Automated Fault Location and Isolation in Distribution Grids With Distributed Control and Unreliable Communication

Kashyap, Neelabh; Yang, Chi; Sierla, Seppo; Flikkema, Paul G.

doi:10.1109/tie.2014.2387093

Cited by 37 publications

(18 citation statements)

References 29 publications

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“…Min and Santoso [8] investigate the effect of the DC component in the phasor data and how it can affect momentary fault localization process. Kashyap et al, [9] implement a fault location and isolation algorithm in a distributed fashion. Lee [10] uses PMU voltage data to search for a fault in a radial network in a timely manner.…”

Section: A Backgroundmentioning

confidence: 99%

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Jamei¹,

Ramakrishna

Tesfay

et al. 2020

IEEE J. Select. Areas Commun.

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In this paper, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between different fault location hypotheses, which are associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults is studied. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyberphysical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations [2].

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Section: A Backgroundmentioning

confidence: 99%

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Jamei¹,

Ramakrishna

Tesfay

et al. 2020

IEEE J. Select. Areas Commun.

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“…A sensitivity analysis is used to study the benefit of automation and the effect of new advanced ICT based component failures in the availability of the service/power to end users. See [25], [26], [27], [28] for further information about FLISR.…”

Section: E Reward Model/metricsmentioning

confidence: 99%

A modeling approach for dependability analysis of smart distribution grids

Amare

Helvik

Heegaard

2018

2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)

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The distribution grids are among the most critical infrastructures which integrates advanced control and communication technologies atop of power systems. This paper presents a comprehensive modeling framework suited to study the resiliency and dependability of the next generation distribution grid. It focuses on revealing insight in the complex interaction and dependencies between the ICT based control system and the powergrid. It looks into the role of automation and new technologies in future distribution grids. The objective is through a quantitative assessment to identify vulnerabilities and to study alternative design principles and architecture of the automated distribution grids. The modeling framework is general and modular based on a stochastic activity networks using the Mobius tool. For illustration, a case study is included at the end.

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“…In this case, Switches 11,12,13,15,22,25,31,35,55,57 and 78 are opened to keep the radiality of the system. The two faults, illustrated in Figure 15, occur in the same lateral in feeder F1.…”

Section: Test Case 3: Simultaneous Faults In the Same Lateralmentioning

confidence: 99%

“…Some methods have used simple but time-consuming visual inspection to locate the fault [2]. Other fault location algorithms that have been proposed include impedance based methods [3][4][5][6][7][8], travelling-wave based methods [9][10][11], minimum fault reactance methods [12,13], voltage-sag based methods [14][15][16][17], knowledge based methods [18][19][20], and multi-agent approaches [21,22]. However, due to the relatively complex nature of distribution systems, each of these methods has some disadvantages.…”

Section: Introductionmentioning

confidence: 99%

“…In distribution systems, for the frequent changing of its topology, it is an onerous task to do the two parts manually. The algorithms proposed in [22][23][24][25] can only recognize the topology of the network. Thus, the novel algorithm proposed in this paper is that it can dramatically reduce the required manpower and is not affected by the changes of topology.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology

2017

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Abstract:The increasing use of modern measuring devices, such as Feeder Terminal Units (FTUs), on power networks can provide multiple types of information for fault location on distribution systems. Using these devices, in this paper, a novel automatic matrix-based algorithm for the identification and isolation of faulted feeder sections on distribution systems is proposed. The algorithm works in two stages: the first stage automatically identifies the radial feeders that make up the whole system and represents the feeders' topology in matrix form; and the second stage automatically identifies the faulted section of the identified feeder and opens the relevant switches to isolate it. The algorithm can be applied to single and multiple faults, as it operates using measuring device information and detecting the status of switch devices. It does not require any electrical parameters and it is not affected by the fault type or fault resistance. The algorithm was thoroughly tested using a large distribution system and was found to efficiently identify and isolate the faulted feeder section in each case.

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Automated Fault Location and Isolation in Distribution Grids With Distributed Control and Unreliable Communication

Cited by 37 publications

References 29 publications

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

A modeling approach for dependability analysis of smart distribution grids

Automatic Faulted Feeder Section Location and Isolation Method for Power Distribution Systems Considering the Change of Topology

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