high accuracy. 2) A controlled islanding scheme to predict and mitigate cascading outages. It uses spectral clustering to partition the system and suggest switching actions to create stable islands with minimum load shedding. The methods were tested on simulated systems and show potential to improve grid monitoring, fault response and prevention of blackouts.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document describes a new method for locating faults in transmission cable lines. It begins by introducing the need for improved cable fault detection technologies. It then describes the development of a novel noncontact sensor (NCS) that can detect electric fields and has adjustable sensitivity through theoretical calculation and simulation. Next, it proposes a new method called FVMD + WVD that uses feedback variational mode decomposition and the Wigner-Ville distribution to more accurately identify the arrival time of fault waves compared to existing methods. Simulations and experiments show that the NCS performs reliably and the new method reduces error in fault location to only 0.48%. The findings demonstrate an improved system for detecting and locating cable faults.
Double Circuit Transmission Line Protection using Line Trap & Artificial Neur...IRJET Journal
This document presents a technique for protecting double circuit transmission lines using line traps and artificial neural networks. Line traps are placed at the terminals of the protected line to detect faults based on high frequency transients. An artificial neural network is trained using the RMS voltage and current signals to classify fault types. MATLAB simulation studies were conducted to model a 300km, 25kV, 50Hz transmission system with three zones. RMS measurements from one end were used to train the neural network to classify faults. The neural network approach provides fast, secure and reliable protection for double circuit transmission lines.
Wavelet based detection and location of faults in 400kv, 50km Underground Po...ijceronline
This document presents a method for detecting and locating faults in underground power cables using wavelet transforms. A 400kV, 50km underground cable system is modeled in MATLAB Simulink. Various single-phase, two-phase, and three-phase faults are simulated at distances of 25km and 50km from the measurement point. Voltage and current signals are analyzed using continuous wavelet transforms to detect and locate faults. Simulation results show the method can accurately estimate fault locations, with errors generally under 7%. The method is capable of determining fault type and location for both transmission and distribution cables.
Ijeee 28-32-accurate fault location estimation in transmission linesKumar Goud
Accurate Fault Location Estimation in Transmission Lines
B. Narsimha Reddy Dr. P. Chandra Sekar
Sr. Assistant Professor, Dept. of EEE Associate Professor, Dept. of EEE
Mahatma Gandhi Institute of Technology Mahatma Gandhi Institute of Technology
Hyderabad, TS, India Hyderabad, TS, India
babubnr@gmail.com Pcs_76@rediffmail.com
Abstract: In trendy power transmission systems, the double-circuit line structure is increasingly adopted. However, owing to the mutual coupling between the parallel lines it is quite difficult to style correct fault location algorithms. Moreover, the widely used series compensator and its protecting device introduce harmonics and non-linearity’s to the transmission lines, that create fault location a lot of difficult. To tackle these issues, this thesis is committed to developing advanced fault location strategies for double-circuit and series-compensated transmission lines. Algorithms utilizing thin measurements for pinpointing the situation of short-circuit faults on double-circuit lines square measure planned. By moldering the initial net-work into 3 sequence networks, the bus ohmic resistance matrix for every network with the addition of the citations fault bus may be developed. It’s a perform of the unknown fault location. With the increased bus ohmic resistance matrices the sequence voltage amendment throughout the fault at any bus may be expressed in terms of the corresponding sequence fault current and also the transfer ohmic resistance between the fault bus and the measured bus. Resorting to tape machine the superimposed sequence current at any branch may be expressed with relevancy the pertaining sequence fault current and transfer ohmic resistance terms. Obeying boundary conditions of different fault sorts, four different categories of fault location algorithms utilizing either voltage phasors, or phase voltage magnitudes, or current phasors or section current magnitudes square measure derived. The distinguishing characteristic of the planned methodology is that the information measurements need not stem from the faulted section itself. Quite satisfactory results are obtained victimisation EMTP simulation studies. A fault location rule for series-compensated transmission lines that employs two-terminal asynchronous voltage and current measurements has been implemented. For the distinct cases that the fault happens either on the left or on the right aspect of the series compensator, 2 subroutines square measure developed. In addition, the procedure to spot the proper fault location estimate is represented during this work. Simulation studies disbursed with Matlab Sim Power Systems show that the fault location results square measure terribly correct.
Keywords: Ohmic Resistance, Transmission Lines, PMU, DFR, VCR, EMTP, MOV.
Fault location and correction are important in case of any power systems. This process has to be prompt and accurate so that system reliability can be improved , outage time can be reduced and restoration of system from fault can be accelerated.
Fault location calculation using Magnetoresistance sensor is described here.
This document summarizes a research paper that proposes new offline Prony and Matrix Pencil methods for phasor estimation to improve fault location accuracy on series compensated transmission lines. The techniques aim to eliminate sub-synchronous frequency components, decaying DC offsets, and noise before phasor estimation. The performance is evaluated using simulated signals in Matlab and results are compared to existing methods. Key aspects of series compensation impacts, the proposed filtering and estimation techniques, and Prony and Matrix Pencil methods are summarized.
Brief Literature Review on Phasor Based Transmission Line Fault Location Algo...sarasijdas
This document summarizes various phasor-based fault location algorithms for transmission lines. It categorizes algorithms as traditional knowledge-based, traveling wave-based, or phasor-based methods that can use synchronized or unsynchronized data from single-end, double-end, or multi-terminal lines. Factors affecting accuracy are discussed. Selected algorithms are presented for untransposed parallel lines, lines with cables, multi-terminal lines, and series compensated lines. References for various algorithms are provided.
This document presents an unsynchronized fault location technique for multisection compound transmission lines. The objective is to identify fault locations on such lines using unsynchronized measurements from both ends of the line, without requiring knowledge of the line parameters. It formalizes the technique in several steps, including manipulating voltage and current measurements based on fault distance and line impedance. The technique then calculates the fault distance over a range of synchronization angles and selects the minimum value. The technique is able to locate faults on both overhead lines and underground cables. It provides fault distances for various single-phase and three-phase faults.
Wide Area Fault Location for Power Transmission Network using Reactance Based...Muhd Hafizi Idris
Download here: https://www.researchgate.net/publication/332441499_Wide_Area_Fault_Location_for_Power_Transmission_Network_using_Reactance_Based_Method?_sg=Tkk3ur2Kc3XGh3JHwtJdPM3IdJJx_K42N3Zu9kX_ECutHW5j91ExIMtrJFOui4E-RikSYmuYR0uZWEEVHoSaDTPZuRvC29V6GzZ5g9BS.GnmzKNF1XN22czjk5npta57bMn8D2KxxwQsAMEPlK7abE5qGykkxj8CgUcnYHlzpKEZST1ujqv7avTquOi7Aug
With the advancements in smart grid, communication technology, intelligent electronic device and substation automation, wide area applications for monitoring, protection, control and fault location becoming focused nowadays and improved from time to time. This research focuses on using wide area synchrophasor measurements for fault location in transmission network which acts as a backup to conventional fault location method. Simple reactance based methods together with a developed rules system are used to locate the possible affected line and its fault location. Using the developed rules and algorithm, fault location impedance will be compared at each synchrophasor bus connected lines for different fault types, then between connected lines and finally between synchrophasors buses. Faults at various locations with different fault resistances have been simulated and the results prove that the developed method can be used to locate the fault point and can be used as a backup to main fault location method. Future works also discussed how the method can be improved to get the best and accurate fault location results.
Wavelet energy moment and neural networks based particle swarm optimisation f...journalBEEI
In this study, a combined approach of discrete wavelet transform analysis and a feed forward neural networks algorithm to detect and classify transmission line faults. The proposed algorithm uses a multi -resolution analysis decoposition of three-phasecurrents only to calculate the wavelet energy moment of detailed coefficients. In comparison with the energy spectrum, the energy moment could reveal the energy distribution features better, which is beneficial when extracting signal features. Theapproach use particle swarm optimization algorithm to train a feed forward neural network. The goal is the enhancement of the convergence rate, learning process and fill up the gap of local minimum point.The purposed scheme consists of two FNNs, one for detecting and another for classifying all the ten types of faults using Matlab/Simulink. The proposed algorithm have been extensively tested on a system 400 kV, 3 phases, 100 km line consideringvarious fault parameter variations.
This document discusses using artificial neural networks (ANNs) for fault detection and location in extra high voltage transmission lines. It presents a fault detector and locator trained on data from power system simulations of different fault scenarios. The fault detector identifies faults based on current and voltage signals. Three ANN-based fault locators are evaluated that use different inputs like current magnitudes, voltage and current magnitudes, and voltage magnitudes. Test results show the ANN approach can accurately detect and locate faults, with the best performance from the locator using both current and voltage phasor magnitudes. This neural network method provides high-speed fault protection for transmission lines.
Wavelet based double line and double line -to- ground fault discrimination i...IAEME Publication
In this paper, an accurate method to discriminate double line and double line to ground faults
in a three terminal transmission circuit based on wavelet transforms is presented. The proposed
algorithm uses the fault indices of three phase currents of all terminals. Fault indices are obtained by
1st level decomposition of current signals using Bior 1.5 mother wavelet considering the variations
in fault resistance, fault inception angle and distance along the transmission circuit. The entire test
results clearly show that the variation in the value of fault index of the healthy phase with the
presence of ground and constant value in the case of non- presence of ground which discriminates
double line fault from the double line to ground faults in the path along one terminal towards the
other terminal with variations in fault inception angle and fault resistance. The algorithm is proved to
be effective and efficient in detection and discrimination of faults.
Dynamic Performance of Distance Relayson Series Compensated Transmission Line...Premier Publishers
Series compensation is installed in power system networks to increase power transfer capacity, improve the system stability, reduce system losses, improve voltage regulation and for achieving flexible power flow control. Distance relays are widely used as main or backup protection of transmission lines including series-compensated transmission lines. The performance of conventional distance relays is affected by series capacitors and cause certain protection issues. This paper briefly discusses the problems like voltage inversion, current inversion, overreach and under reach during the fault conditions specific to series compensated lines. The behavior of capacitor protection techniques is discussed with simulations performed using Real Time Digital Simulator (RTDS) simulator for a typical 400 kV system having series compensation. The analysis is based on Transmission Line fault simulations, internal and external to the 400-transmission line where the Fixed Series Compensation (FSC)is installed.
Transmission line is one the important compnent in protection of electric power system because the transmission line connects the power station with load centers.
The fault includes storms, lightning, snow, damage to insulation, short circuit fault [1].
Fault needs to be predicted earlier in order to be prevented before it occur
Enhancement algorithm for reverse loop technique on planar reverse loop antennaTELKOMNIKA JOURNAL
This document presents a method to stabilize wireless transfer efficiency (WTE) between two planar loop antennas using a reverse loop technique. The method involves introducing a reverse loop to the transmitting planar loop antenna to form a planar reverse loop antenna (PRLA). This helps control the mutual inductance between the antennas in the over-coupled region where they are closer than the optimal operating distance. Mathematical modeling and electromagnetic simulations show that the PRLA maintains a more constant mutual inductance with distance changes compared to conventional planar loop antennas. Fabricated prototypes validate that the reverse loop technique results in greater stability of WTE at closer distances without additional system adjustments.
Impact Analysis of Midpoint Connected STATCOM on Distance Relay PerformanceRadita Apriana
This paper presents the impact of the Static Synchronous Compensator (STATCOM) on the
performance of distance protection of EHV transmission lines. A 400kV transmission system having
midpoint connected STATCOM with its control circuit is modeled using MATLAB/SIMULINK software. The
impact of STATCOM on distance relay for different fault conditions and different fault locations is analyzed.
Simulation results indicate that the presence of the STATCOM in the transmission system significantly
changes the line impedance seen by the distance relay to be lower or higher than the actual line
impedance. Due to this the performance of the distance relay changes, either overreaches or under
reaches.
This document compares the performance of the 6th derivative Gaussian UWB pulse shape to the 2nd derivative Gaussian pulse shape in an IEEE 802.15.3a multipath fading channel using different types of RAKE receivers in the presence of multiple-user interference and Gaussian noise. It finds that both the pulse shape used and the number of RAKE fingers impact the signal-to-noise ratio and bit error rate performance in the channel model. Specifically, it concludes that the 6th derivative pulse is more suitable for meeting FCC power regulations and achieving better BER performance since higher derivatives increase the peak emission frequency while decreasing signal bandwidth.
Limitations of DC injection into the AC network is an important operational requirement for grid connected photovoltaic systems. There is one way to ensure that this issue needs a power transformer as a connection to the AC network. However, this solution adds cost, volume, mass, and power losses. Ideally there shouldn't be any DC at the output of the inverter, but practically, a small amount of DC current is present. Therefore, in this paper there are techniques for the DC offset elimination are proposed. Some have drawbacks which was treated by another technique. Also there are best solutions for eliminating DC offset as in section 17, and 18 as it explains how to reduce the DC offset in a transformerless operation with reducing the power losses, mass and the cost effect.
Sliding Discrete Fourier Transform (SDFT) is very efficient regarding computational load and it possesses a very fast phase angle detection with excellent harmonic rejection at nominal frequency. However, at off-nominal frequency, SDFT generates errors in both magnitude and phase angle due to spectral leakage. This paper introduces a workaround for Fourier Transform to handle this disability under off-nominal frequency while avoiding variable-rate sampling. Sliding Fourier Transform (SFT) is used as a phase detector for a phase-locked loop whose output frequency is used to drive the SFT. The paper revisits the mathematics of Fourier Transform (FT) in a three-phase setting via a time-domain approach to show a newly proposed filtering technique for the double-frequency oscillation just by summing the FT sine/cosine filter outputs of the three individual phases. Also, the analysis aims to determine and correct the phase and magnitude errors under offnominal frequency operation. The proposed technique (SFT-PLL) is tested in real time on dSPACE DS1202 DSP using voltage vectors that are pregenerated to simulate the most adverse grid conditions. The testing scenarios compare the performance of the SFT-PLL with that of the Decoupled Stationary Reference Frame PLL (dαβPLL). The results prove that SFT-PLL is superior to dαβPLL.
Adjusting third zone distance protectionravi yadav
This document proposes an adaptive distance relaying scheme to avoid undesirable third zone tripping during voltage instability events. The scheme uses local measurements to adjust the third zone protection characteristics based on the apparent impedance trajectory entering a predefined Third Zone Proximity Area. This provides time for emergency controls like undervoltage load shedding to mitigate system collapse before third zone tripping occurs. The adjustments include using blinders, modifying the characteristic shape, rotating the characteristic, and reducing the third zone reach. The scheme aims to prevent cascading outages during heavy stressed system conditions.
Effective two terminal single line to ground fault location algorithmMuhd Hafizi Idris
This paper presents an effective algorithm to locate Single Line to Ground (SLG) fault at a transmission line. Post fault voltages and currents from both substation terminals were used as the input parameters to the algorithm. Discrete Fourier Transform (DFT) was used to extract the magnitudes and phase angles of three phase voltages and currents. The modeling of the transmission line along with the algorithm was performed using Matlab/Simulink package. The results of fault location for SLG faults along the transmission line demonstrated the validity of the algorithm used even for high resistance earth fault.
Wavelet based analysis for transmission line fault locationAlexander Decker
This document summarizes a technique for locating faults on electric power transmission lines using wavelet analysis. It begins with an introduction to transmission line faults and issues with existing fault location methods. It then describes the basics of traveling wave theory and modal analysis for decomposing fault currents. A proposed algorithm is outlined that uses the discrete wavelet transform to analyze modal components of fault current received at a relay point. Time delays between modal components are used to determine the fault location based on the faulted transmission line length and wave propagation speed. Simulation results using MATLAB are presented to illustrate the approach. The method aims to provide accurate fault location independently of factors like fault inception angle and impedance.
This document discusses various methods for locating faults in underground cable systems. It begins with an introduction to fault location and describes terminal and tracer methods. It then examines specific techniques like bridge techniques, capacitance ratio methods, and wavelet transforms. Wavelet transforms are highlighted as they allow good time-frequency resolution needed to analyze fault transients. The document concludes by discussing how wavelet analysis can be used to extract features from signals to identify characteristic frequencies and locate faults.
A simple faulted phase-based fault distance estimation algorithm for a loop d...IJEECSIAES
This paper presents a new fault distance estimation algorithm for loop distribution systems that uses traveling wave theory. The algorithm filters signals to remove noise, transforms the signals to modal components to avoid mutual effects, and uses discrete wavelet transforms to extract arrival times. It then identifies the faulted phase and estimates the fault distance based on the time delay between the zero mode and faulted phase-based aerial mode components. Simulations test the algorithm on a modified IEEE 14-bus test system under various fault conditions and noise levels. Results show the algorithm can accurately estimate fault distance up to 99.7% with 30dB SNR.
Ijeee 28-32-accurate fault location estimation in transmission linesKumar Goud
Accurate Fault Location Estimation in Transmission Lines
B. Narsimha Reddy Dr. P. Chandra Sekar
Sr. Assistant Professor, Dept. of EEE Associate Professor, Dept. of EEE
Mahatma Gandhi Institute of Technology Mahatma Gandhi Institute of Technology
Hyderabad, TS, India Hyderabad, TS, India
babubnr@gmail.com Pcs_76@rediffmail.com
Abstract: In trendy power transmission systems, the double-circuit line structure is increasingly adopted. However, owing to the mutual coupling between the parallel lines it is quite difficult to style correct fault location algorithms. Moreover, the widely used series compensator and its protecting device introduce harmonics and non-linearity’s to the transmission lines, that create fault location a lot of difficult. To tackle these issues, this thesis is committed to developing advanced fault location strategies for double-circuit and series-compensated transmission lines. Algorithms utilizing thin measurements for pinpointing the situation of short-circuit faults on double-circuit lines square measure planned. By moldering the initial net-work into 3 sequence networks, the bus ohmic resistance matrix for every network with the addition of the citations fault bus may be developed. It’s a perform of the unknown fault location. With the increased bus ohmic resistance matrices the sequence voltage amendment throughout the fault at any bus may be expressed in terms of the corresponding sequence fault current and also the transfer ohmic resistance between the fault bus and the measured bus. Resorting to tape machine the superimposed sequence current at any branch may be expressed with relevancy the pertaining sequence fault current and transfer ohmic resistance terms. Obeying boundary conditions of different fault sorts, four different categories of fault location algorithms utilizing either voltage phasors, or phase voltage magnitudes, or current phasors or section current magnitudes square measure derived. The distinguishing characteristic of the planned methodology is that the information measurements need not stem from the faulted section itself. Quite satisfactory results are obtained victimisation EMTP simulation studies. A fault location rule for series-compensated transmission lines that employs two-terminal asynchronous voltage and current measurements has been implemented. For the distinct cases that the fault happens either on the left or on the right aspect of the series compensator, 2 subroutines square measure developed. In addition, the procedure to spot the proper fault location estimate is represented during this work. Simulation studies disbursed with Matlab Sim Power Systems show that the fault location results square measure terribly correct.
Keywords: Ohmic Resistance, Transmission Lines, PMU, DFR, VCR, EMTP, MOV.
Fault location and correction are important in case of any power systems. This process has to be prompt and accurate so that system reliability can be improved , outage time can be reduced and restoration of system from fault can be accelerated.
Fault location calculation using Magnetoresistance sensor is described here.
This document summarizes a research paper that proposes new offline Prony and Matrix Pencil methods for phasor estimation to improve fault location accuracy on series compensated transmission lines. The techniques aim to eliminate sub-synchronous frequency components, decaying DC offsets, and noise before phasor estimation. The performance is evaluated using simulated signals in Matlab and results are compared to existing methods. Key aspects of series compensation impacts, the proposed filtering and estimation techniques, and Prony and Matrix Pencil methods are summarized.
Brief Literature Review on Phasor Based Transmission Line Fault Location Algo...sarasijdas
This document summarizes various phasor-based fault location algorithms for transmission lines. It categorizes algorithms as traditional knowledge-based, traveling wave-based, or phasor-based methods that can use synchronized or unsynchronized data from single-end, double-end, or multi-terminal lines. Factors affecting accuracy are discussed. Selected algorithms are presented for untransposed parallel lines, lines with cables, multi-terminal lines, and series compensated lines. References for various algorithms are provided.
This document presents an unsynchronized fault location technique for multisection compound transmission lines. The objective is to identify fault locations on such lines using unsynchronized measurements from both ends of the line, without requiring knowledge of the line parameters. It formalizes the technique in several steps, including manipulating voltage and current measurements based on fault distance and line impedance. The technique then calculates the fault distance over a range of synchronization angles and selects the minimum value. The technique is able to locate faults on both overhead lines and underground cables. It provides fault distances for various single-phase and three-phase faults.
Wide Area Fault Location for Power Transmission Network using Reactance Based...Muhd Hafizi Idris
Download here: https://www.researchgate.net/publication/332441499_Wide_Area_Fault_Location_for_Power_Transmission_Network_using_Reactance_Based_Method?_sg=Tkk3ur2Kc3XGh3JHwtJdPM3IdJJx_K42N3Zu9kX_ECutHW5j91ExIMtrJFOui4E-RikSYmuYR0uZWEEVHoSaDTPZuRvC29V6GzZ5g9BS.GnmzKNF1XN22czjk5npta57bMn8D2KxxwQsAMEPlK7abE5qGykkxj8CgUcnYHlzpKEZST1ujqv7avTquOi7Aug
With the advancements in smart grid, communication technology, intelligent electronic device and substation automation, wide area applications for monitoring, protection, control and fault location becoming focused nowadays and improved from time to time. This research focuses on using wide area synchrophasor measurements for fault location in transmission network which acts as a backup to conventional fault location method. Simple reactance based methods together with a developed rules system are used to locate the possible affected line and its fault location. Using the developed rules and algorithm, fault location impedance will be compared at each synchrophasor bus connected lines for different fault types, then between connected lines and finally between synchrophasors buses. Faults at various locations with different fault resistances have been simulated and the results prove that the developed method can be used to locate the fault point and can be used as a backup to main fault location method. Future works also discussed how the method can be improved to get the best and accurate fault location results.
Wavelet energy moment and neural networks based particle swarm optimisation f...journalBEEI
In this study, a combined approach of discrete wavelet transform analysis and a feed forward neural networks algorithm to detect and classify transmission line faults. The proposed algorithm uses a multi -resolution analysis decoposition of three-phasecurrents only to calculate the wavelet energy moment of detailed coefficients. In comparison with the energy spectrum, the energy moment could reveal the energy distribution features better, which is beneficial when extracting signal features. Theapproach use particle swarm optimization algorithm to train a feed forward neural network. The goal is the enhancement of the convergence rate, learning process and fill up the gap of local minimum point.The purposed scheme consists of two FNNs, one for detecting and another for classifying all the ten types of faults using Matlab/Simulink. The proposed algorithm have been extensively tested on a system 400 kV, 3 phases, 100 km line consideringvarious fault parameter variations.
This document discusses using artificial neural networks (ANNs) for fault detection and location in extra high voltage transmission lines. It presents a fault detector and locator trained on data from power system simulations of different fault scenarios. The fault detector identifies faults based on current and voltage signals. Three ANN-based fault locators are evaluated that use different inputs like current magnitudes, voltage and current magnitudes, and voltage magnitudes. Test results show the ANN approach can accurately detect and locate faults, with the best performance from the locator using both current and voltage phasor magnitudes. This neural network method provides high-speed fault protection for transmission lines.
Wavelet based double line and double line -to- ground fault discrimination i...IAEME Publication
In this paper, an accurate method to discriminate double line and double line to ground faults
in a three terminal transmission circuit based on wavelet transforms is presented. The proposed
algorithm uses the fault indices of three phase currents of all terminals. Fault indices are obtained by
1st level decomposition of current signals using Bior 1.5 mother wavelet considering the variations
in fault resistance, fault inception angle and distance along the transmission circuit. The entire test
results clearly show that the variation in the value of fault index of the healthy phase with the
presence of ground and constant value in the case of non- presence of ground which discriminates
double line fault from the double line to ground faults in the path along one terminal towards the
other terminal with variations in fault inception angle and fault resistance. The algorithm is proved to
be effective and efficient in detection and discrimination of faults.
Dynamic Performance of Distance Relayson Series Compensated Transmission Line...Premier Publishers
Series compensation is installed in power system networks to increase power transfer capacity, improve the system stability, reduce system losses, improve voltage regulation and for achieving flexible power flow control. Distance relays are widely used as main or backup protection of transmission lines including series-compensated transmission lines. The performance of conventional distance relays is affected by series capacitors and cause certain protection issues. This paper briefly discusses the problems like voltage inversion, current inversion, overreach and under reach during the fault conditions specific to series compensated lines. The behavior of capacitor protection techniques is discussed with simulations performed using Real Time Digital Simulator (RTDS) simulator for a typical 400 kV system having series compensation. The analysis is based on Transmission Line fault simulations, internal and external to the 400-transmission line where the Fixed Series Compensation (FSC)is installed.
Transmission line is one the important compnent in protection of electric power system because the transmission line connects the power station with load centers.
The fault includes storms, lightning, snow, damage to insulation, short circuit fault [1].
Fault needs to be predicted earlier in order to be prevented before it occur
Enhancement algorithm for reverse loop technique on planar reverse loop antennaTELKOMNIKA JOURNAL
This document presents a method to stabilize wireless transfer efficiency (WTE) between two planar loop antennas using a reverse loop technique. The method involves introducing a reverse loop to the transmitting planar loop antenna to form a planar reverse loop antenna (PRLA). This helps control the mutual inductance between the antennas in the over-coupled region where they are closer than the optimal operating distance. Mathematical modeling and electromagnetic simulations show that the PRLA maintains a more constant mutual inductance with distance changes compared to conventional planar loop antennas. Fabricated prototypes validate that the reverse loop technique results in greater stability of WTE at closer distances without additional system adjustments.
Impact Analysis of Midpoint Connected STATCOM on Distance Relay PerformanceRadita Apriana
This paper presents the impact of the Static Synchronous Compensator (STATCOM) on the
performance of distance protection of EHV transmission lines. A 400kV transmission system having
midpoint connected STATCOM with its control circuit is modeled using MATLAB/SIMULINK software. The
impact of STATCOM on distance relay for different fault conditions and different fault locations is analyzed.
Simulation results indicate that the presence of the STATCOM in the transmission system significantly
changes the line impedance seen by the distance relay to be lower or higher than the actual line
impedance. Due to this the performance of the distance relay changes, either overreaches or under
reaches.
This document compares the performance of the 6th derivative Gaussian UWB pulse shape to the 2nd derivative Gaussian pulse shape in an IEEE 802.15.3a multipath fading channel using different types of RAKE receivers in the presence of multiple-user interference and Gaussian noise. It finds that both the pulse shape used and the number of RAKE fingers impact the signal-to-noise ratio and bit error rate performance in the channel model. Specifically, it concludes that the 6th derivative pulse is more suitable for meeting FCC power regulations and achieving better BER performance since higher derivatives increase the peak emission frequency while decreasing signal bandwidth.
Limitations of DC injection into the AC network is an important operational requirement for grid connected photovoltaic systems. There is one way to ensure that this issue needs a power transformer as a connection to the AC network. However, this solution adds cost, volume, mass, and power losses. Ideally there shouldn't be any DC at the output of the inverter, but practically, a small amount of DC current is present. Therefore, in this paper there are techniques for the DC offset elimination are proposed. Some have drawbacks which was treated by another technique. Also there are best solutions for eliminating DC offset as in section 17, and 18 as it explains how to reduce the DC offset in a transformerless operation with reducing the power losses, mass and the cost effect.
Sliding Discrete Fourier Transform (SDFT) is very efficient regarding computational load and it possesses a very fast phase angle detection with excellent harmonic rejection at nominal frequency. However, at off-nominal frequency, SDFT generates errors in both magnitude and phase angle due to spectral leakage. This paper introduces a workaround for Fourier Transform to handle this disability under off-nominal frequency while avoiding variable-rate sampling. Sliding Fourier Transform (SFT) is used as a phase detector for a phase-locked loop whose output frequency is used to drive the SFT. The paper revisits the mathematics of Fourier Transform (FT) in a three-phase setting via a time-domain approach to show a newly proposed filtering technique for the double-frequency oscillation just by summing the FT sine/cosine filter outputs of the three individual phases. Also, the analysis aims to determine and correct the phase and magnitude errors under offnominal frequency operation. The proposed technique (SFT-PLL) is tested in real time on dSPACE DS1202 DSP using voltage vectors that are pregenerated to simulate the most adverse grid conditions. The testing scenarios compare the performance of the SFT-PLL with that of the Decoupled Stationary Reference Frame PLL (dαβPLL). The results prove that SFT-PLL is superior to dαβPLL.
Adjusting third zone distance protectionravi yadav
This document proposes an adaptive distance relaying scheme to avoid undesirable third zone tripping during voltage instability events. The scheme uses local measurements to adjust the third zone protection characteristics based on the apparent impedance trajectory entering a predefined Third Zone Proximity Area. This provides time for emergency controls like undervoltage load shedding to mitigate system collapse before third zone tripping occurs. The adjustments include using blinders, modifying the characteristic shape, rotating the characteristic, and reducing the third zone reach. The scheme aims to prevent cascading outages during heavy stressed system conditions.
Effective two terminal single line to ground fault location algorithmMuhd Hafizi Idris
This paper presents an effective algorithm to locate Single Line to Ground (SLG) fault at a transmission line. Post fault voltages and currents from both substation terminals were used as the input parameters to the algorithm. Discrete Fourier Transform (DFT) was used to extract the magnitudes and phase angles of three phase voltages and currents. The modeling of the transmission line along with the algorithm was performed using Matlab/Simulink package. The results of fault location for SLG faults along the transmission line demonstrated the validity of the algorithm used even for high resistance earth fault.
Wavelet based analysis for transmission line fault locationAlexander Decker
This document summarizes a technique for locating faults on electric power transmission lines using wavelet analysis. It begins with an introduction to transmission line faults and issues with existing fault location methods. It then describes the basics of traveling wave theory and modal analysis for decomposing fault currents. A proposed algorithm is outlined that uses the discrete wavelet transform to analyze modal components of fault current received at a relay point. Time delays between modal components are used to determine the fault location based on the faulted transmission line length and wave propagation speed. Simulation results using MATLAB are presented to illustrate the approach. The method aims to provide accurate fault location independently of factors like fault inception angle and impedance.
This document discusses various methods for locating faults in underground cable systems. It begins with an introduction to fault location and describes terminal and tracer methods. It then examines specific techniques like bridge techniques, capacitance ratio methods, and wavelet transforms. Wavelet transforms are highlighted as they allow good time-frequency resolution needed to analyze fault transients. The document concludes by discussing how wavelet analysis can be used to extract features from signals to identify characteristic frequencies and locate faults.
A simple faulted phase-based fault distance estimation algorithm for a loop d...IJEECSIAES
This paper presents a new fault distance estimation algorithm for loop distribution systems that uses traveling wave theory. The algorithm filters signals to remove noise, transforms the signals to modal components to avoid mutual effects, and uses discrete wavelet transforms to extract arrival times. It then identifies the faulted phase and estimates the fault distance based on the time delay between the zero mode and faulted phase-based aerial mode components. Simulations test the algorithm on a modified IEEE 14-bus test system under various fault conditions and noise levels. Results show the algorithm can accurately estimate fault distance up to 99.7% with 30dB SNR.
A simple faulted phase-based fault distance estimation algorithm for a loop d...nooriasukmaningtyas
This paper presents a new fault distance estimation algorithm for loop distribution systems that uses traveling wave theory. The algorithm filters signals to remove noise, transforms the signals to modal components to avoid mutual effects, and uses discrete wavelet transforms to extract detail coefficients. It then identifies the faulted phase and estimates fault distance based on the time delay between the zero mode and faulted phase-based aerial mode detail coefficients. Simulations test the algorithm on a modified IEEE 14-bus test system under various fault conditions and noise levels. Results show the algorithm can accurately estimate fault distance up to 99.7% with 30dB SNR.
This document presents a new method for locating ungrounded faults in underground distribution systems using wavelet analysis and artificial neural networks (ANNs). Voltage and current signals are simulated for different fault types, locations, and conditions using EMTP software. Wavelet analysis is used to extract features from the signals related to fault classification and location. ANNs are then applied to classify fault types based on the extracted features and to determine the fault location for each fault type based on additional extracted features. The results indicate the technique can accurately locate faults under a variety of system conditions.
Fault location in sec interconnected network based on synchronized phasor mea...Abhishek Kulshreshtha
This document discusses using synchronized phasor measurements from Phasor Measurement Units (PMUs) to locate faults in interconnected power networks. It addresses the challenge that it is not economical to install PMUs at all network buses. The paper proposes using the Tree Search Method (TSM) to determine a near-optimal placement of PMUs that allows fault location. It presents simulation results applying TSM to standard test systems and a real network, showing the ability to accurately locate different fault types. Mathematical formulations for calculating fault distances are also discussed.
The document presents a new method for fault classification and direction discrimination in transmission lines using 1D convolutional neural networks (1D-CNNs). A 132kV transmission line model is simulated to generate training and testing data for the 1D-CNN algorithm. The proposed 1D-CNN approach directly uses the voltage and current signals from one end as input, merging feature extraction and classification into a single learning process. Testing shows the 1D-CNN method accurately classifies and discriminates fault direction with higher accuracy than conventional neural network and fuzzy neural network methods under different fault conditions.
This document presents a technique for detecting, classifying, and locating faults on an 11kV underground cable system using continuous wavelet transform (CWT). Faults generate high frequency signals that propagate along the cable. CWT is applied to extract these signals and analyze them to determine the fault location based on the travel time of the signals. A 100km long underground cable system is modeled in MATLAB and simulated with different fault types and locations. CWT is effective at extracting the transient fault signals and fault locations are determined with less than 1% error for single line faults and around 8% error for double line faults based on the signal travel times.
Detection and Location of Faults in 11KV Underground Cable by using Continuou...IOSR Journals
This document presents a technique for detecting, classifying, and locating faults on an 11kV underground cable system using continuous wavelet transform (CWT). Faults generate high frequency signals that propagate along the cable. CWT is applied to extract these signals and analyze them to determine the fault location based on the travel time of the signals. A 100km long cable is modeled in MATLAB and faults are simulated at different locations. CWT effectively extracts the high frequency components from the fault signals. The results show that CWT can accurately detect and locate faults by analyzing the extracted signal components. Fault location is determined by measuring the time difference between peaks in the CWT coefficients.
DETECTION OF FAULT LOCATION IN TRANSMISSION LINE USING INTERNET OF THINGS (IOT)Journal For Research
Transmission lines are used to transmit electric power to distant large load centres. These lines are exposed to faults as a result of lightning, short circuits, faulty equipment’s, miss-operation, human errors, overload, and aging.To avoid this situation, and we need the exact location of fault occurrence. This problem ishandled by a set of resistors representing cable length in KMs and fault creation is made by a set of switches at every known KM to cross check the accuracy of the same. The fault occurring at what distance and which phase is displayed on a 16X2 LCD interfaced with the microcontroller. Calculated values are sends to the receiving section with help of Zigbee. Measured values are updated in PC and monitored with help of .NET. RTC is used here to time and date reference, that when the event occurs.
This document discusses a method for detecting, classifying, and locating faults on 220kV transmission lines using discrete wavelet transform and neural networks. Fault detection is performed by calculating the energy of detail coefficients from wavelet transformation of phase current signals. A neural network is then used for fault classification and location. The neural network is trained using patterns generated by simulating different fault conditions, including varying fault location, type, and resistance. The proposed method aims to classify 10 different fault types and locate faults occurring at different points along the transmission line.
This paper presents a discrete wavelet transform and neural network approach to fault
detection and classification and location in transmission lines. The fault detection is carried out by
using energy of the detail coefficients of the phase signals and artificial neutral network algorithm
used for fault type classification and fault distance location for all the types of faults for 220 KV
transmission line. The energies of the all three phases A, B, C and ground phase are given in put to
the neural network for the fault classification. For each type of fault separate neural network is
prepared for finding out the fault location. An improved performance is obtained once the neutral
network is trained suitably, thus performance correctly when faced with different system parameters
and conditions.
Signal-Energy Based Fault Classification of Unbalanced Network using S-Transf...idescitation
This document presents a technique for classifying faults on overhead transmission lines using S-Transform and a Probabilistic Neural Network (PNN) classifier. Voltage signals are processed using S-Transform to extract energy features from each phase. These 3 features (1 per phase) are used as inputs to a PNN classifier to determine the type of fault (e.g. line-ground, line-line) and faulty phase. The method was tested on a simulated 3-phase transmission line model in MATLAB with different fault conditions. It produced accurate classification results, even when noise was added to the signals. The paper concludes the method provides fast and accurate fault classification.
Determination of Fault Location and Type in Distribution Systems using Clark ...IJAPEJOURNAL
In this paper, an accurate method for determination of fault location and fault type in power distribution systems by neural network is proposed. This method uses neural network to classify and locate normal and composite types of faults as phase to earth, two phases to earth, phase to phase. Also this method can distinguish three phase short circuit from normal network position. In the presented method, neural network is trained by αβ space vector parameters. These parameters are obtained using clarke transformation. Simulation results are presented in the MATLAB software. Two neural networks (MLP and RBF) are investigated and their results are compared with each other. The accuracy and benefit of the proposed method for determination of fault type and location in distribution power systems has been shown in simulation results.
Enhanced two-terminal impedance-based fault location using sequence valuesIJECEIAES
Fault at transmission line system may lead to major impacts such as power quality problems and cascading failure in the grid system. Thus, it is very important to locate it fast so that suitable solution can be taken to ensure power system stability can be retained. The complexity of the transmission line however makes the fault point identification a challenging task. This paper proposes an enhanced fault detection and location method using positive and negative-sequence values of current and voltage, taken at both local and remote terminals. The fault detection is based on comparison between the total fault current with currents combination during the pre-fault time. While the fault location algorithm was developed using an impedancebased method and the estimated fault location was taken at two cycles after fault detection. Various fault types, fault resistances and fault locations have been tested in order to verify the performance of the proposed method. The developed algorithms have successfully detected all faults within high accuracy. Based on the obtained results, the estimated fault locations are not affected by fault resistance and line charging current. Furthermore, the proposed method able to detect fault location without the needs to know the fault type.
This document summarizes a research paper that explores using synchrophasor technology for transmission line fault detection via current differential protection. It begins by discussing limitations of traditional current differential protection schemes. It then provides details on implementing a digital current differential protection scheme using synchronized phasor measurements from Phasor Measurement Units at both ends of a transmission line. The paper describes simulating this approach in MATLAB for different fault types, locations, and resistances on a sample transmission system. It is able to compensate for charging currents and achieve nearly 100% reliability in fault detection using synchrophasor-based current differential protection.
Wavelet based double line and double line -to- ground fault discrimination i...IAEME Publication
This document presents a method for discriminating between double line faults and double line-to-ground faults in a three terminal transmission circuit using wavelet transforms. The proposed algorithm analyzes the detail coefficients from the first level decomposition of phase current signals at each terminal using the Bior 1.5 mother wavelet. The algorithm discriminates between the fault types based on variations in the fault index of the healthy phase, which remains constant for double line faults but varies for faults involving ground. Simulation results demonstrate the effectiveness of using the proposed wavelet-based fault indices to discriminate between the fault types at different locations along each transmission path with variations in fault inception angle and resistance.
A comprehensive fuzzy-based scheme for online detection of operational and t...IJECEIAES
Operational modes and topological changes affect power flow in the power systems. As a result, a broad spectrum of protection issues may happen in the power system. So, both the operational and topological changes should be detected fast to prevent blackouts. On the other hand, the existing detection schemes are complex in analyzing and implementation. Therefore, there is a need for an online scheme to identify the network's topology and operation mode simultaneously without complex computations and additional communication infrastructures. To this end, a comprehensive scheme is proposed in which the changes are detected by analyzing the power flow obtained from the network. For this purpose, line outage contingencies and operation modes are defined in rules to be used in a fuzzy inference system (FIS) as a decision-making tool. The proposed scheme can be implemented on existing lines as a communication infrastructure and determines the network’s status in an online manner. Also, in comparison to the existing schemes, the proposed scheme reduces the complexity and the computational burden. The proposed scheme is implemented on IEEE 8-bus system and the results proved its efficiency.
The transmission overhead line is one of the vital elements in the power system for transmitting the electrical energy. In the transmission, the disturbances are often occurred. In the conventional algorithm, alpha and beta (mode) currents generated by Clarke’s transformation are utilized to convert the signal of Discrete Wavelet Transform (DWT) to obtain the Wavelet Transform Coefficient (WTC) and the Wavelet Coefficient Energy (WCE). This study introduces a new algorithm, called Modified Clarke for fault detection and classification using DWT and Back-Propagation Neural Network (BPNN) based on Clarke’s transformation on transmission overhead line by adding gamma current in the system. Daubechies4 (Db4) is used as a mother wavelet to decompose the high frequency components of the signal error. Simulation is performed using PSCAD / EMTDC transmission system modeling and carried out at different locations along the transmission line with different types of fault, fault resistances, fault locations and fault of the initial angle on a given power system model. The simulated fault types are in the study are the Single Line to Ground, the Line To Line, the Double Line to Ground and the Three Phases. There are four statistic methods utilized in the present study to determine the accuracy of detection and classification of faults. The result shows that the best and the worst structures of BPNN occurred on the configuration of 12-24-48-4 and 12-12-6-4, respectively. For instance, the error using Mean Square Error Method. The Error Of Clarke’s, Without Clarke’s and Modified Clarke’s are 0.05862, 0.05513 and 0.03721 which are the best, respectively, whereas, the worst are 0.06387, 0.0753 and 0.052, respectively. This indicates that the Modified Clarke’s result is in the lowest error. The method is successfully implement can be utilized in the detection and classification of fault in transmission line by utilities and power regulation in power system planning and operation.
Similar to Wavelet-Based Fault Location and Distance Protection Method for Transmission Lines (20)
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Wavelet-Based Fault Location and Distance Protection Method for Transmission Lines
1. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 5 | P a g e
Wavelet-Based Fault Location and Distance Protection Method for Transmission Lines K. Prasanna Kumar1, K. Durga Syam Prasad2, K. Sravanthi3
1 P.G Student, Department of EEE, DIET College Of Engineering, Visakhapatnam- 531 002 2 Sr. Assistant Professor, Department of EEE, DIET College Of Engineering, Visakhapatnam- 531 002 3Assistant Professor, Department of EEE, Vignan’s Institute of Information Technology, Visakhapatnam. Abstract This paper presents a single-ended traveling wave -based fault location and distance protection method for a hybrid transmission line: an overhead line combined with an underground cable. Dis-crete wavelet transformation (DWT) is used to extract transient information from the measured voltages. Support vector machine (SVM) classifiers are utilized to identify the faulty-section and faulty-half. Bewley diagrams are observed for the traveling wave patterns and the wavelet coeffi cients of the aerial mode voltage are used to locate the fault. The transient simulation for different fault types and locations are obtained by ATP using frequency - de-pendent line and cable models. MATLAB is used to process the simulated transients and apply the proposed method. The perfor-mance of the method is tested for different fault inception angles (FIA), different fault resistances, non-linear high impedance faults (NLHIF), and non-ideal faults with satisfactory results. The impact of cable aging on the proposed method accuracy is also investigated.
Index Terms—Alternative transients program (ATP), fault lo-cation, frequency -dependent line model, support vector machine, travelling waves, underground cable, wavelet transformation.
I. INTRODUCTION
A. Motivation and Literature Review
In Tomorrow’s Smart grid, fast and accurate fault lo-cation along power transmission and distribution networks will be achieved by deployment of modern technologies used for data recording and analysis combined with intelligent al- gorithms. Smart fault location will result in power system re-liability improvement, quick restoration of the power service and reduction in outage time [1]. The proliferation of under-ground cables combined with overhead transmission lines (hy-brid transmission) in medium- and high -voltage will increase in the future grid. “Hybrid transmission” systems are preferred when right-of-way related issues arise and they offer better reli-ability. In addition, underground cables are also used to connect off-shore wind farms to the existing grid through overhead lines. However, the complexity of fault location problem increases with the proliferation of such an unusual topology. The fault location methods for overhead lines or underground cables are based on post-fault phasors; traveling waves or artifi-cial intelligence. Traveling wave-based fault locators are more accurate, and more reliable when compared to phasor-based methods; however they require advanced sensors with high sampling rates.
Future grid can employ traveling wave- based methods by taking advantage of modern technologies such as optical transducers instead of conventional CTs and CVTs. The main challenge in traveling wave-based fault location for combined overhead line and underground cable is faulty-sec-tion identification. This challenge is due to the reflections of the fault signal from the joint-node and the fault point as well as the unequal traveling wave velocities in line and cable. This paper uses support vector machine (SVM) and discrete wavelet transformation (DWT) to address these challenges and proposes a new traveling wave-based fault location method. Following is an overview of the use of DWT and SVM in power system fault location followed by the review of fault location methods for cable.
The use of SVM for faulty- section identification in series com-pensated transmission line is proposed in [2]–[4]. In [2] steady-state post-fault voltages and currents are used as the input to the SVM classifier, while the current transients are the inputs to the SVM faulty-section identifier in [3] and voltage transients are utilized as the input to the SVM in [4]. The proposed methods in [3] and [4] are dependent on the fault type. In [5] fault lo-cation in transmission lines using SVM- Neural Network with voltage and current transients is proposed. The proposed method assumes that the fault type is known and the SVM corresponding to the fault type is used. References [6] and [7] propose a fault classifi cation and location method based on wavelet transform, SVM, and ANN. The wavelet transformation coeffi cients of three- phase voltage and current transients are used as the input to the SVM fault classi fiers. The ANN is
RESEARCH ARTICLE OPEN ACCESS
2. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 6 | P a g e
then used for fault lo-cation according to the identified fault type.
The single-ended fault location in underground cable using steady -state post-fault phasor voltage and current measure-ments are proposed in [8] and [9]. The faulted underground cable is modeled using the distributed line model. Offline traveling wave- based fault location methods for underground cables are proposed in [10] and [11] where the traveling waves are generated by applying an external excitation voltage. A real -time single- ended traveling wave -based fault location for underground cable is proposed and implemented in [12]. Voltage and current transients are recorded by 200-MHz optic measurements. In [13] a two-ended traveling wave- based fault location using current transients recorded by optic CTs is implemented. The use of discrete wavelet transform (DWT) for transmission line fault location is first proposed in [14]. DWT is applied to the aerial mode voltage to extract the traveling wave information from the recorded transients. In [15] and [16], two -ended traveling wave-based fault locations are pro-posed for underground cables. The time delay between arrivals of traveling waves at both ends is used to calculate the fault location. In [17] and [18] phasor-based fault location methods for hybrid transmission line consisting of an overhead line an underground cable are proposed.an underground cable are proposed. The proposed methods uti-lize the synchronized voltage and current measurements from both ends of the transmission line. In [19] an adaptive neural network-fuzzy approach is used to locate the fault accurately in a combined transmission line using fundamental compo-nents of post-fault measured voltages. In [20] a single-ended traveling wave - based fault-location method using discrete and continuous wavelet transformation is implemented. The current transients are recorded by using 1.25 MHz optical current transducers. [21] presents a wavelet-fuzzy fault location method for transmission lines. DWT is applied to the current transients and the current wavelet energies are used as the input to the fuzzy fault location algorithm. In [22], a two-ended fault location method using the DWT coefficients at 97–195 Hz fre-quency band of three-phase current transients is proposed. The algorithm is dependent on fault type. Cubical interpolation is finally utilized to determine the exact fault location. Reference [23] presents a wavelet and neuro -fuzzy based fault location method. Voltage and current DWT coefficients are used as the input for faulty-section identification. The impedance- based fault location method is then utilized which is dependent on fault type. In [24], a single-ended traveling wave-based fault location method for combined transmission lines is proposed. The voltage traveling wave’s polarity change is used to identify the faulty-section. The time delay between traveling waves is then used to calculate fault location. References [25] and [26] present traveling wave- based fault location methods for underground cables using DWT. [25] uses DWT to cancel the noise and detect the arrival instant of waves observing the correlation between wavelet scales. [26] assumes that the mea-surements are synchronized at both ends. In [27], a combined wavelet-neural network based fault classification and location is proposed. The authors use scale- 3 wavelet coefficients of voltages and fast Fourier transform of reconstructed voltage signal at the same scale to train the neural network. B. Contribution and Paper Organization This paper presents a single-ended fault location method based on traveling waves for a hybrid transmission line, which is composed of an overhead line combined with an underground cable. The preliminary results are presented in [28] and this paper extends the analyses. The method uses DWT and SVM for faulty -section/half identification. The main contributions of the paper are as follows:
• The proposed method uses SVM for faulty- section identi-fication, which is independent of fault type.
• The faulty-half identification is improved by utilization of SVM instead of the time-delay between the arrival time of the initial travelling waves in ground mode and aerial mode.
• The SVM classifiers use a smaller set of inputs for decision making.
The SVM identifiers use the normalized voltage wavelet ener-gies and the normalized transient current energies as input. The performance of the proposed method is insensitive to the fault in-ception angle (FIA) and the method is tested for different fault resistances, non-linear high impedance faults (NLHIF) and non-ideal faults. The impact of cable aging on the proposed fault loca-tion method is also discussed. This paper is organized as follows: In Section II, the fundamentals of SVM classifiers are brie fly re-viewed. In Section III, the proposed fault location method based
Fig. 1. 2-dimensional feature space with the optimal separating hyperplane [30]. on DWT and SVM is presented. Simulation results are provided in Section IV followed by the conclusions in Section V.
3. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 7 | P a g e
II. REVIEW OF SUPPORT VECTOR
MACHINES (SVM)
Support vector machine (SVM) was first
introduced by Vapnik as a binary linear classifier
[29]. The SVM classi fica-tion finds an optimal
hyperplane to separate data sets with two different
classes({+1,-1}). The linear hyperplane is defined by
a weight vector and a bias term as:
(1)
Fig. 1 shows the separating hyperplane in a 2-
dimensional space. The separation margin
between two classes is given as [30]:
w
m
2
(2)
In order to maximize m, is minimized.thus
the maximum margin ,m can be found by solving the
following quadratic optimizing problem [30]:
min w
2
2
1 (3)
subject to yi(WTxi +b) ≥ 1 (4)
Where yi {-1,+1} is the corresponding label for
each xi.
The solution to the problem provides the values
of w and b such that the separation between the
classes is maximum. The SVMs are obtained by
solving the following dual optimization problem
[30]:
N
i
N
i
N
i
L i i j yi yj xi xj
1 1 1
1 max ( ) 2 (5)
Subject to
N
i
i i y
1
(6)
i 0 (7)
where is the Lagrangian multiplier and is the
number of training data.
Once the dual optimization problem is solved,
the training points with are the support vectors
(SVs), and then and are calculated as [30]
N
i
SV
i
i i w y x
1
* *
(8)
NSV
i
i i
sv
y w x
N
b
1
* * ( )
1 (9)
where is the number of SVs.
However, if the original data in the input space
is not linearly separable, it can be mapped into a
higher dimensional feature space using non-linear
functions to obtain a linearly separable data set. As
calculation of inner product of in higher dimen-sional
feature space is computationally complex,
kernel func-tion ; is utilized to calculate the inner
product directly as a func-tion of the original data in
the input space. Thus, the SVMs are obtained by
solving the following optimization problem [30]:
Thus, the optimization problem is solved and the
training points with are the SVs. The optimal
decision function is then expressed as follows [30]:
The most commonly used kernel functions such as
linear, sig-moidal, and Gaussian radial basis function
(RBF) are tested for training and evaluating the SVM
classifiers in this paper and the Gaussian RBF is
chosen due to its better performance. The Gaussian
RBF kernel function is given as:
K(xi,xj)=exp( ( ) /
2
xix j
(14)
Where xi and xj are n-dimensional input vectors .
2 2 ,
is the standard deviation of the Gaussian. The
kernel function parameter is tuned only once in
order to achieve sufficient accuracy. For a more
detailed review of SVM, refer to [30].
In the following section, the proposed fault
location method based on SVM and DWT are
presented.
III. PROPOSED METHOD FOR FAULT
LOCATION
This section describes the proposed single-ended
traveling wave-based fault location method for a
hybrid transmission line including an overhead line
combined with an underground cable. The one-line
diagram of the transmission line is shown in Fig. 2,
where is the length of the overhead line, is the
length of the underground cable and M is the
4. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 8 | P a g e
measurement location.
The fault location is developed based on the
following as-sumptions:
Measurements at the sending end of overhead line
are available.
Fig. 2. A 230-kV transmission line including an
overhead line combined with an underground cable.
• The measurements are obtained through optic
voltage and current recorders instead of
conventional CVTs and CTs.
• Measurement devices are not available at the
joint point.
• Generation and load are not present at the joint
point. The proposed fault location method is
summarized as fol-lows:
A. The faulty-section (i.e., line or cable) is
identified using a binary SVM classier.
B. The faulty-half is identified by using another
binary SVM corresponding to the faulty-section.
C. The Bewley diagram of the fault-initiated
travelling waves is used for fault location.
Note that each topology (different tower con
figuration, dif-ferent phase configuration, different
conductor, different line/ cable length, etc.) requires a
different training of support vector machines. The
three steps outlined above are described in the
following subsections.
A. SVM Faulty-Section Identification
Faulty-section identification is performed using
a binary sup-port vector machine, . The
output implies whether the fault is in the overhead
line or in the underground cable . The
classifier needs to be trained using different fault
scenarios in a given topology. The performance of
the classifier is then evaluated using other fault
scenarios.
The magnitude of voltage and current transients
change with respect to fault location, fault inception
angle (FIA) and fault re-sistances subsequently
affecting the calculated voltage wavelet energies and
current energies. In this paper, normalized wavelet
energies of three-phase and ground mode transient
voltages and normalized energies of three- phase and
ground mode transients currents are used as input to
the binary SVM classifiers. Nor-malization prevents
having large weight vectors in (8) and over-fitting
for the SVMs. The classification is tested
using three different wavelets: Daubechies- 4 (db-4),
db-8, and Meyer. The classification accuracy for
three wavelets remains the same and db-4 is utilized
as the mother wavelet in this paper. The input feature
extraction steps for the SVM classifiers are provided
as follows:
1. Clarke’s modal transformation for transposed
lines is ap-plied to three-phase voltages to
obtain aerial and ground mode voltages. In the
case of untransposed lines, the modal
transformation matrix obtained by ATP
software can be used.
2. DWT is applied to three phase voltages(va,vb,vc)
and ground-mode voltage(V0) to obtain the
wavelet transfor-mation coefficients (WTCs) in
scale -2. The selection of scale-2 over scale-1 is
due to better performance for the investigated
circuits in this study. WTCs are then squared to
identify the arrival instants and hereafter
denoted s
Fig. 3. Faulty-section identification flowchart.
3. The energies of voltage wavelet coeffi
cients, and cur-rents,
are calculated over one cycle after the fault
is detected as follows:
where is the voltage wavelet energy, is the
current energy and is the number of samples in
one cycle.
4. The voltage wavelet energies and current
energies are nor-malized as:
E E E E
E
E
Va Vb Vc V
Vk
Nvk
0
(17)
Where kЄ{a,b,c,0}
E E E E
E
E
Ia Ib Ic I
Ik
Nvk
0
(18)
Where kЄ{a,b,c,0}
Where ENvk is the normalized voltage wavelet
energy and
5. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 9 | P a g e
is the normalized current energy.
The training is carried out to obtain the optimum
decision function for the binary SVM.The input
features,ENvk and ENik are stored in an N 8 matrix
where each column represents one feature and each
row represents one training sample. is the total
number of different fault scenarios with different
locations, types, FIAs, loadings, and fault resistances.
The flowchart of the algorithm is provided in Fig. 3.
is trained using the training matrix
corresponding to an 8-dimen-sional feature space.
Once the training process is completed and the
optimal decision function for the two-class separation
is known, the is ready to identify the faulty-section.
B. SVM Faulty-Half Identification
The existing traveling wave-based fault location
methods use the time delay between the arrival time
of the initial travelling waves in ground mode and
aerial mode for faulty-half identifi-cation. In this
paper, SVM is utilized for faulty -half identifi ca-tion,
which makes the algorithm insensitive to the
possible er-rors resulting from calculation of the time
delay, especially for the faults close to the middle of
the lines. The faulty-half SVM identifiers are trained
by using ENvk and ENik described in the
Fig. 4. Faulty-half identification DT-SVM diagram.
Fig. 5. Bewley diagram of faults in underground
cable.
previous section. The SVM based decision tree (DT-SVM)
for faulty-half identification is shown in Fig.
4, where and are utilized for faulty-half
identification in the overhead line and underground
cable, respectively. Using a trained SVM for each
section (i.e., line or cable) for all fault types is
another advantage of the proposed method.
C. Fault Location
Once the faulty-section and half are identified,
the single-ended traveling wave-based is utilized for
fault location. For the faults located in the
underground cable ( and in Fig. 5), the first
peak of the traveling wave arrives at bus at time
. The first reflected backward travelling wave from
the joint point arrives at bus S after with a time
delay, where is the time required for a traveling
wave to travel the full length of the line. Since the
overhead line travelling wave velocity and the
line length are known, can be calculated as:
(19)
The travelling waves arriving at time instants
after the fi rst observed traveling wave are
not used for fault location. For a fault in the fi rst half
of the cable, the fault location from bus S is
calculated by using:
(20)
where is the propagation velocity along the
underground cable calculated at the frequency
corresponding to the middle value of scale -2 and
[s] is the time delay between the first and the
second peak aerial mode voltage s in
scale-2 at bus S corresponding to backward traveling
wave and the reflected backward traveling wave
from the fault point, respectively. For a fault in the
second half of the underground cable, the fault
location is calculated by using:
(21)
where [mi] is the length of the underground cable
and [s] is the time difference between the first
and the second peak of s at bus S
corresponding to the backward traveling wave and
the reflected forward traveling wave from bus R,
respectively.
The single-ended traveling wave-based method
developed in [14] is utilized to locate the faults
identified by SVMs in over-head line. For a fault in
the first half of the overhead line, the time delay
between the first and the second traveling waves,
[s] is used to calculate the fault location. The time
delay is de-termined by observing aerial mode
voltage s in scale-2. Fault location is
calculated as:
(22)
where [mi/s] is the propagation velocity in the
6. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 10 | P a g e
overhead line calculated at the frequency corresponding to the middle value of scale-2. For the faults identified in the second half of the overhead line, the first and the second traveling waves are used to calculate the fault location as: (23) where [s] is the time delay between the fi rst and the second peak of scale-2 aerial mode voltage s at bus S. The next section presents the simulation results on a test system.
IV. SIMULATION RESULTS
The performance of the proposed fault location method is tested on a 230-kV, 60-Hz transmission line. Line lengths are assumed to be mi and mi. Transient simula-tions are carried out using ATP. Overhead line and underground cable are modeled as frequency-dependent using the data pro- vided in [31] and [32], respectively. The overhead line tower structure and underground cable layout are shown in Fig. 6. In this paper, the results for transposed lines are provided; how-ever the proposed method is also tested on untransposed lines with satisfactory results which are not provided due to space limitations. The sampling time interval of voltage measurement is 5 s (sampling frequency, kHz). The aerial mode traveling wave velocities are calculated using ATP software at 37.5 kHz, which corresponds to the middle value in scale- 2 (25 kHz–50 kHz). The velocities are mi/s in overhead line and mi/s in cable. MATLAB Wavelet Toolbox and SVM Toolbox [33] are used to implement the proposed method. Gaussian noise is introduced to the measured transient voltages and currents to account for measurement noise. The noise is assumed to have zero mean and standard deviation equal to 1% of the sampled voltage or current signal.
Fig. 6. Overhead line tower structure and underground cable layout.
Different fault scenarios under various system conditions(δ-loading ,FIA,Rf and location of the fault )are simulated to evaluate the performance of the proposed method. The simulations are carried out for the following cases:
1) and 30
2) and 120
3) , 100
4) % % % % of the line and cable
A total of 2448 different cases that include all the conditions listed above are simulated. The feature extraction steps given in Section III.A are performed on all obtained simulation re-sults. The obtained input features and their corresponding outputs(i.e.,+1 for the faults in the line and -1 for the faults in the cable) in the first loading level (δ=100) are used to train the SVM faulty –section/half identifiers. The trained SVMs are then tested using the data set corre-sponding to all fault conditions at the second loading level. Other fault scenarios with different fault conditions (f and FIA) corresponding to the intermediate fault locations in the training set (e.g., fault occurring at %) are also tested. The faulty-section identification accu-racy is calculated by using: The accuracies for SVM faulty-section/half identification with three different kernel functions are provided in Table I. Note that the Gaussian RBF has better accuracy than the other kernel functions as mentioned in Section II. The kernel function parameter is tuned to achieve sufficient accuracy. The iden-tification accuracy deteriorates during extreme cases when a high- resistance fault (i.e., ) occurs at small fault inception angles (i.e., ). This combination produces smaller wavelet coeffi cients leading to low signal energies which makes it difficult for SVMs to identify the faulty-section. First scenario assumes that a phase -to-ground fault occurs in overhead line at 87 miles from bus S. The fault conditions are assumed as follows: . The output of faulty-section identifier is identifying TABLE I SVM FAULTY-SECTION/HALF IDENTIFICATION ACCURACY WITH DIFFERENT KERNEL FUNCTIONS
7. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 11 | P a g e
Fig. 7. Voltage s in aerial mode in scale-2 for a single-phase-to-ground fault in overhead line at 87 miles from bus S. the faulty-section as the overhead line. for faulty- half identification in the line gives the output as implying that the aerial mode (mode 1) voltage s at scale-2, shown in Fig. 7 is used for fault location. The time difference between the first and the second travelling waves peaks in s, is observed as 140 s. The fault location is then calculated by using (23): Second scenario assumes that a b-to-ground fault occurs in underground cable at 103 miles from bus s(ie, 3 miles from J-point )with the conditions as δ=150 ,Rf =10Ω and FIA=2750 identification is performed using svm1 resulting in -1 which implies an underground cable fault. The faulty-half of the cable is then identified by using svm3.the svm3 gives the output as +1 impling that the fault is in the second half .Voltage WTC2 in aerial mode at scale-2 at bus s is shown in figure 8.Δt is observed as 60 μs.The fault location is then calculated using (20). Fig. 8. Voltage s in aerial mode in scale-2 for a single-phase-to-ground fault in underground cable at 103 miles from bus S. TABLE II Fault Location Error For Different Case As the common practice, the absolute error is calculated as a percentage of the total section length in order to evaluate the effectiveness of the proposed fault location method [24]. (25) where AFD is the actual fault distance and CFD is the calculated fault distance. Different cases of phase - to-ground faults with 0.5 fault resistance are considered. The results are presented in Table II. The calculated fault locations show good correlation with the actual fault locations. The fault locations in the under-ground cable are calculated with respect to bus S. A. The Effect of Fault Inception Angle The severity of the fault initiated transients is affected by dif-ferent fault inception angles; however, the use of normalized wavelet energies, and as input to the SVMs in the proposed method reduces these impacts. The results for four dif-ferent locations with respect to the changes in FIA are shown
8. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 12 | P a g e
TABLE III
FAULTY LINE IDENTIFICATION AND FAULT
LOCATION FOR DIFFERENT FIA
TABLE IV
FAULTY LINE IDENTIFICATION AND FAULT
LOCATION FOR DIFFERENT
in Table III. The results show that the faulty -
section/half iden-tification methods give reasonably
accurate results for a wide range of fault inception
angles varying between 6 and 354 . The method has
satisfactory performance for locating the faults
occurring under different fault inception angles as
demonstrated in Table III. Our investigations show
that the misclassification zone around the middle
point of the line or cable is 2 miles for extreme cases
such as high-resistance (i.e., ) faults or faults
occurring at small fault inception angles (i.e.,
). The misclassification zone around the joint point is
3 miles for such cases.
B. The Effect of Fault Resistance
The performance of the proposed method is
evaluated for a wide range of fault resistances. As in
the case of small fault inception angles, high
impedance faults (HIFs) affects the severity of the
traveling waves, resulting in smaller signal energies.
As mentioned in the previous subsection the use of
and for faulty line/section identification,
reduces the impacts of high-impedances faults. The
performance of the method is tested for fault
resistances varying from 0.1 to 70 . The faulty-section/
half identi fication results for various fault
resistances are demonstrated in Table IV for different
fault locations. The calculated fault distances and the
corresponding errors do not change with fault
resistance.
TABLE V
FAULTY LINE IDENTIFICATION AND FAULT
LOCATION FOR DIFFERENT FAULT TYPE
C. The Effect of Fault Type
The effects of fault type on the proposed method
for faulty line and faulty-half identification
procedures as well as on fault location are evaluated
in this section. The fault location results for two
different locations in the overhead line and
underground cable with respect to the fault type are
shown in Table V. Al-though different fault types
affect the severity of the fault initi-ated traveling
waves, the proposed method uses the normalized
wavelet energies, and as the input to the
SVMs. As the results show, the faulty-section/half
identification methods give accurate results for four
different fault types. Even though the arrival times of
the traveling waves can vary slightly for dif-ferent
types of faults at a specific location, the time delay
be-tween consecutive traveling waves remains
unchanged. As the time delay between the traveling
waves is used to determine the fault location, the
method gives satisfactory accuracy for lo-cating the
faults occurring under different types as
demonstrated in Table V.
D. The Effect of Non-Linear High Impedance Fault
The performance of the proposed method is
evaluated for a non-linear high impedance fault
(NLHIF) . The model of a dy-namic time-varying
resistance is provided below [34]:
where is the arc resistance which varies with
time, is the time varying arc conductance, [kA] is
the arc current, is the stationary arc conductance,
[kV] is the stationary arc voltage and is the arc
time constant. The stationary arc voltage is estimated
as:
vst u r iarc l ( . ) 0 (29)
9. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 13 | P a g e
where u0[ V/cm] is the constant voltage parameter
per arc length,r[mΩ/cm] is the resistive component
per arc length and [cm] is the arc length.The
following parameters are used to simulate the fault
[34]; u0=9.6, r=1.6 ,l=350 and 1ms
A single- phase - to-ground NLHIF is assumed
to be located at 66 miles away from bus S on the
overhead line. The fault conditions are assumed as
follows:δ=150 and FIA=3100.
The method first identifies the faulty-section
according to the output of which is . The
for half side detection in the overhead line
gives the output as . Thus the faulty-half is
determined in the second half of the line. Voltage
s at bus S in aerial mode at scale- 2 are finally
observed to detect the time delay between the first
two peaks, which is 360 s. The fault location is
calculated by using (23):
Similar to the cases of small fault inception
angles and high-resistance faults, a NLHIF also
affects the magnitude of the trav-eling waves. The
arrival times of the traveling waves are delayed due
to the impact of non-linear impedance on reflection
and re-fraction coefficients. However, the time
difference between the first and the second traveling
wave arrivals remains unaffected. The delay for the
simulated fault is observed to be in the order of 300
s when compared with a resistive fault.
E. The Effect of Non-Ideal Fault
The performance of the proposed fault location
method is evaluated for a non-ideal short-circuit
fault. The 0.5 resis-tance is connected through a 2
inductance to the ground. A -to -ground fault is
located at 26 miles in the overhead line. The faulty-section
identification is first performed using
which gives output as . The for half side
identifi er in the overhead line then gives the output
. Thus the fault sec-tion is identified in the first
half of the line. The aerial mode voltage s at
bus S at scale-2 are used and is observed as 290
s. Thus, the fault location is calculated using (22):
Even though the magnitudes of the traveling
waves decrease as in the case of high- impedance
faults and it also delays the arrival of the traveling
waves for 20 s, the time difference be-tween the
first two arriving waves remain unchanged. The pro-posed
method gives satisfactory results in presence
of non-ideal faults.
F. Discussions
1) Faulty-Half Identification: In this section, the
perfor-mance of the proposed method for faulty-half
identification is compared with that of an existing
method. The time delay between the first traveling
wave arrival in the ground and aerial mode s,
are used for faulty-half identifica-tion in single-ended
wavelet-based methods. In these methods,
faulty-half is identified by comparing with a pre-calculated
time-delay for a fault located in the
middle, . For illustrative purposes, a phase -to-ground
fault is assumed to have occurred in the
underground cable located at 5 miles from the joint
(i.e., 105 miles from bus S). Fig. 9 shows the voltage
s at bus S in aerial and ground mode at scale-
2. The time delay for a fault in the middle of the
underground cable (i.e., 10 mi) obtained using ATP
simulation is Δtm is 50μs this example the
observedΔt0 is 40μs identifying the faulty-half
accurately;however,very high precision
isneededtocompare. Δtm and Δt0 It is also difficult to
accurately calculate Δt0 as fig 9 demonstrates
theproximity of the instants of initial peaks.
Fig. 9. Voltage s at bus S in aerial and ground
mode in scale-2 for a phase- -ground fault at 105
miles away from bus S in underground cable.
The proposed method in this paper uses SVMs
for faulty-half/section identification using the
normalized wavelet ener-gies,ENvk and normalized
transient current energies,ENik as input .the
SVM1output for faulty section identification gives -1
and the half-identifier svm2 for the cable is utilized
to determine the faulty -half. The faulty-half is
identifi ed as first half of the cable since the output of
the is . The proposed method overcomes the
precision problem pertinent to existing single-ended
traveling wave methods using wavelet transform and
Bewley diagram.
2) Cable Aging: The traveling wave velocity in
cables decreases with aging due to the increase in
cable inductance (L) [35]. The accuracy of single-
10. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 14 | P a g e
ended traveling wave- based fault location degrades
as the electromagnetic traveling wave velocity in the
cable changes during the years.
As an example, a phase -to-ground fault is
simulated in the aged underground cable located at
13 miles from the joint (i.e., 113 miles from bus S).
The aged underground is simulated by increasing the
relative permeability μr of each phase from 1 to
1.5.The fault conditions are δ=250 ,Rf =1Ω and
FIA=700. The observed Δt in the voltage WTC2 at the
bus s is 180 μs.
The traveling wave velocity calculated using
ATP software at 37.5 kHz in the aged underground
cable is mi/s.
However, the fault location calculated by using the
traveling Wave velocity in the original cable
(i.e.,0.98*105 mi/s) is:
Note that the fault location error is 9.1%. As
expected; the change in inductance due to aging
affects the traveling wave-velocity, subsequently
deteriorating the performance of the al-gorithm. This
shortcoming can be addressed by introducing a
correction factor, which translates the change in
cable param-eters to a change in velocity. Correction
factor can be deter-mined by carrying out site tests in
certain time intervals or by employing a parameter
estimation tool.
4.3 Single Line To Ground Fault
The circuit for simulating AC line fault for a
given transmission line is shown in Fig. 10. If the
circuit breaker is said to open then say switching
times are given for 0.6 to 0.65 sec, then it implies
that the circuit breaker closes at 0.6 sec and opens at
0.65 sec. So a fault period lies between 0.6 to 0.65
sec is observed on AC line. The fault voltage waves
and current waves of an AC line fault are obtained in
data acquisition box which was shown in Fig.
5.3&5.4. The reverse voltage travelling wave for the
fault line is calculated using
Vr = [Vac – Zc
* iac ]/2
Where, Vr = reverse voltage travelling wave.
Vac = voltage obtained during normal
operation
Iac = current obtained during normal
operation
Zc = surge impedance of the transmission
line.
Reverse voltage travelling wave appears in the
line only when, Zc> Zt or Zc<Z where Zc is the
characteristic impedance of the transmission line
where Zt is the terminating impedance of the
transmission line.
Line to ground fault on phase A
Fig.10 voltage signal during ac single line to ground
fault
The fault occurs at a distance of 200km from the
three phase source. The fault occurs from 0.6 seconds
to 0.65 seconds for a period of 0.05 seconds. In the
simulation diagram the block parameters and the
switching times of the breaker are adjusted to be
between 0.6 to 0.65 seconds. The wavelet modulus
maxima which are obtained for faulted signal in case
of a single line to ground fault are shown in Figures.
Fig. 11Wavelet modulus maxima signal for line to
ground fault
Fig.12 Wavelet modulus maxima signal for line to
ground fault
Fig.13 fault signal which occurred in line A
Fig.14 fault impedance trajectory signal for line to
ground fault
11. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 15 | P a g e
Fault Calculations: The value of the positive polared sample is obtained as N1=723.5 .The value of the negative polared sample is obtained as N2=723 .The total number of samples is obtained as N=1600 By knowing the values of N1, N2 and N, the value of Δt can be compared by using the equation shown below Δt=(N2-N1)/N Where (N2-N1) is the difference between the oppositely polared samples and N is the total number of samples.Δt is time delay between first two oppositely polared samples.The value of Δt is compared and is obtained as Δt= (723.5-723)/1600 s. Δt=0.00031s. The distance of the fault location is calculated by the following equation, L= (V*Δt) Where V is the speed of the travelling wave=299750 km/s. L is the distance at which single line to ground fault occurred.The fault distance is computed and is obtained as L=299750*0.00031 km L=93.36 km. Thus by using wavelet modulus maxima the fault distance is calculated. The fault is occurred at a distance of 93.36 km.
V. CONCLUSION
This paper proposes a single-ended traveling wave-based fault location method for a hybrid transmission line: an overhead line combined with an underground cable. Modal transformation and DWT are applied to the transient voltages recorded at the sending-end of overhead line. The normalized voltage wavelet energies and the normalized current energies are used for SVM faulty-section/half identification. The SVM classifiers use smaller set of inputs and are independent of fault type. The location of the fault is calculated by using the aerial mode voltage wavelets. The transient simulations are carried out using ATP software and the method is tested on MATLAB by using Wavelet Toolbox and SVM Toolbox. The performance of the proposed method is tested for various fault scenarios including different fault resistances, fault inception angles, fault locations, loading levels, non-linear high- impedance and non-ideal faults with satisfactory results. REFERENCES
[1] M. Kezunovic, “Smart fault location for smart grid,” IEEE Trans. Smart Grid, vol. 2, no. 1, pp. 11–22, Mar. 2011.
[2] P. K. Dash, S. R. Samantaray, and G. Panda, “Fault classification and section identification of an advanced series
compensated transmission line using support vector machine,” IEEE Trans. Power Del., vol. 22, no. 1, pp. 67–73, Jan. 2007.
[3] U. B. Parikh, B. Das, and R. P. Maheshwari, “Combined wavelet-SVM technique for fault zone detection in a series compensated transmission line,” IEEE Trans. Power Del., vol. 23, no. 4, pp. 1789–1794, Oct. 2008.
[4] A. A. Yusuffa, C. Fei, A. A. Jimoha, and J. L. Munda, “Fault location in a series compensated transmission line based on wavelet packet de-composition and support vector regression,” Elect. Power Syst. Res., vol. 81, no. 7, pp. 1258–1265, Apr. 2011.
[5] R. Salat and S. Osowski, “Accurate fault location in the power trans-mission line using support vector machine approach,” IEEE Trans. Power Syst., vol. 29, no. 2, pp. 979–986, May 2004.
[6] J. A. Jiang, C. L. Chuang, Y. C. Wang, C. H. Hung, J. Y. Wang, C.H Lee, and Y. T. Hsiao, “Hybrid framework for fault detection, clas-sification, and location Part I: Concept, structure, and methodology,” IEEE Trans. Power Del., vol. 26, no. 3, pp. 1988–1997, Jul. 2011.
H. J. A. Jiang, C. L. Chuang, Y. C. Wang, C. H. Hung, J. Y. Wang, C.H. Lee, and Y. T. Hsiao, “Hybrid framework for fault detection, clas-sification, and location Part II: Implementation and test results,” IEEE Trans. Power Del., vol. 26, no. 3, pp. 1999– 2008, Jul. 2011.
[7] X. Yang, M. S. Choi, S. J. Lee, C. W. Ten, and S. I. Lim, “Fault location for underground power cable using distributed parameter approach,” IEEE Trans. Power Syst., vol. 23, no. 4, pp. 1809–1816, Nov. 2008.
[8] Z. Xu and T. S. Sidhu, “Fault location method based on single-end measurements for underground cables,” IEEE Trans. Power Del., vol. 26, no. 4, pp. 2845–2854, Oct. 2011.
[9] M. S. Mashikian, R. Bansal, and R. B. Northorp, “Location and char-acterization of partial discharge sites in shielded power cables,” IEEE Trans. Power Del., vol. 5, no. 2, pp. 833–839, Apr. 1990.
[10] H. E. Gallagher, D. R. Mize, and A. F. Dickerson, “Fault location system for transmission-type cable,” IEEE Trans. Power App. Syst., vol. PAS-101, no. 6, pp. 1700–1710, Jun. 1982.
[11] C. M. Wiggins, D. E. Thomas, T. M. Salas, F. S. Nickel, and H. W. Ng, “A novel concept for URD cable fault location,”
12. K. Durga Syam Prasad et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 7( Version 4), July 2014, pp.05-16
www.ijera.com 16 | P a g e
IEEE Trans. Power Del., vol. 9, no. 1, pp. 591–597, Jan. 1994.
[12] N. Inoue, T. T. Tsunekage, and S. Sakai, “On-line fault location system for 66 kV underground cables with fast O/E and fast A/D technique,” IEEE Trans. Power Del., vol. 9, no. 1, pp. 579–584, Jan. 1994.
[13] F. H. Magnago and A. Abur, “Fault location using wavelets,” IEEE Trans. Power Del., vol. 13, no. 4, pp. 1475–1480, Oct. 1998.
[14] W. Zhao, Y. H. Song, and W. R. Chen, “Improved GPS traveling wave fault locator for power cables by using wavelet analysis,” Electr. Power Energy Syst., vol. 23, no. 5, pp. 403–411, Jun. 2001.
[15] M. Gilany, D. K. Ibrahim, and E. S. T. Eldin, “Traveling-wave-based fault-location scheme for multiend-aged underground cable system,” IEEE Trans. Power Del., vol. 22, no. 1, pp. 82–89, Jan. 2007.
[19] J. Sadeh and H. Afradi, “A new and accurate fault location algo-rithm for combined transmission lines using adaptive network-based fuzzy inference system,” Elect. Power Syst. Res., vol. 79, no. 11, pp. 1538–1545, Nov. 2009.
[20] D. Spoor and J. G. Zhu, “Improved single- ended traveling-wave fault-location algorithm based on experience with conventional substation transducers,” IEEE Trans. Power Del., vol. 21, no. 3, pp. 1714– 1720, Jul. 2006.
[21] M. J. Reddy and D. K. Mohanta, “A wavelet-fuzzy combined approach for classification and location of transmission line faults,” Int. J. Electr. Power Energy Syst., vol. 29, no. 9, pp. 669–678, Nov. 2007.
[22] D. Chanda, N. K. Kishore, and A. K. Sinha, “A wavelet multiresolu-tion analysis for location of faults on transmission lines,” Int. J. Electr. Power Energy Syst., vol. 25, no. 1, pp. 59–69, Jan. 2003.
[23] C. K. Jung, K. H. Kim, J. B. Lee, and B. Klöckl, “Wavelet and neuro-fuzzy based fault location for combined transmission systems,” Int. J. Electr. Power Energy Syst., vol. 29, no. 6, pp. 445–454, Jul. 2007.
[24] I. Niazy and J. Sadeh, “A new single ended fault location algorithm for combined transmission line considering fault clearing transients without using line parameters,” Int. J. Electr. Power Energy Syst., vol. 44, no. 1, pp. 616–623, Jan. 2013.
[25] C. K. Jung, J. B. Lee, X. H. Wang, and Y. H. Song, “Wavelet based noise cancellation technique for fault location on underground
power cables,” Elect. Power Syst. Res., vol. 77, no. 10, pp. 1342–1369, Aug. 2007.
[26] W. Zhao, Y. H. Song, and W. R. Chen, “Improved GPS traveling wave fault locator for power cables by using wavelet analysis,” Int. J. Electr. Power Energy Syst., vol. 23, no. 5, pp. 403–411, Jun. 2001.
[27] P. S. Bhowmik, P. Purkait, and K. Bhattacharya, “A novel wavelet transform aided neural network based transmission line fault analysis method,” Int. J. Electr. Power Energy Syst., vol. 31, no. 5, pp. 213– 219, Jun. 2009.