Fault location in distribution feeders with optimally placed PMU's

Rajeev, Aneesh; Angel, T. S. Shiny; Khan, Faraz Zafar

doi:10.1109/tapenergy.2015.7229659

Cited by 18 publications

(6 citation statements)

References 5 publications

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“…The work in [53], proposed a fault location strategy to detect the fault in ring or radial networks. The scheme comprised three autonomous steps that running together to get the precise location of the fault from the main substation.…”

Section: Pmus Based Techniquesmentioning

confidence: 99%

A Survey of Fault Location Techniques for Distribution Networks

Sheta

Abdulsalam

Eladl

2020

Bulletin of the Faculty of Engineering. Mansoura University

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Since recent societies become more hooked into electricity, a higher level of power supply continuity is required from power systems. The expansion of those systems makes them liable to electrical faults and several failures are raised due to totally different causes. As a result of these failures, the faulty element ought to be disconnected and isolated as soon as possible to reduce the damage and remove the emergency state from the whole system. Power quality considerations impose the grid to spot the faulted area as rapidly as doable, which forces utility operators in speeding up fault detection and system recovery and subsequently decreasing blackout time and pertinent costs. All these conditions have raised incredible significances about investigating methods and techniques used for fast detecting of faulted area, thus this matter needs to be pulled in broad consideration among researchers in power systems. In this paper, a comparative environment classifies and surveys a wide number of fault location procedures for distribution networks. The paper can be considered as a guide for operating engineers and researchers to settle on the foremost viable plausibility backed their existing framework and necessities.

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Section: Pmus Based Techniquesmentioning

confidence: 99%

A Survey of Fault Location Techniques for Distribution Networks

Sheta

Abdulsalam

Eladl

2020

Bulletin of the Faculty of Engineering. Mansoura University

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“…The diagnosis and detection of fault have become extensively believe in power grids, data from Phasor measurement unit (PMU) is used to locate the fault index of smart grids [5], [6], [7].Voltages and currents are determined by using PMU which receipts synchronization signals from global positioning system (GPS) satellites [8]. And because that; the measurements of PMU are actual excessive [5] and it is not favorable to connect them at everywhere in the power grid, so; it is widespread to use minimum number of PMUs and compute voltage at all nodes of different grids using the most common relation as Ohm formula [6]. Numerous data from altered sources to the structure of database creates a wealthy databank which is further consistent and reliable than discrete sources, this is owing to the integral assets of the methods of data fusion, and the results are suitable and proper in an occasion of imperfect data.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Fault Diagnostic Technique Applied to IEEE 14-bus Smart Grid Standard

Amer,

Selmy*,

Mohamed

2020

IJITEE

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Due to the gigantic power quality (PQ) demands for modern systems, power systems fault detection and diagnosis have become a significant issue. For this aim, it’s very important to detect the fault at early time and determine its location through any signal. Several methods and techniques are applied to solve this problem such as discrete wavelet transform (DWT). Although DWT has the ability of fast time detection of the fault, it has a problem to discriminate between faulty and noisy signals. DWT succeeds to extract features from altered transient disturbances, but it fails to differentiate between transient disturbances due to healthy or noisy signals. Fusion between DWT for its speed and radial basis function for its accuracy is done. The fusion technique used has a major disadvantage of its delay time as the fault can be detected after the exact location with several samples. In this paper new technique will be proposed to overcome the DWT and data fusion method problems, to achieve the classification between noisy and faulty signals with high accuracy. The proposed method is executed to classify the signals premised on weights of them, complex tree classifier uses the energy of the signal as a feature. All simulations are achieved and done on IEEE standard 14 bus system to confirm the ability and capacity of new suggested technique. Simulation results show a better performance of the proposed system in comparison with other methods, and that it capable to differentiate between faulty and noisy signals and precisely locate the fault position.

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“…Data from the Phasor measurement unit (PMU) is used to discover the place of fault for smart systems. Finding and discovering defective signals has advanced towards becoming widespread stock in power systems [10], [11], and [12]. Voltages and currents are dictated by using PMU that receives synchronization indications from global positioning system (GPS) satellites [13].…”

Section: Introductionmentioning

confidence: 99%

“…For these purposes, the PMU measurements are real extremes [10] and it is not nice to interface them anywhere in the power systems. Thus, it is across the board to use the least amount of PMUs and compute voltage at all hubs of different devices using the most commonly known link as an Ohm principle [11]. Different information from different sources to the database structure makes a more stable and consistent affluent database than a single source [14], this is attributable to the fundamental techniques of data fusion strategies, and the results are appropriate and legitimate in the event of faulty information.…”

Section: Introductionmentioning

confidence: 99%

Improved Technique to Diagnose Fault in IEEE Standard 14-Bus System

Amer*,

Selmy*,

Mohamed

2019

IJITEE

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This study presents a new technique for fast detecting and diagnosing of power grids faults. Discrete Wavelet transform (DWT) has a major disadvantage of noise sensitivity. The proposed technique solves the problems of DWT, where a highprecision classification of noisy and faulty signals could be obtained. Fusion between voltage and power readings is done to provide a more reliable and accurate decision to determine the exact location of the fault. In this technique, the learner classifier is used,and the system is trained for multiple situations where most faults may occur. All simulations were carried out and performed on the standard IEEE 14 bus system to check the efficiency and performance of the technique proposed. Simulation results demonstrate, as will be discussed, a strong effectiveness of the suggested approach relative to others. The main feature of the proposed technique is that it can differentiate between faulty and noisy signals and recognize the fault's location quickly and with high reliability

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Fault location in distribution feeders with optimally placed PMU's

Cited by 18 publications

References 5 publications

A Survey of Fault Location Techniques for Distribution Networks

A Survey of Fault Location Techniques for Distribution Networks

Enhanced Fault Diagnostic Technique Applied to IEEE 14-bus Smart Grid Standard

Improved Technique to Diagnose Fault in IEEE Standard 14-Bus System

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