Transmission and distribution lines are vital links between generating units and consumers. They are
exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high, which has to be
immediately taken care of in order to minimize damage caused by it. This paper focuses on detecting the faults
on electric power transmission lines using artificial neural networks. A feed forward neural network is
employed, which is trained with back propagation algorithm. Analysis on neural networks with varying number
of hidden layers and neurons per hidden layer has been provided to validate the choice of the neural networks
in each step. The developed neural network is capable of detecting single line to ground and double line to
ground for all the three phases. Simulation is done using MATLAB Simulink to demonstrate that artificial
neural network based method are efficient in detecting faults on transmission lines and achieve satisfactory
performances. A 300km, 25kv transmission line is used to validate the proposed fault detection system.
Hardware implementation of neural network is done on TMS320C6713.
IRJET- Three Phase Line Fault Detection using Artificial Neural NetworkIRJET Journal
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This document describes a study that uses an artificial neural network to detect and classify faults on electric power transmission lines. The researchers modeled a three-phase transmission line system in MATLAB/Simulink and simulated different types of faults at various locations and resistances. Voltage and current data from the simulations were extracted and preprocessed as inputs to train an artificial neural network. The trained network was then able to detect and classify faults with 95.7% accuracy, demonstrating its effectiveness. Previous methods had issues with stability and slow dynamic response, but the artificial neural network approach provided improved fault detection performance.
IRJET- A Simple Approach to Identify Power System Transmission Line Faults us...IRJET Journal
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This paper presents a Probabilistic Neural Network (PNN) approach for identifying and classifying faults on power transmission lines. The PNN is trained on voltage waveform data simulated using Electromagnetic Transient Program (EMTP) software for different fault types and locations on a 150km transmission line. Only two sets of simulated data are used to train the PNN, requiring less computation than other methods that preprocess data. The trained PNN is able to accurately identify and classify fault types based on the voltage waveform, which helps ensure reliable power transmission by isolating only faulty lines or phases.
- Motivated Electrical Engineer with 1 year of experience in power transmission planning, generator interconnection studies, and NERC compliance studies seeking a position in power systems engineering.
- Master's degree in Electrical Engineering with a focus on power systems and experience in software development.
- Skilled in transmission planning tools like PSSE and experience analyzing power flows, contingencies, and reliability standards.
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
- This paper proposes a new technique of using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) based on Clarkeâs 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 Clarkeâs 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.
Ijeee 28-32-accurate fault location estimation in transmission linesKumar Goud
Â
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-linearityâs 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. Itâs 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.
S-MAC is a medium access control (MAC) protocol designed for wireless sensor networks to improve energy efficiency. It reduces energy waste from sources like idle listening, collisions, overhearing unnecessary traffic, and control packet overhead. S-MAC establishes low-duty-cycle operation where nodes periodically sleep to reduce idle listening. It also introduces coordinated sleeping among neighboring nodes to reduce control overhead and enable traffic-adaptive wakeups. S-MAC was implemented and evaluated on wireless sensor nodes, demonstrating significant energy savings compared to IEEE 802.11 while achieving good scalability and collision avoidance.
IRJET- Three Phase Line Fault Detection using Artificial Neural NetworkIRJET Journal
Â
This document describes a study that uses an artificial neural network to detect and classify faults on electric power transmission lines. The researchers modeled a three-phase transmission line system in MATLAB/Simulink and simulated different types of faults at various locations and resistances. Voltage and current data from the simulations were extracted and preprocessed as inputs to train an artificial neural network. The trained network was then able to detect and classify faults with 95.7% accuracy, demonstrating its effectiveness. Previous methods had issues with stability and slow dynamic response, but the artificial neural network approach provided improved fault detection performance.
IRJET- A Simple Approach to Identify Power System Transmission Line Faults us...IRJET Journal
Â
This paper presents a Probabilistic Neural Network (PNN) approach for identifying and classifying faults on power transmission lines. The PNN is trained on voltage waveform data simulated using Electromagnetic Transient Program (EMTP) software for different fault types and locations on a 150km transmission line. Only two sets of simulated data are used to train the PNN, requiring less computation than other methods that preprocess data. The trained PNN is able to accurately identify and classify fault types based on the voltage waveform, which helps ensure reliable power transmission by isolating only faulty lines or phases.
- Motivated Electrical Engineer with 1 year of experience in power transmission planning, generator interconnection studies, and NERC compliance studies seeking a position in power systems engineering.
- Master's degree in Electrical Engineering with a focus on power systems and experience in software development.
- Skilled in transmission planning tools like PSSE and experience analyzing power flows, contingencies, and reliability standards.
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
- This paper proposes a new technique of using discrete wavelet transform (DWT) and back-propagation neural network (BPNN) based on Clarkeâs 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 Clarkeâs 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.
Ijeee 28-32-accurate fault location estimation in transmission linesKumar Goud
Â
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-linearityâs 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. Itâs 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.
S-MAC is a medium access control (MAC) protocol designed for wireless sensor networks to improve energy efficiency. It reduces energy waste from sources like idle listening, collisions, overhearing unnecessary traffic, and control packet overhead. S-MAC establishes low-duty-cycle operation where nodes periodically sleep to reduce idle listening. It also introduces coordinated sleeping among neighboring nodes to reduce control overhead and enable traffic-adaptive wakeups. S-MAC was implemented and evaluated on wireless sensor nodes, demonstrating significant energy savings compared to IEEE 802.11 while achieving good scalability and collision avoidance.
The main purpose of the project is to detect the location of fault in underground cable lines from the base station in kilometers using a Renesas micro-controller. This project uses the standard concept of Ohms law i.e., when a low DC voltage is applied at the feeder end through a series resistor to the Cable lines, then current would vary depending upon the location of fault in the short circuited cable. Both the methods use voltage convertor, microcontroller and potentiometer to find the fault location under unsymmetrical faults.
In the urban areas, the electrical cables run in undergrounds instead of overhead lines. Whenever the fault occurs in underground cable it is difficult to detect the exact location of the fault for process of repairing that particular cable and long outage of power supply can cause the power distributors and retailers heavy loss of revenue and discomfort of the customers. Therefore, a quick detection and rectification of the faults is a major drawback for other power distributors and retailers. The proposed system finds the exact location of the fault using GSM Module and IOT
This system uses a Renesas micro-controller and a rectified power supply. Here the current sensing circuits made with combination of resistors are interfaced to Renesas controller with help of the ADC device for providing digital data to the microcontroller representing the cable length in KMâs. The fault creation is made by the set of switches. The relays are controlled by the relay driver IC which is used for switching the power sequentially to all the lines. A 16x2 LCD display connected to the microcontroller to display the information.
In case of short circuit (Line to Ground), the voltage across series resistors changes accordingly, which is then fed to an ADC to develop precise digital data to a programmed Renesas board that further displays fault location in kilometers.
The project future can be implemented by using capacitor in an ac circuit to measure the impedance which can even locate the open circuited cable.
Backpropagation Neural Network Modeling for Fault Location in Transmission Li...ijeei-iaes
Â
In this topic research was provided about the backpropagation neural network to detect fault location in transmission line 150 kV between substation to substation. The distance relay is one of the good protective device and safety devices that often used on transmission line 150 kV. The disturbances in power system are used distance relay protection equipment in the transmission line. However, it needs more increasing large load and network systems are increasing complex. The protection system use the digital control, in order to avoid the error calculation of the distance relay impedance settings and spent time will be more efficient. Then backpropagation neural network is a computational model that uses the training process that can be used to solve the problem of work limitations of distance protection relays. The backpropagation neural network does not have limitations cause of the impedance range setting. If the output gives the wrong result, so the correct of the weights can be minimized and also the response of galat, the backpropagation neural network is expected to be closer to the correct value. In the end, backpropagation neural network modeling is expected to detect the fault location and identify operational output current circuit breaker was tripped it. The tests are performance with interconnected system 150 kV of Riau Region.
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 the design of a wireless cortical neural recording system with bidirectional data transmission. It includes:
1) The development of a transcutaneous two-way wireless power and data link for neural recording, with wireless powering at 1.25Mbps and reverse telemetry from the implant at rates over 3Mbps to stream 16 channels of raw neural data.
2) The use of an integer-N PLL in the implant circuitry to generate the reverse telemetry carrier frequency as a multiple of the power carrier frequency, allowing simultaneous reverse telemetry from multiple implants.
3) Optimization of the dual inductive link design for power transmission and reverse telemetry using an analytic model to maximize coupling between the data coils within
A Survey- Energy Efficient Techniques in WBANIRJET Journal
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This document summarizes research on energy efficient techniques in wireless body area networks (WBANs). It discusses how WBANs use sensor nodes connected to or implanted in the human body to remotely monitor health. However, the sensor nodes have limited battery life so energy efficiency is important. The document reviews several medium access control (MAC) protocols designed to minimize energy consumption, including SMAC, WISEMAC, an adaptive energy efficient MAC protocol, and a dynamic duty cycle algorithm. It finds the latter two protocols are more energy efficient than SMAC and WISEMAC based on simulations. The document also outlines sources of energy waste in WBANs and applications of WBAN technology in both medical and non-medical fields.
The document discusses wireless sensor networks (WSNs) and energy efficiency in WSNs. It defines WSNs and their components. It identifies the major sources of energy waste in WSNs as idle listening, overhearing, collisions, and control packets. It describes general approaches to energy saving, including duty cycling and data-driven methods. It also discusses various medium access control (MAC) protocols for WSNs like S-MAC, T-MAC, Ό-MAC, and DEE-MAC. Finally, it covers applications, standards, advantages and disadvantages of WSNs.
Development of a Wavelet-ANFIS based fault location system for underground po...IOSRJEEE
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In the past decade, electricity demand has increased rapidly in metropolitan areas. All over the world, large scale underground power cable installations networks are replacing overhead transmission lines due to environmental concerns in densely populated areas. Underground cable systems are manufactured to have long life with reliability. However, the useful life span of these cables is not infinite. The increase in failure rates and system breakdowns on older underground power cables are now adversely impacting system reliability and many losses involved; therefore it is readily apparent that necessary action has to be taken to manage the consequences of this trend. In this paper, a method that combines wavelets and Neuro-fuzzy technique for fault location and identification is proposed. A 10km, 34.5KV, 50Hz power transmission line model was developed and different faults and locations simulated, and then certain selected features of the wavelet transformed signals were extracted to develop an ANFIS for fault location. Comparison of the ANFIS output values and the actual values show that the percentage error was established to be less than 1%. Thus, it can be concluded that the wavelet-ANFIS technique is accurate enough to be used in identifying and locating underground power line faults.
Brief Literature Review on Phasor Based Transmission Line Fault Location Algo...sarasijdas
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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.
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.
A transient current based micro grid connected power system protection scheme...IJECEIAES
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Micro-grids comprise Distributed Energy Resources (DERâs) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DERâs provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DERâs from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network. This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.
Opportunistic routing algorithm for relay node selection in wireless sensor n...LogicMindtech Nologies
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NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
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.
Artificial Neural Network Based Fault Classifier for Transmission Line Protec...IJERD Editor
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This paper presents a method for classification of transmission line faults based on Artificial Neural Network (ANN).Samples of prefault and postfault three phase currents taken at one end of transmission line are used as ANN inputs. Simulation studies have been carried out extensively on two power system models: one in which the transmission line is fed from one end and another, in which the transmission line is fed from two ends. Different types of faults at different operating conditions have been considered for carrying out simulation studies. The simulation results confirm the feasibility of the proposed approach.
This document analyzes the optimal positioning of superconducting fault current limiters (SFCLs) in smart grids. It simulates different fault scenarios in a model smart grid containing distributed generation from wind farms. It finds that installing an SFCL at the substation or distribution network increases fault current from wind farms. The best performance is achieved by installing a single SFCL at the point of integration between the wind farm and the grid. This location limits fault current from both the wind farm and the main power system effectively without negative impacts. The analysis suggests strategic placement of SFCLs at integration points is most efficient for protecting multiple distributed resources in smart grids.
This document proposes a new energy efficient MAC protocol called E-BMA for wireless sensor networks. It aims to minimize idle times during contention periods to improve energy efficiency, especially for low to medium traffic loads. The E-BMA protocol is simulated and its energy consumption is compared to TDMA, EA-TDMA, and BMA protocols. The results show that E-BMA performs better and consumes less energy than the other protocols under different traffic conditions.
Automatic Fault Detection System with IOT BasedYogeshIJTSRD
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The fault location is an important part for any transmission line and distribution system. The location of fault is difficult task sometimes it takes lot of times needed for the exact location of the fault. The exact fault location can help the service man to overcome the fault free system in very less time. In this paper we are able to detect the fault range in easy way using the ESP module and the message is transferred on the mobile. This project is cost effective and reliable. Fast fault detection provide the protection of equipment before any significant damage. Er. Sanjeev Kumar | Mohd Mehraj Khan | Nadeem | Shailesh Kumar Yadav | Harsh Gupta "Automatic Fault Detection System with IOT Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43806.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/43806/automatic-fault-detection-system-with-iot-based/er-sanjeev-kumar
Fault detection and diagnosis of high speed switching devices in power invertereSAT Journals
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Abstract
Power electronic based inverters are the major components in industry. A fault diagnostics framework composed of a pattern recognition system, having machine learning technology as its integral part is utilized for failure detection of different switches and tracing multiple types of faults in an inverter. Hardware point of view power electronics inverter can be considered to be the weakest link. Hence, this work is carried on detecting faults and classifies which switches in the inverter cause the fault. Diagnosis can help to avoid unplanned breakdown, to make possible to run an emergency operation in case of a fault. On the basis of theoretical foundations of electronic power inverter a simulation model has been developed to simulate the healthy condition and all single-switch open circuit faults. The generated signal is processed using Discrete Wavelet Transform (DWT) and Fuzzy Inference Logic (FIL). A smart and accurate classification of faults is obtained using simulation results, which are tested on a wide operation domain and various load conditions.
Keywords: Fault Diagnosis, DWT, Fuzzy Logic, Artificial Intelligence (AI).
This document summarizes research into improving transient stability in power transmission systems using a Static VAR Compensator (SVC) with a hybrid PI-Fuzzy Logic controller. It begins with an introduction to Flexible AC Transmission Systems (FACTS) and the role of SVC devices in voltage control and reactive power compensation. It then describes modeling an SVC and the operating principles of conventional PI control. The limitations of PI control for nonlinear systems are discussed. The document proposes a hybrid PI-Fuzzy Logic controller to combine the advantages of both. Simulation results using MATLAB on a 2-machine 3-bus test system show the hybrid controller improves performance during disturbances over PI or Fuzzy Logic control alone.
This document summarizes a study that analyzed the performance of vertical skirted strip footings on slopes using the finite element software PLAXIS 2D. Various parameters were considered, including the vertical load, depth of footing embedment, distance of footing from crest, ratio of skirt depth to footing width, and configuration of the skirt (one side, both sides, unequal sides). The results showed that skirted foundations significantly improved the bearing capacity compared to unskirted foundations. Bearing capacity increased with deeper skirt depths. Footings at the crest also showed improved bearing capacity. Footing embedment depth did not affect bearing capacity. The study provides insights into using skirted foundations to improve slope stability and bearing capacity
This document describes the design of an electronic voting response system for use in parliamentary settings. The system was designed to address issues with traditional voice voting methods, such as time wasted, inaccuracy in discerning the majority view, and potential for bias or conflict. The system uses an ATmega328P microcontroller to control wireless keypads with yes and no buttons and a liquid crystal display output unit. Each keypad transmits votes via radio frequency to the display unit. The system is a prototype designed for two respondents but could be scaled up at low cost. It aims to provide a more efficient, accurate and unbiased method for capturing parliamentary votes.
The document presents the results of an experimental investigation into the performance of a laboratory screw jack. Various tests were conducted by applying different loads between 450N and 100N to the screw jack. For each load, the mechanical advantage, velocity ratio, and mechanical efficiency were calculated. The results showed that the mechanical efficiency of the screw jack was always less than 50% since the mechanical advantage and velocity ratio were less than half. Frictional forces in the screw and base contributed to the efficiency not remaining constant across different loads.
This document discusses different algorithms for task scheduling in cloud computing environments based on various quality of service (QoS) parameters. It summarizes several QoS-based scheduling algorithms including QDA, Improved Cost Based, PAPRIKA, ANT Colony, CMultiQoSSchedule, and SHEFT Workflow. It also provides a comparative table of these algorithms and discusses the various metrics considered by QoS-based scheduling algorithms like time, cost, makespan, trust, and resource utilization. The paper concludes that scheduling is an important factor for cloud environments and that existing algorithms can be improved by considering additional parameters like trust values, execution rates, and success rates.
The main purpose of the project is to detect the location of fault in underground cable lines from the base station in kilometers using a Renesas micro-controller. This project uses the standard concept of Ohms law i.e., when a low DC voltage is applied at the feeder end through a series resistor to the Cable lines, then current would vary depending upon the location of fault in the short circuited cable. Both the methods use voltage convertor, microcontroller and potentiometer to find the fault location under unsymmetrical faults.
In the urban areas, the electrical cables run in undergrounds instead of overhead lines. Whenever the fault occurs in underground cable it is difficult to detect the exact location of the fault for process of repairing that particular cable and long outage of power supply can cause the power distributors and retailers heavy loss of revenue and discomfort of the customers. Therefore, a quick detection and rectification of the faults is a major drawback for other power distributors and retailers. The proposed system finds the exact location of the fault using GSM Module and IOT
This system uses a Renesas micro-controller and a rectified power supply. Here the current sensing circuits made with combination of resistors are interfaced to Renesas controller with help of the ADC device for providing digital data to the microcontroller representing the cable length in KMâs. The fault creation is made by the set of switches. The relays are controlled by the relay driver IC which is used for switching the power sequentially to all the lines. A 16x2 LCD display connected to the microcontroller to display the information.
In case of short circuit (Line to Ground), the voltage across series resistors changes accordingly, which is then fed to an ADC to develop precise digital data to a programmed Renesas board that further displays fault location in kilometers.
The project future can be implemented by using capacitor in an ac circuit to measure the impedance which can even locate the open circuited cable.
Backpropagation Neural Network Modeling for Fault Location in Transmission Li...ijeei-iaes
Â
In this topic research was provided about the backpropagation neural network to detect fault location in transmission line 150 kV between substation to substation. The distance relay is one of the good protective device and safety devices that often used on transmission line 150 kV. The disturbances in power system are used distance relay protection equipment in the transmission line. However, it needs more increasing large load and network systems are increasing complex. The protection system use the digital control, in order to avoid the error calculation of the distance relay impedance settings and spent time will be more efficient. Then backpropagation neural network is a computational model that uses the training process that can be used to solve the problem of work limitations of distance protection relays. The backpropagation neural network does not have limitations cause of the impedance range setting. If the output gives the wrong result, so the correct of the weights can be minimized and also the response of galat, the backpropagation neural network is expected to be closer to the correct value. In the end, backpropagation neural network modeling is expected to detect the fault location and identify operational output current circuit breaker was tripped it. The tests are performance with interconnected system 150 kV of Riau Region.
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 the design of a wireless cortical neural recording system with bidirectional data transmission. It includes:
1) The development of a transcutaneous two-way wireless power and data link for neural recording, with wireless powering at 1.25Mbps and reverse telemetry from the implant at rates over 3Mbps to stream 16 channels of raw neural data.
2) The use of an integer-N PLL in the implant circuitry to generate the reverse telemetry carrier frequency as a multiple of the power carrier frequency, allowing simultaneous reverse telemetry from multiple implants.
3) Optimization of the dual inductive link design for power transmission and reverse telemetry using an analytic model to maximize coupling between the data coils within
A Survey- Energy Efficient Techniques in WBANIRJET Journal
Â
This document summarizes research on energy efficient techniques in wireless body area networks (WBANs). It discusses how WBANs use sensor nodes connected to or implanted in the human body to remotely monitor health. However, the sensor nodes have limited battery life so energy efficiency is important. The document reviews several medium access control (MAC) protocols designed to minimize energy consumption, including SMAC, WISEMAC, an adaptive energy efficient MAC protocol, and a dynamic duty cycle algorithm. It finds the latter two protocols are more energy efficient than SMAC and WISEMAC based on simulations. The document also outlines sources of energy waste in WBANs and applications of WBAN technology in both medical and non-medical fields.
The document discusses wireless sensor networks (WSNs) and energy efficiency in WSNs. It defines WSNs and their components. It identifies the major sources of energy waste in WSNs as idle listening, overhearing, collisions, and control packets. It describes general approaches to energy saving, including duty cycling and data-driven methods. It also discusses various medium access control (MAC) protocols for WSNs like S-MAC, T-MAC, Ό-MAC, and DEE-MAC. Finally, it covers applications, standards, advantages and disadvantages of WSNs.
Development of a Wavelet-ANFIS based fault location system for underground po...IOSRJEEE
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In the past decade, electricity demand has increased rapidly in metropolitan areas. All over the world, large scale underground power cable installations networks are replacing overhead transmission lines due to environmental concerns in densely populated areas. Underground cable systems are manufactured to have long life with reliability. However, the useful life span of these cables is not infinite. The increase in failure rates and system breakdowns on older underground power cables are now adversely impacting system reliability and many losses involved; therefore it is readily apparent that necessary action has to be taken to manage the consequences of this trend. In this paper, a method that combines wavelets and Neuro-fuzzy technique for fault location and identification is proposed. A 10km, 34.5KV, 50Hz power transmission line model was developed and different faults and locations simulated, and then certain selected features of the wavelet transformed signals were extracted to develop an ANFIS for fault location. Comparison of the ANFIS output values and the actual values show that the percentage error was established to be less than 1%. Thus, it can be concluded that the wavelet-ANFIS technique is accurate enough to be used in identifying and locating underground power line faults.
Brief Literature Review on Phasor Based Transmission Line Fault Location Algo...sarasijdas
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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.
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.
A transient current based micro grid connected power system protection scheme...IJECEIAES
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Micro-grids comprise Distributed Energy Resources (DERâs) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DERâs provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DERâs from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network. This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.
Opportunistic routing algorithm for relay node selection in wireless sensor n...LogicMindtech Nologies
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NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
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.
Artificial Neural Network Based Fault Classifier for Transmission Line Protec...IJERD Editor
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This paper presents a method for classification of transmission line faults based on Artificial Neural Network (ANN).Samples of prefault and postfault three phase currents taken at one end of transmission line are used as ANN inputs. Simulation studies have been carried out extensively on two power system models: one in which the transmission line is fed from one end and another, in which the transmission line is fed from two ends. Different types of faults at different operating conditions have been considered for carrying out simulation studies. The simulation results confirm the feasibility of the proposed approach.
This document analyzes the optimal positioning of superconducting fault current limiters (SFCLs) in smart grids. It simulates different fault scenarios in a model smart grid containing distributed generation from wind farms. It finds that installing an SFCL at the substation or distribution network increases fault current from wind farms. The best performance is achieved by installing a single SFCL at the point of integration between the wind farm and the grid. This location limits fault current from both the wind farm and the main power system effectively without negative impacts. The analysis suggests strategic placement of SFCLs at integration points is most efficient for protecting multiple distributed resources in smart grids.
This document proposes a new energy efficient MAC protocol called E-BMA for wireless sensor networks. It aims to minimize idle times during contention periods to improve energy efficiency, especially for low to medium traffic loads. The E-BMA protocol is simulated and its energy consumption is compared to TDMA, EA-TDMA, and BMA protocols. The results show that E-BMA performs better and consumes less energy than the other protocols under different traffic conditions.
Automatic Fault Detection System with IOT BasedYogeshIJTSRD
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The fault location is an important part for any transmission line and distribution system. The location of fault is difficult task sometimes it takes lot of times needed for the exact location of the fault. The exact fault location can help the service man to overcome the fault free system in very less time. In this paper we are able to detect the fault range in easy way using the ESP module and the message is transferred on the mobile. This project is cost effective and reliable. Fast fault detection provide the protection of equipment before any significant damage. Er. Sanjeev Kumar | Mohd Mehraj Khan | Nadeem | Shailesh Kumar Yadav | Harsh Gupta "Automatic Fault Detection System with IOT Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43806.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/43806/automatic-fault-detection-system-with-iot-based/er-sanjeev-kumar
Fault detection and diagnosis of high speed switching devices in power invertereSAT Journals
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Abstract
Power electronic based inverters are the major components in industry. A fault diagnostics framework composed of a pattern recognition system, having machine learning technology as its integral part is utilized for failure detection of different switches and tracing multiple types of faults in an inverter. Hardware point of view power electronics inverter can be considered to be the weakest link. Hence, this work is carried on detecting faults and classifies which switches in the inverter cause the fault. Diagnosis can help to avoid unplanned breakdown, to make possible to run an emergency operation in case of a fault. On the basis of theoretical foundations of electronic power inverter a simulation model has been developed to simulate the healthy condition and all single-switch open circuit faults. The generated signal is processed using Discrete Wavelet Transform (DWT) and Fuzzy Inference Logic (FIL). A smart and accurate classification of faults is obtained using simulation results, which are tested on a wide operation domain and various load conditions.
Keywords: Fault Diagnosis, DWT, Fuzzy Logic, Artificial Intelligence (AI).
This document summarizes research into improving transient stability in power transmission systems using a Static VAR Compensator (SVC) with a hybrid PI-Fuzzy Logic controller. It begins with an introduction to Flexible AC Transmission Systems (FACTS) and the role of SVC devices in voltage control and reactive power compensation. It then describes modeling an SVC and the operating principles of conventional PI control. The limitations of PI control for nonlinear systems are discussed. The document proposes a hybrid PI-Fuzzy Logic controller to combine the advantages of both. Simulation results using MATLAB on a 2-machine 3-bus test system show the hybrid controller improves performance during disturbances over PI or Fuzzy Logic control alone.
This document summarizes a study that analyzed the performance of vertical skirted strip footings on slopes using the finite element software PLAXIS 2D. Various parameters were considered, including the vertical load, depth of footing embedment, distance of footing from crest, ratio of skirt depth to footing width, and configuration of the skirt (one side, both sides, unequal sides). The results showed that skirted foundations significantly improved the bearing capacity compared to unskirted foundations. Bearing capacity increased with deeper skirt depths. Footings at the crest also showed improved bearing capacity. Footing embedment depth did not affect bearing capacity. The study provides insights into using skirted foundations to improve slope stability and bearing capacity
This document describes the design of an electronic voting response system for use in parliamentary settings. The system was designed to address issues with traditional voice voting methods, such as time wasted, inaccuracy in discerning the majority view, and potential for bias or conflict. The system uses an ATmega328P microcontroller to control wireless keypads with yes and no buttons and a liquid crystal display output unit. Each keypad transmits votes via radio frequency to the display unit. The system is a prototype designed for two respondents but could be scaled up at low cost. It aims to provide a more efficient, accurate and unbiased method for capturing parliamentary votes.
The document presents the results of an experimental investigation into the performance of a laboratory screw jack. Various tests were conducted by applying different loads between 450N and 100N to the screw jack. For each load, the mechanical advantage, velocity ratio, and mechanical efficiency were calculated. The results showed that the mechanical efficiency of the screw jack was always less than 50% since the mechanical advantage and velocity ratio were less than half. Frictional forces in the screw and base contributed to the efficiency not remaining constant across different loads.
This document discusses different algorithms for task scheduling in cloud computing environments based on various quality of service (QoS) parameters. It summarizes several QoS-based scheduling algorithms including QDA, Improved Cost Based, PAPRIKA, ANT Colony, CMultiQoSSchedule, and SHEFT Workflow. It also provides a comparative table of these algorithms and discusses the various metrics considered by QoS-based scheduling algorithms like time, cost, makespan, trust, and resource utilization. The paper concludes that scheduling is an important factor for cloud environments and that existing algorithms can be improved by considering additional parameters like trust values, execution rates, and success rates.
This document summarizes a paper that presents a novel method for determining the optimal location of Flexible AC Transmission System (FACTS) controllers in a multi-machine power system using a Fuzzy Controlled Genetic Algorithm (FCGA). The proposed algorithm aims to simultaneously optimize the location, type, and rated values of FACTS controllers while minimizing the overall system cost, which includes generation and investment costs. The algorithm is tested on IEEE 14-bus and 30-bus test systems, incorporating thyristor-controlled series compensator (TCSC) and unified power flow controller (UPFC) devices. Simulation results show the obtained solution is feasible and accurate for solving the optimal power flow problem.
This document summarizes a study on the body composition of children participating in regular football, cricket, and gymnastics training. The study aimed to compare the anthropometric and body composition status of children in these three sports. Body composition measurements including body fat percentage, fat mass, and lean mass were taken for children in each sport. Statistical analysis found that footballers had significantly lower body fat percentage and fat mass than cricketers but did not differ significantly in lean mass. Footballers also had significantly lower body fat percentage and fat mass than cricketers as well as significantly higher lean mass. Gymnasts had significantly lower body fat percentage and fat mass than cricketers but did not differ significantly in lean mass. The study concluded that footballers generally had a better body
This document presents a new approach for human identification using sclera recognition. It begins with background on sclera and challenges with sclera recognition. It then describes the proposed methodology which includes sclera segmentation, feature extraction using Gabor filtering, and recognition using Bayesian classification. Experimental results show the false accept and reject rates for the approach. It concludes that sclera recognition is promising for human identification and can achieve accuracy comparable to iris recognition in visible light. The proposed approach uses Bayesian classification for recognition, which is more effective than previous matching score methods.
This document provides an overview of digital image steganography and steganalysis. It discusses various image steganography techniques including least significant bit modification in the spatial domain, and algorithms like JSteg and F5 that operate in the transform domain. It also covers hybrid techniques like patchwork and spread spectrum. The document compares the techniques based on parameters like invisibility, bit rate, and robustness. Finally, it discusses steganalysis methods for detecting hidden information in images, including techniques based on higher-order image statistics.
1) The document reviews land acquisition policies and processes used in various countries around the world. It examines studies that analyzed land acquisition practices in countries like India, China, Nigeria, Malaysia, Mozambique, Ghana, Zambia, Tanzania, Bangladesh, and Vietnam.
2) The studies found that compensation provided to land owners for acquisition varied significantly between countries and sometimes within countries. Valuation methods also differed, though market value was commonly used.
3) No single best practice for land acquisition and compensation was identified. The document concludes that developing a transparent framework informed by principles, processes, and mechanisms could help improve compensation systems.
89 jan-roger linna - 7032576 - capillary heating control and fault detectio...Mello_Patent_Registry
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Jan-Roger Linna, John Paul Mello - Capillary Heating Control and Fault Detection System and Methodology for Fuel System in an Internal Combustion Engine
The document discusses the use of shunt active filters to mitigate current harmonics in power systems. It analyzes the performance of a shunt active filter controlled by a PI controller and fuzzy logic controller (FLC) under normal and increased load conditions with balanced and unbalanced source voltages. The main points are:
A) Shunt active filters inject compensating current to make the source current sinusoidal and maintain unity power factor.
B) Both PI and FLC controllers perform well under balanced voltages but FLC provides better compensation under unbalanced voltages.
C) The FLC with a triangular membership function offers superior results compared to the PI controller in mitigating current harmonics.
1. The document examines a local Nigerian game called "tsorry checkerboard" and applies group theory concepts.
2. The game is played on a 2x2 board with each player having up to 3 pieces, and the goal is to line up all three of one's pieces horizontally, vertically, or diagonally.
3. The possible moves of each piece (vertical, horizontal, diagonal, or staying in place) form a Klein four-group, satisfying the group properties of closure, associativity, identity, and inverses. Therefore, group theory can be applied to model the game.
The document discusses an energy efficient geographic routing protocol called Energy Efficient Geographic Adaptive Fidelity (EEGAF) for wireless sensor networks. It summarizes the basic Geographic Adaptive Fidelity (GAF) protocol and then proposes EEGAF, which improves on GAF in two ways: 1) It enhances the discovery phase to reduce energy used by nodes during discovery. 2) It uses a location-aware multicast routing protocol called Location Aided Routing (LAR) for data transmission, which decreases energy consumption and optimizes network lifetime. The document evaluates EEGAF using MATLAB simulations and finds it performs better than GAF in terms of network lifetime, energy efficiency, and quality of service metrics like throughput and routing overhead.
This document presents a hybrid algorithm that combines Apriori Growth and FP-Split Tree algorithms for web usage mining. The algorithm has two phases: 1) It constructs an FP-Split Tree from web logs in a single pass, reducing complexity compared to FP-Tree which requires two passes. 2) It mines frequent patterns from the FP-Split Tree using an Apriori Growth approach instead of FP-Growth to avoid repeatedly recreating trees. The algorithm was tested on university website logs and showed better performance than traditional FP-Tree and Apriori methods, as it was faster at extracting frequent patterns for different support counts.
The document discusses improving power system performance using Flexible AC Transmission System (FACTS) devices. It describes three types of FACTS devices: Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), and Unified Power Flow Controller (UPFC). The SVC and TCSC are able to control voltage and improve the voltage profile. Simulations showed adding FACTS devices decreased power losses and improved the voltage level. The UPFC can simultaneously control parameters like line impedance, voltage, and phase angle to regulate power flow.
This document discusses the importance of methodology in scientific research papers that aim to apply science and technology to address millennium challenges. It defines methodology as the framework and methods used in a research study. The document examines key components of methodology, including research design, study population, variables, sampling techniques, sample size determination, data collection methods, and data analysis. It provides examples for how to determine these methodological components and stresses that applying the appropriate methodology is essential for producing valid, high-quality research that can help solve important problems.
This document presents a new segmentation technique for brain MRI images and compares it to existing techniques. The proposed technique is a two-stage brain extraction algorithm (2D-BEA) that first removes noise and enhances brain boundaries, then uses morphological operations to extract the brain region. It is shown to accurately extract the brain from MRI images. The technique is then compared to other segmentation methods like thresholding, edge detection, fuzzy c-means clustering, and k-means clustering. The results demonstrate that the 2D-BEA technique outperforms these other methods in effectively segmenting the brain region from MRI images.
This document summarizes a survey on balancing network load using geographic hash tables. It discusses how geographic hash tables are used to store and retrieve data from nodes in a wireless network. Two approaches to balancing the network load are proposed: 1) An analytical approach that adds new nodes to servers when load exceeds thresholds. 2) A heuristic approach that moves data between nodes to prevent any single node from receiving too many requests. The approaches aim to extend network life by distributing load more evenly without changing underlying georouting protocols.
Fault Diagnosis of a High Voltage Transmission Line Using Waveform Matching A...ijsc
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This paper is based on the problem of accurate fault diagnosis by incorporating a waveform matching technique. Fault isolation and detection of a double circuit high voltage power transmission line is of immense importance from point of view of Energy Management services. Power System Fault types namely single line to ground faults, line to line faults, double line to ground faults etc. are responsible for transients in current and voltage waveforms in Power Systems. Waveform matching deals with the approximate superimposition of such waveforms in discretized versions obtained from recording devices and Software respectively. The analogy derived from these waveforms is obtained as an error function of voltage and current, from the considered metering devices. This assists in modelling the fault identification as an optimization problem of minimizing the error between these sets of waveforms. In other words, it utilizes the benefit of software discrepancies between these two waveforms. Analysis has been done using the Bare Bones Particle Swarm Optimizer on an IEEE 2 bus, 6 bus and 14 bus system. The performance of the algorithm has been compared with an analogous meta-heuristic algorithm called BAT optimization on a 2 bus level. The primary focus of this paper is to demonstrate the efficiency of such methods and state the common peculiarities in measurements, and the possible remedies for such distortions.
Fault diagnosis of a high voltage transmission line using waveform matching a...ijsc
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This paper is based on the problem of accurate fault diagnosis by incorporating a waveform matching technique. Fault isolation and detection of a double circuit high voltage power transmission line is of immense importance from point of view of Energy Management services. Power System Fault types namely single line to ground faults, line to line faults, double line to ground faults etc. are responsible for transients in current and voltage waveforms in Power Systems. Waveform matching deals with the approximate superimposition of such waveforms in discretized versions obtained from recording devices and Software respectively. The analogy derived from these waveforms is obtained as an error function of voltage and current, from the considered metering devices. This assists in modelling the fault identification as an optimization problem of minimizing the error between these sets of waveforms. In other words, it utilizes the benefit of software discrepancies between these two waveforms. Analysis has been done using the Bare Bones Particle Swarm Optimizer on an IEEE 2 bus, 6 bus and 14 bus system. The performance of the algorithm has been compared with an analogous meta-heuristic algorithm called BAT optimization on a 2 bus level. The primary focus of this paper is to demonstrate the efficiency of such methods and state the common peculiarities in measurements, and the possible remedies for such distortions.
Distance protection scheme for transmission line using back propagation neura...eSAT Publishing House
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
25 9757 transmission paper id 0025 (ed l)IAESIJEECS
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Transmission line is the most important part of the power system. Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production, and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However, the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection.
FUZZY LOGIC APPROACH FOR FAULT DIAGNOSIS OF THREE PHASE TRANSMISSION LINEJournal For Research
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This document summarizes a journal article that proposes using fuzzy logic to diagnose faults on three-phase transmission lines. It begins with an abstract of the journal article, which describes using fuzzy logic as an intelligent technique to quickly and accurately identify the type of fault that occurs on a transmission system. It then provides background on transmission line faults, fault types, and challenges with transmission line protection. The document outlines the proposed fuzzy logic approach, including defining fault types as fuzzy sets and developing if-then rules to relate transmission line voltages and currents to faults. Simulation results are presented showing the fuzzy logic approach can identify different fault types based on the current responses. The conclusion is that the proposed fuzzy logic method allows for fast and reliable fault detection on transmission
This document presents a novel methodology for fault section estimation in power systems. The methodology uses protective device settings and a search algorithm to identify isolated sections. It considers changes in network topology caused by protective devices operating. The methodology calculates a fault reference value for each section based on relay settings and topology. It then calculates the deviation between this reference and the actual weights based on operated protections to identify the most likely fault sections. The result provides operators a prioritized list of fault candidates to assist with decision making during disturbances. The methodology uses intrinsic system information rather than uncertainties used in other existing methods.
1) The document describes the simulation of a differential relay for transformer protection using MATLAB/Simulink. A differential relay operates by comparing the current flowing into and out of a transformer and tripping the circuit breaker if there is a difference, indicating an internal fault.
2) The simulation models a power system including a transformer protected by a differential relay. Current transformers measure the primary and secondary currents which are compared in the relay.
3) Under normal operation the currents match and the relay does not trip, but internal faults create a difference that causes the relay to send a trip signal to the circuit breakers to isolate the fault. The simulation tests the relay under different fault conditions.
A Novel Back Up Wide Area Protection Technique for Power Transmission Grids U...Power System Operation
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Current differential protection relays are widely applied
to the protection of electrical plant due to their simplicity,
sensitivity and stability for internal and external faults. The proposed
idea has the feature of unit protection relays to protect large
power transmission grids based on phasor measurement units. The
principle of the protection scheme depends on comparing positive
sequence voltage magnitudes at each bus during fault conditions
inside a system protection center to detect the nearest bus to
the fault. Then the absolute differences of positive sequence current
angles are compared for all lines connecting to this bus to
detect the faulted line. The new technique depends on synchronized
phasor measuring technology with high speed communication
system and time transfer GPS system. The simulation of the interconnecting
system is applied on 500 kV Egyptian network using
Matlab Simulink. The new technique can successfully distinguish
between internal and external faults for interconnected lines. The
new protection scheme works as unit protection system for long
transmission lines. The time of fault detection is estimated by 5
msec for all fault conditions and the relay is evaluated as a back
up relay based on the communication speed for data transferring.
Transmission line short circuit analysis by impedance matrix method IJECEIAES
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Fault analysis is the process of determining the magnitude of fault voltage and current during the occurrence of different types of fault in electrical power system. Transmission line fault analysis is usually done for both symmetrical and unsymmetrical faults. Symmetrical faults are called three-phase balance fault while unsymmetrical faults include: single line-to-ground, line-to-line, and double line-to-ground faults. In this research, bus impedance matrix method for fault analysis is presented. Bus impedance matrix approach has several advantages over Theveninâs equivalent method and other conventional approaches. This is because the off-diagonal elements represent the transfer impedance of the power system network and helps in calculating the branch fault currents during a fault. Analytical and simulation approaches on a single line-to-ground fault on 3-bus power system network under bolted fault condition were used for the study. Both methods were compared and result showed negligible deviation of 0.02% on the average. The fault currents under bolted condition for the single line-to-ground fault were found to be 4. 7244p.u while the bus voltage is 0. 4095p.u for buses 1 and 2 respectively and 0. 00p.u for bus 3 since the fault occurred at this bus. Therefore, there is no need of burdensomely connecting the entire three sequence network during fault analysis in electrical power system.
Differential equation fault location algorithm with harmonic effects in power...TELKOMNIKA JOURNAL
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About 80% of faults in the power system distribution are earth faults. Studies to find effective methods to identify and locate faults in distribution networks are still relevant, in addition to the presence of harmonic signals that distort waves and create deviations in the power system that can cause many problems to the protection relay. This study focuses on a single line-to-ground (SLG) fault location algorithm in a power system distribution network based on fundamental frequency measured using the differential equation method. The developed algorithm considers the presence of harmonics components in the simulation network. In this study, several filters were tested to obtain the lowest fault location error to reduce the effect of harmonic components on the developed fault location algorithm. The network model is simulated using the alternate transients program (ATP)Draw simulation program. Several fault scenarios have been implemented during the simulation, such as fault resistance, fault distance, and fault inception angle. The final results show that the proposed algorithm can estimate the fault distance successfully with an acceptable fault location error. Based on the simulation results, the differential equation continuous wavelet technique (CWT) filter-based algorithm produced an accurate fault location result with a mean average error (MAE) of less than 5%.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
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.
Enhanced two-terminal impedance-based fault location using sequence valuesIJECEIAES
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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.
DETECTION OF FAULT LOCATION IN TRANSMISSION LINE USING INTERNET OF THINGS (IOT)Journal For Research
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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 equipmentĂ¹ùâÂŹĂąâÂąs, 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 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.
Protection Technique for Complex Distribution Smart Grid Using Wireless Token...Power System Operation
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Distributed generation is expected to increase sharply
as more and more renewable are integrated to power system with
the realization of smart grid, consequently complex distribution
smart grid is given. The traditional protection devices cannot
be able to protect complex power system configuration due to
many fault current loops will feed the fault point. Relays based on
standalone decisions cannot provide reliable and correct action
when used on a complex distribution system. This paper proposes
new protection philosophy using wireless technology. Data
sharing among relays to obtain reliable and accurate decision are
introduced. Wireless Token Ring Protocol (WTRP) as a wireless
local area network (LAN) protocol inspired by the IEEE 802.4
Token Bus Protocol is used for data sharing. WTRP is selected
to improve efficiency by reducing the number of retransmissions
due to collisions. WTRP architecture and protocol are described
to verify operation. MATLAB simulation program is used to
simulate the data exchange protocol between relays in a ring for
a specified amount of time.
International Journal of Computational Engineering Research(IJCER) ijceronline
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nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Neural computing is now one of the most promising technologies in all fields of engineering,
resulting in the development of a number of Artificial Neural Networks (ANN). Double circuit transmission lines
are being employed in the distribution of power to consumers and have become more widespread than single
transmission line, as they increase the electric power transmission capacity and the reliability of an electrical
system. Losses along transmission lines occur due to faults. Possible faults on the transmission line were
predicted using Artificial Neutral Network. In this work, the simulation of fault on a 132kV double circuit
transmission lines using MATLAB was undertaken. Parameters considered during the simulation were the input
of the network which is the fault current value at each fault location while the output of the network is the fault
location. The efficiency of the neural network was tested and verified. This approach provided satisfactory
results with accuracy of 95% or higher.
Double Circuit Transmission Line Protection using Line Trap & Artificial Neur...IRJET Journal
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Intelligent Fault Identification System for Transmission Lines Using Artificial Neural Network
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 1, Ver. I (Jan. 2014), PP 23-31
www.iosrjournals.org
www.iosrjournals.org 23 | Page
Intelligent Fault Identification System for Transmission Lines
Using Artificial Neural Network
Seema Singh1
, Mamatha K R2
,Thejaswini S3
1
(Associate Professor, Dept. of Electronics & Comm. Engg., BMS Institute of Technology, Bangalore, India)
2
(Assistant Professor, Dept. of Electronics & Comm. Engg., BMS Institute of Technology, Bangalore, India)
3
(Assistant Professor, Dept. of Telecommunication Engg., BMS Institute of Technology, Bangalore, India)
Abstract: Transmission and distribution lines are vital links between generating units and consumers. They are
exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high, which has to be
immediately taken care of in order to minimize damage caused by it. This paper focuses on detecting the faults
on electric power transmission lines using artificial neural networks. A feed forward neural network is
employed, which is trained with back propagation algorithm. Analysis on neural networks with varying number
of hidden layers and neurons per hidden layer has been provided to validate the choice of the neural networks
in each step. The developed neural network is capable of detecting single line to ground and double line to
ground for all the three phases. Simulation is done using MATLAB Simulink to demonstrate that artificial
neural network based method are efficient in detecting faults on transmission lines and achieve satisfactory
performances. A 300km, 25kv transmission line is used to validate the proposed fault detection system.
Hardware implementation of neural network is done on TMS320C6713.
Keywords: Transmission Line, Asymmetric fault detection, Artificial neural network (ANN), Back Propagation
algorithm, DSP processor TMS320C6713, Code Composer Studio, MATLAB/Simulink
I. Introduction
The advent of large generating stations and highly interconnected transmission lines makes early fault
detection and rapid equipment isolation imperative to maintain system stability. Transmission line is used to
transfer power or voltage to long distance destination. Power or voltage generated from source is supplied to the
load through the Transmission Line. While transmitting, Transmission Line encounters various faults due to
momentary tree contact, a bird or an animal contact or due to other natural reasons such as thunderstorms or
lightning.
Earlier systems use conventional method for the fault detection which results in the late detection and
inaccurate results [1]-[5]. Conventional algorithms are based on deterministic computations on a well-defined
model for transmission line protection. Bergon model was extensively used to model transmission line.
Conventional distance relays consider power swing as a fault and tripping because of such malfunctioning
would lead to serious consequences for power system stability. To improve the performance, Neural Network
architecture is used which results in the earlier fault detection.
From quite a few years, intelligent based methods are being used in the process of fault detection.
Three major artificial intelligence based techniques that have been widely used in the power and automation
industry are:
ï· Expert System Techniques
ï· Artificial Neural Networks
ï· Fuzzy Logic Systems
Ref [6] used an adaptive neuro-fuzzy approach to develop an inference system for transmission line
fault classification and location. It incorporates the effects of power swings. Fault location is done using
wavelet-neuro-fuzzy combined approach. The wavelet transform captures the dynamic characteristics of fault
signals using wavelet multi-resolution analysis (MRA) coefficients. The fuzzy inference system (FIS) and the
adaptive-neuro-fuzzy inference system (ANFIS) are both used to extract important features from wavelet MRA
coefficients and thereby to reach conclusions regarding fault location. However, combination of different
approaches makes the system complicated. This work uses ANN based approach which uses the fluctuations in
current level as the key feature to detect faults. Neural network is capable of working with real time data and
responses to the changes in surrounding environment immediately and this makes the system more flexible for
the fault detection.
ANN based methods do not require a knowledge base for the detection of faults unlike the other
artificial intelligence based methods. The prime motive behind this work is that a very accurate fault detector
could make if employed in a power transmission and distribution system, in terms of the amount of money and
2. Intelligent Fault Identification System for Transmission Lines Using Artificial Neural Network
www.iosrjournals.org 24 | Page
time that can be saved. The main goal of Fault Detection is to detect a fault in the power system with the highest
practically achievable accuracy. When the physical dimensions and the size of the transmission lines are
considered, the accuracy with which the designed fault detector detects faults in the power system becomes very
important.
Special features of ANN for fault tolerant systems:
ï· ANN is made of massive interconnection of elementary processing units, information processing can be
carried out in a parallel distributed manner. This makes real time processing of large volumes of data more
readily realizable.
ï· ANN can model any degree of nonlinearity and thus are useful in solving these problems which are
inherently nonlinear.
ï· ANN approach is non-algorithmic and requires no prior knowledge functions relating the problem
variables. Also being non algorithmic, they do not make any approximations unlike as the case with most of
the mathematical models.
ï· ANN is capable of handling situations of incomplete information, corrupt data and thus is highly fault
tolerant.
As power system grow both in size and complexity, it becomes necessary to identify different faults
faster and more accurately using more powerful algorithms. Back propagation algorithm of neural network is
used for the fault diagnosis system. Different fault like single line to ground fault and double line to ground
faults are detected using ANN. Fault detector module of a transmission line protective scheme can be used to
start other relaying modules.
The basic block diagram of the work is shown in Figure 1. The Simulink model of 300 km transmission
line with sampling time 0.02s is used for simulation.
Fig 1: Block diagram for fault identification in transmission line using ANN
Simulink model of transmission line is used for validation of neural network based fault detection
system. Neural networks have an inherent parallel architecture with multiple input and output nodes, it can be
implemented to high speed parallel hardware with multivariable input and output. Neural network model in this
paper is implemented using DSP processor TMS320C6713.
II. Transmission line and asymmetric fault
Transmission lines are used for long distance power supply. Transmission lines, when interconnected
with each other, become transmission networks. High-voltage overhead conductors are not covered by
insulation. The conductor material is nearly always an aluminum alloy, made into several strands and possibly
reinforced with steel strands. Copper was sometimes used for overhead transmission but aluminum is lighter,
yields only marginally reduced performance, and costs much less. Overhead conductors are a commodity
supplied by several companies worldwide. Improved conductor material and shapes are regularly used to allow
increased capacity and modernize transmission circuits. High-voltage direct current (HVDC) is used to transmit
large amounts of power over long distances or for interconnections between asynchronous grids. The
Transmission line model, three phase source and three phase load is simulated using MATLAB/Simulink
powergui. Sampling is done to reduce complexity and increase simulation speed.
In an electric power system, a fault is any abnormal electric current. For example, a short circuit is a
fault in which current bypasses the normal load. An open-circuit fault occurs if a circuit is interrupted by some
failure. In three-phase systems, a fault may involve one or more phases and ground, or may occur only between
3. Intelligent Fault Identification System for Transmission Lines Using Artificial Neural Network
www.iosrjournals.org 25 | Page
phases. In a "ground fault" or "earth fault", charge flows into the earth. The prospective short circuit current of a
fault can be calculated for power systems. In power systems, protective devices detect fault conditions and
operate circuit breakers and other devices to limit the loss of service due to a failure.
An asymmetric or unbalanced fault does not affect each of the three phases equally. There are three
common types of asymmetric faults, namely line to line, line to ground and double line to ground. Line-to-line
fault is a short circuit between lines, caused by ionization of air, or when lines come into physical contact, for
example due to a broken insulator. Line-to-ground - is a short circuit between one line and ground, very often
caused by physical contact, for example due to lightning or other storm damage. Double line-to-ground fault is
where two lines come into contact with the ground (and each other), also commonly due to storm damage.
Single line to ground and double line to ground fault is simulated using three phase fault block. It is capable of
introducing short circuit fault at the different interval of time. It can be visualized using the waveform of the
input and output current and voltages through scope.
III. ANN based fault detection system
Artificial intelligence, cognitive modeling, and neural networks are information processing paradigms
inspired by the way biological neural systems process data. Artificial intelligence and cognitive modeling try to
simulate some properties of biological neural networks. Artificial neural networks have been applied
successfully to speech recognition, image analysis and adaptive control, in order to construct software agents (in
computer and video games) or autonomous robots and specially in fault detection system [16], [17]. Neural
network theory has served both to better identify how the neurons in the brain function and to provide the basis
for efforts to create artificial intelligence. Fig 2 shows a single neuron. The following diagram shows a simple
neuron with:
Neuron consists of three basic components, namely weights, thresholds/biases and a single activation
function. Values w1, w2âŠâŠwn are weights to determine the strength of input vector X = [x1, x2,âŠ.., xn]T
. Each
input is multiplied with its associated weight of the neuron XT.W.
I= XT
.W = x1w1 + x2w2 + âŠâŠ + xnwn = â
Threshold, Ï is the neuronâs internal offset. The neuron fire or produces positive output only if the total
input I is above the threshold value. It affects the activation of the node output y as
Y = f(I) = f {â }
To generate the final output Y, the sum is passed on to a non- linear filter f called activation function or
transfer function, which releases the output Y. There are various activation functions which are chosen
depending on the type of problem to be solved by the network. The most common activation function includes
linear function, tangent hyperbolic function, threshold function and sigmoidal function. Most popular sigmoidal
function follows the transition equation shown below.
Y = f(I) = , where α is the slope of sigmoidal function followed.
Fig. 2: A single neuron and sigmoidal activation function
The capability of the neural network increases as number of neurons increases. This capability
multiplies as number of layers in neural network structure increases. Figure 3 shows multilayer neural network
with one hidden layer. The weights connecting neurons are varied continuously while training the neural
network. In NN applications, the challenge is to find the right values for the weights and the threshold. Various
algorithms are developed in neural network field depending on different problems and applications where it has
been used. Back Propagation, Radial Basis Functions, Multi-Layer Perceptron algorithm, Adaptive Resonance
Theory (ART), Self Organizing Maps (SOM) and Counter Propagation Networks (CPN) are few algorithms of
neural networks.
Various neural network architecture, training algorithms and transfer functions were studied to decide
upon the final neural network model for fault detection system. Back propagation algorithm, a supervised
learning is used as the network will be trained using the data created from the simulation model of transmission.
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Number of hidden layers and number of neurons in each layer can be varied depending on the complexity of the
problem to be solved.
The training data was created using Simulink model of 300 km long transmission line for various fault
cases. This training data consists of various vectors of the output and input current and voltage. Using these
values and the created target vector, neural network is trained to detect the fault at the different instants of time.
Training is done using back propagation training algorithm using âtraingdâ function of neural network toolbox
of MATLAB. The trained/updated neural network model for fault detection is converted to Simulink block
using neural network toolbox. This is done to make it usable with Simulink model of transmission line.
3.1 Training of the Neural Network
The neural network architecture with three hidden layers was fixed for the simulation purpose. Hidden
layers consist of 7-10-3 neurons as shown in Fig. 3. Input layer consists of three neurons which takes the current
of three phases of the transmission line. Output layer consists of one neuron which indicates if fault is there. A
threshold of 0.9 is fixed based on simulation in order to avoid false alarms. As shown in figure, the training
algorithm used is gradient descent variant of back propagation algorithm. Figure shows the number of iteration,
time taken to train the Neural Network. It also shows the different performance plots of the Neural Network
after training of the network.
The different training parameter encountered during the training process is gradient, mean square error
and validation check. For better training purpose, mean square error value should decrease when the training
process continues; validation check gives us maximum number of fails in the Neural Network training process.
These training parameter plots are shown in Fig. 4.
3.3 Performance Plot
As discussed earlier in this section, the training data is created using simulation model of transmission
lines. Single line to ground and double line to ground fault was introduced in different phases at different time
instants. This training data, when fed for training the neural network, is divided into three parts. The data
samples are divided into train, test and validation sets randomly by the program, in the ratio 0.7:0.15:0.15.
Fig 3: Neural network training in Simulink tool
Fig 4: Training parameter plots
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The figure 5 shows the performance of Neural Network when Neural Network is trained with particular input
vectors and target vectors. The plot shows that the variation of different parameters throughout the training
process.
After training is completed satisfactorily, the neural network is tested with the available sample data to
evaluate the performance of the updated trained neural network. If the performance is not up to the expectations,
some variations may me experimented with the neural network structure by varying number of hidden layers of
number of neurons in each layer. Different training algorithm may also be experimented with various activation
functions.
Fig 5: Performance plot
Once the neural network with satisfactory performance is developed, its Simulink model is developed
using âgensimâ function so that it can be used with other block in the simulation model. Neural network
simulation model is shown in Fig. 6. The complete simulation set up is shown in Fig. 7.
Fig 6: Simulink model of developed neural network
IV. Simulation Set-up and Hardware Implementation
As discussed in previous section, transmission line with three phase source and load, three phase fault
and neural network based fault detection simulation models are developed to test the capability of the proposed
method. Transmission line model is generated with discrete state and pi section line. Using this model samples
are reduced from 1000 samples to 50 samples, which is feasible for real time application and easy for
implementation. Sampling time of this model is Ts= 0.02ms and simulation is done for 1 sec. With these
specifications, the current and voltage vectors consist of 51 samples. This simulation model of transmission line
with various fault cases is used to create training data which was used to train neural network.
A feed forward neural network with 3 hidden layers is used for fault detection purpose. The number of
neurons in all hidden layer can be varied to get the optimum performance. First hidden layer is fixed with 7
neurons, second with 10 neurons and last hidden layer with 3 neurons as shown in Fig. 3. Output layer has one
neuron, output indicates whether fault has occurred or not at different instants of time. This neural network
structure is trained using back propagation training algorithm for the training data of transmission line model.
This trained/updated neural network is capable of detecting faults. Detection of fault is successfully done for
single line to ground and double line to line ground for all the three phases.
The fault detection system successfully detects single line and double line to ground fault in
transmission line.
Hardware Implementation:
Fault detection system using neural network is implemented on DSP processor. Neural network model
parameters are studied and programmed using âCâ language and the same is implemented in TMS320C6713
using code composer studio. DSP processor is used to verify the result for timing constraints.
Implementation of Neural Network on DSP Processor TMS320C6713 is difficult, because of the size
of the generated Neural Network. To overcome the difficulties faced while doing implementation, Neural
Network was modified as mentioned below:
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ï· Changing the input from floating point to the binary form. For eg. Input in floating point =0.04 is changed to
the input in binary form= 0 and Input in floating point = 0.92 is changed to the input in binary form=1.As
detection of line to ground fault is short circuit fault, input can be transformed to binary values.
ï· The size of the neural network is reduced, by changing the number of hidden layer to 1 and number of
neurons in the hidden layer to 4. This neural network could give satisfactory results for the transformed
binary values.
ï· Implementation of this neural network with one hidden layer of 4 neurons is preferred for the hardware,
which contains 16 weight values and 5 biases. Totally 21 values are required, which is easier for hardware
implementation and able to detect faults successfully.
Fig 7: Simulink model of Intelligent Fault identification system in transmission line model
V. Discussion Of The Results
In this work, an attempt was made to develop an intelligent fault identification system for transmission
lines using artificial neural network. Three phase current and voltages are in analog form and the waveform in
its analog form is shown in Fig. 8. It shows the continuous signals for all the three phases of the voltage before
sampling.
However, to design a fast and accurate fault detection system, it is important to sample it. The sampled
waveform at 0.2 s is shown in Fig. 9 for 1 s. This figure shows the discrete signals for all the three phases of the
voltages after sampling.
Fig 8: Waveform before sampling Fig 9 : Waveform after sampling
Various cases of single line to ground and double line to ground fault is tested for the developed fault
detection system. Test cases are listed in the table 1 and corresponding plots are shown in Fig. 10 to 21. Each
figure has four sub plots. First three sub plots show current levels at phase A, B and C. Fourth plot show neural
network output, which indicates the occurrence of fault by switching to a high level. Fault in one phase disturbs
other phase current as shown in all the result plots. Fig.22 shows fault detection from neural network
implemented in DSP Processor TMS320C6713.A slight delay is seen in the output when it is switching to â1â to
show occurrence of fault. This happens due to hardware delay.
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Fig 10: Fault detection for Single line to ground Fig 11: Fault detection for Single line to ground
fault in phase A at 4s fault in phase B at 4s
Fig 12: Fault detection for Single line to Fig 13: Fault detection for double line to ground
ground fault in phase C at 4s (Phase A and B) Fault at 4s
Fig 14: Fault detection for double line to ground (Phase B and C) Fault at 4s
Fig 15: Fault detection for double line to ground Fig 16: Fault detection for Single line to ground Fault
(Phase A and C) Fault at 4s in Phase A at 6s
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Fig 17: Fault detection for Single line to ground Fig 18: Fault detection for Single line to ground
Fault in Phase B at 6 s Fault in Phase C at 6s
Fig 19: Fault detection for double line to ground Fig 20: Fault detection for double line to ground
(Phase A and B) Fault at 6s (Phase B and C) Fault at 6s
Fig 21: Fault detection for double line to ground Fig 22: Neural network output from DSP Processor
(Phase A and C) Fault at 6s
Neural network is generalized and thus capable of finding any type of fault in the transmission line. The trained
Neural Network can detect Single line to ground and Double line to ground fault. Effects of the different system
parameters and conditions are studied. Extensive studies indicate that the network is able to detect faults earlier
and correctly and its performance is not affected by the changing network conditions.
VI. CONCLUSION
The proposed method uses an artificial neural network-based scheme for fast and reliable fault
detection. Various Asymmetric fault (Single line to ground and double line to ground fault) are simulated and an
ANN based algorithm is used for detection of these faults. Performance of the proposed scheme is evaluated
using various fault types and encouraging results are obtained.
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There are many applications for which the Digital Signal Processor becomes an ideal choice as they
provide the best possible combination of performance, power and cost. Most of the DSP applications can be
simplified into multiplications and additions, so the MAC (Multiply- Accumulate) formed a main functional unit
in early DSP processors. Neural network is a mathematical structure with combination of parallel MAC
operation in its each layer with different transfer functions like sigmoid and linear functions. Thus neural
network can be efficiently implemented on DSP processor using CC Studio as done in this work. Thus neural
network based analysis provides the solution much faster than the conventional methods without degrading the
accuracy.
Further work can be carried out by developing detection system to detect other asymmetric and
symmetric fault. Hardware implementation can be extended to more complex neural networks with higher
version of DSPs. FPGA may also be another alternative for hardware implementation with a comparative
analysis of the two possibilities of hardware.
Acknowledgements
The authors thank the students, Mamta Devi, Mohanakalyani B N, Pratibha C and Nagashree K Rao,
who played an important role in carrying out this work. The authors are also thankful to KSCST, Bangalore for
selecting and sponsoring this work.
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