Fuzzy logic based fault detector and classifier for three phase transmission lines with STATCOM
01 Jan 2016-pp 469-474
TL;DR: This paper presents the fault detection and classification for shunt faults on transmission lines with Static Synchronous Compensator (STATCOM) using fuzzy logic, which is able to detect and classify the faults for varying fault resistances and fault distances from the relaying point.
Abstract: This paper presents the fault detection and classification for shunt faults on transmission lines with Static Synchronous Compensator (STATCOM) using fuzzy logic. The fuzzy logic is implemented by using the fuzzy logic toolbox in MATLAB. The 500kV, 60Hz system is simulated using simulink and simpower systems toolbox in MATLAB. The proposed method uses only the three phase currents for fault detection and classification of faulted phase. The system is simulated for various shunt faults with different fault resistances and with different fault locations between 10 percent and 90 percent of the transmission line. The results from the simulation show that fuzzy logic based fault detector and classifier accurately detects and classifies the faults on transmission system. The proposed method is able to detect and classify the faults for varying fault resistances and fault distances from the relaying point.
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TL;DR: The type of fault that possibly occurs in an electric power system, thetype of fault detection and location technique that are available together with the protection device that can be utilized in the power system to protect the equipment from electric fault are reviewed.
Abstract: Electric fault is the main challenge in the process of providing continues electric supply. Fault can occur at anytime and anywhere. Due to the fault causes are mainly based on natural disaster or accident. Most fault occurrence hardly predicted nor avoided. Therefore, a quick response fault detection is necessary to ensure that the fault area is maintained to ensure a continuous power supply system. Hence, a system is required to detect and locate the position of the fault in the power system especially in the transmission line and distribution line. This paper will review the type of fault that possibly occurs in an electric power system, the type of fault detection and location technique that are available together with the protection device that can be utilized in the power system to protect the equipment from electric fault.
9 citations
Cites background from "Fuzzy logic based fault detector an..."
...One of an example of a fuzzy logic application with solid membership function was simulated in [28] where the system is capable of detecting and classifying all types of shunt faults accurately....
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12 Jun 2018
TL;DR: In this paper, a fuzzy logic-based fault classification of transmission lines using Z & S type membership functions is proposed and classification is made on the basis of magnitudes positive sequence and zero sequence currents of lines during the faulty conditions.
Abstract: Since the overhead transmission lines are exposed to external faults and they ultimately disrupt the characteristics of system if not detected in defined span of time. Therefore, in order to maintain the stability and reliability of power system, it is necessary to detect the exact type of fault occurred. This research proposes a simplest fuzzy logic system to detect the type of fault on High Voltage (HVAC) 400 kV transmission lines supplied from both ends. In this paper, a fuzzy logic-based fault classification of transmission lines using Z & S type membership functions is proposed and classification is made on the basis of magnitudes positive sequence and zero sequence currents of lines during the faulty conditions. These membership functions divide the inputs into two ranges and thus making the fuzzy system digitized with low (0) and high (1) outcomes. The designed method is able to detect all types of faults i.e, three phases shorts, two phases shorts, two phase to ground, three phase to ground and single-phase to ground faults with better precision and accuracy. The suggested technique has better performance even in long transmission lines or if a fault occurs away from protection point and also for overloaded lines. The operating times for relays to isolate the fault are also calculated. The propositions are verified through fuzzy logic toolbox in MATLAB.
6 citations
Cites methods from "Fuzzy logic based fault detector an..."
...The functional time for relay operation is calculated by using equation (11) [15-16] ] [ ] ) [( F N T F I OR I I T TMS T T T × × − = (11)...
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11 Feb 2021
TL;DR: In this paper, a protection scheme for six-phase transmission line for series faults or open conductor fault has been presented, which initiates with the estimation of fundamental current component from the measured time-domain current signals at bus located at sending end.
Abstract: In recent times the power demand has increased considerably Power demand can be achieved by multi-phase transmission line In the present work, a protection scheme for six-phase transmission line for series faults or open conductor fault has been presented The scheme initiates with the estimation of fundamental current component from the measured time-domain current signals at bus located at sending end These signals are fed to fuzzy logic-based protection approach The proposed protection scheme has been analyzed for different types of series faults at different locations with various fault inception angles From simulation results, it is evident that the proposed fuzzy logic-based relay scheme perfectly detects and classifies all types of series faults accurately
5 citations
TL;DR: In this article, a neural network (NN) algorithm was used to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL).
Abstract: The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
3 citations
01 Dec 2017
TL;DR: A fuzzy logic based fault detection and classification scheme has been proposed for six phase transmission line and a performance analysis has been carried out which authenticates the suitability and quickness of the proposed protection.
Abstract: A fuzzy logic based fault detection and classification scheme has been proposed for six phase transmission line. The algorithm is based on the monitoring of fundamental voltage of all the six phases and the deviation of phase voltage and current phasor with respect to a predefined reference phase angle. The variations in the voltage and current phase angles post fault have been framed as linguistic variables and further mapped with the status (healthy or faulty) of the phases using a set of fuzzy rules. The proposed fuzzy logic based protection scheme has been tested for different fault scenarios with varying fault parameters. A performance analysis has been carried out which authenticates the suitability and quickness of the proposed protection.
3 citations
Cites methods from "Fuzzy logic based fault detector an..."
...A fuzzy logic based protection scheme for transmission lines with STATCOM has been reported [13]....
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References
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Book•
01 Dec 1994
TL;DR: This chapter discusses Fuzzy Systems Simulation, specifically the development of Membership Functions and the Extension Principle, and some of the methods used to derive these functions.
Abstract: About the Author. Preface to the Third Edition. 1 Introduction. The Case for Imprecision. A Historical Perspective. The Utility of Fuzzy Systems. Limitations of Fuzzy Systems. The Illusion: Ignoring Uncertainty and Accuracy. Uncertainty and Information. The Unknown. Fuzzy Sets and Membership. Chance Versus Fuzziness. Sets as Points in Hypercubes. Summary. References. Problems. 2 Classical Sets and Fuzzy Sets. Classical Sets. Operations on Classical Sets. Properties of Classical (Crisp) Sets. Mapping of Classical Sets to Functions. Fuzzy Sets. Fuzzy Set Operations. Properties of Fuzzy Sets. Alternative Fuzzy Set Operations. Summary. References. Problems. 3 Classical Relations and Fuzzy Relations. Cartesian Product. Crisp Relations. Cardinality of Crisp Relations. Operations on Crisp Relations. Properties of Crisp Relations. Composition. Fuzzy Relations. Cardinality of Fuzzy Relations. Operations on Fuzzy Relations. Properties of Fuzzy Relations. Fuzzy Cartesian Product and Composition. Tolerance and Equivalence Relations. Crisp Equivalence Relation. Crisp Tolerance Relation. Fuzzy Tolerance and Equivalence Relations. Value Assignments. Cosine Amplitude. Max Min Method. Other Similarity Methods. Other Forms of the Composition Operation. Summary. References. Problems. 4 Properties of Membership Functions, Fuzzification, and Defuzzification. Features of the Membership Function. Various Forms. Fuzzification. Defuzzification to Crisp Sets. -Cuts for Fuzzy Relations. Defuzzification to Scalars. Summary. References. Problems. 5 Logic and Fuzzy Systems. Part I Logic. Classical Logic. Proof. Fuzzy Logic. Approximate Reasoning. Other Forms of the Implication Operation. Part II Fuzzy Systems. Natural Language. Linguistic Hedges. Fuzzy (Rule-Based) Systems. Graphical Techniques of Inference. Summary. References. Problems. 6 Development of Membership Functions. Membership Value Assignments. Intuition. Inference. Rank Ordering. Neural Networks. Genetic Algorithms. Inductive Reasoning. Summary. References. Problems. 7 Automated Methods for Fuzzy Systems. Definitions. Batch Least Squares Algorithm. Recursive Least Squares Algorithm. Gradient Method. Clustering Method. Learning From Examples. Modified Learning From Examples. Summary. References. Problems. 8 Fuzzy Systems Simulation. Fuzzy Relational Equations. Nonlinear Simulation Using Fuzzy Systems. Fuzzy Associative Memories (FAMS). Summary. References. Problems. 9 Decision Making with Fuzzy Information. Fuzzy Synthetic Evaluation. Fuzzy Ordering. Nontransitive Ranking. Preference and Consensus. Multiobjective Decision Making. Fuzzy Bayesian Decision Method. Decision Making Under Fuzzy States and Fuzzy Actions. Summary. References. Problems. 10 Fuzzy Classification. Classification by Equivalence Relations. Crisp Relations. Fuzzy Relations. Cluster Analysis. Cluster Validity. c-Means Clustering. Hard c-Means (HCM). Fuzzy c-Means (FCM). Fuzzy c-Means Algorithm. Classification Metric. Hardening the Fuzzy c-Partition. Similarity Relations from Clustering. Summary. References. Problems. 11 Fuzzy Pattern Recognition. Feature Analysis. Partitions of the Feature Space. Single-Sample Identification. Multifeature Pattern Recognition. Image Processing. Summary. References. Problems. 12 Fuzzy Arithmetic and the Extension Principle. Extension Principle. Crisp Functions, Mapping, and Relations. Functions of Fuzzy Sets Extension Principle. Fuzzy Transform (Mapping). Practical Considerations. Fuzzy Arithmetic. Interval Analysis in Arithmetic. Approximate Methods of Extension. Vertex Method. DSW Algorithm. Restricted DSW Algorithm. Comparisons. Summary. References. Problems. 13 Fuzzy Control Systems. Control System Design Problem. Control (Decision) Surface. Assumptions in a Fuzzy Control System Design. Simple Fuzzy Logic Controllers. Examples of Fuzzy Control System Design. Aircraft Landing Control Problem. Fuzzy Engineering Process Control. Classical Feedback Control. Fuzzy Control. Fuzzy Statistical Process Control. Measurement Data Traditional SPC. Attribute Data Traditional SPC. Industrial Applications. Summary. References. Problems. 14 Miscellaneous Topics. Fuzzy Optimization. One-Dimensional Optimization. Fuzzy Cognitive Mapping. Concept Variables and Causal Relations. Fuzzy Cognitive Maps. Agent-Based Models. Summary. References. Problems. 15 Monotone Measures: Belief, Plausibility, Probability, and Possibility. Monotone Measures. Belief and Plausibility. Evidence Theory. Probability Measures. Possibility and Necessity Measures. Possibility Distributions as Fuzzy Sets. Possibility Distributions Derived from Empirical Intervals. Deriving Possibility Distributions from Overlapping Intervals. Redistributing Weight from Nonconsonant to Consonant Intervals. Comparison of Possibility Theory and Probability Theory. Summary. References. Problems. Index.
4,958 citations
"Fuzzy logic based fault detector an..." refers methods in this paper
...The main advantage of fuzzy logic is, it uses simple, “IF-THEN” type of relations and its knowledge representation is explicit [14]....
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TL;DR: In this paper, a fuzzy-logic-based algorithm to identify the type of faults for digital distance protection system has been developed, which is able to accurately identify the phase(s) involved in all ten types of shunt faults that may occur in a transmission line under different fault resistances, inception angle, and loading levels.
Abstract: In this paper, a fuzzy-logic-based algorithm to identify the type of faults for digital distance protection system has been developed. The proposed technique is able to accurately identify the phase(s) involved in all ten types of shunt faults that may occur in a transmission line under different fault resistances, inception angle, and loading levels. The proposed method needs only three line-current measurements available at the relay location and can perform the fault classification task in about a half-cycle period. Thus, the proposed technique is well suited for implementation in a digital distance protection scheme.
221 citations
"Fuzzy logic based fault detector an..." refers methods in this paper
...A digital distance protection scheme based on fuzzy logic algorithm using three line currents for classification of different faults on transmission lines was discussed in [3]....
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TL;DR: Results indicate that this approach can be used as an effective tool for high-speed digital relaying, as the correct detection is achieved in less than half a cycle and that computational burden is much simpler than the recently postulated fault classification techniques.
Abstract: This paper presents a new approach to real-time fault classification in power transmission systems using fuzzy-logic-based multicriteria approach Only the three line currents are utilized to detect fault types such as LG, LL, and LLG, and then to define the faulty line An online wavelet-based preprocessor stage is used with data window of ten samples (based on 45-kHz sampling rate and 50-Hz power frequency) The multicriteria algorithm is developed based on fuzzy sets for the decision-making part of the scheme Computer simulation has been conducted using EMTP programs Results are shown and they indicate that this approach can be used as an effective tool for high-speed digital relaying, as the correct detection is achieved in less than half a cycle and that computational burden is much simpler than the recently postulated fault classification techniques
207 citations
"Fuzzy logic based fault detector an..." refers methods in this paper
...A wavelet fuzzy logic based protection technique using line currents for classification of faults was discussed in [5]....
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Book•
15 Aug 2004
TL;DR: An embedded interaction of generators through the transmission network which is governed by the differential and algebraic equations of the apparatus and interconnects is implied, which has to be protected from abnormalities.
Abstract: They may occupy different angular positions, but all machines rotate at the same electrical speed. This close knitting implies an embedded interaction of generators through the transmission network which is governed by the differential and algebraic equations of the apparatus and interconnects. This aspect is referred to as the system behaviour. This system has to be protected from abnormalities which is the task of protection system.
204 citations
13 Jul 2003
TL;DR: Voltage source converter (VSC) technology has been selected as the basis for several recent projects due to its controllability, compact modular design, ease of system interface and low environmental impact as mentioned in this paper.
Abstract: Voltage source converter (VSC) technology has been selected as the basis for several recent projects due to its controllability, compact modular design, ease of system interface and low environmental impact. This paper describes the rationale for selection of VSC technology and the latest technical developments utilized in several recent projects.
108 citations
"Fuzzy logic based fault detector an..." refers background in this paper
...Voltage source converters are preferred for independent control of real and reactive power control, simple interface with ac system, continuous ac voltage regulation, no minimum power restriction [13]....
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