Evaluation of Components Reliability Importance Measures of Electric Transmission Systems Using the Bayesian Network

Daemi, Tahereh; Ebrahimi, Akbar

doi:10.1080/15325008.2012.694973

Cited by 15 publications

(7 citation statements)

References 9 publications

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“…2 The applications of graph theory for network analysis are perceived in various domains of engineering such as oil and gas distribution, computer and communication system, power transmission and distribution, transportation etc. 4,5 The recent advancements in data communication and infrastructure modeling further coax the possibility to interconnect the important infrastructures through interconnected multi-networks. 6,7 These diverse fields of application of networks proffer a challenge for engineers worldwide to provide the society with reliable and resilient networks.…”

Section: Networkmentioning

confidence: 99%

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A literature review on network reliability analysis and its engineering applications

Gaur

Yadav

Soni

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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The applications of networks can be observed in numerous engineering realms mainly computers and communication, transportation, electric transmission and oil and gas distribution. Estimating the reliability of such networks is a critical task for the well-being of society as well as a nation. The paradigm of network reliability has evolved considerably over the past few decades. The purpose of this article is to present the developments in network reliability domain in a laconic manner. This paper discusses the various metrics used to evaluate network connectivity along with their mathematical backgrounds. The various algorithms namely State Enumeration, Sum of disjoint product, Minimal Cut Set, Factoring theorem, Cellular Automata, Subset Simulation, Percolation theory, Binary Decision Diagrams, and Universal Generating Functions are enumerated in this review study. The application part of algorithms with their advantages, limitations and scope are presented. Finally, the methodologies used for assessment of network reliability are discussed. This article aims at providing a holistic view of the network reliability practices, which may prove to be helpful for researchers across the globe.

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Section: Networkmentioning

confidence: 99%

“…Directed graphs are used to represent power transmission and oil distribution networks whereas undirected graphs are used for depicting communication and transportation networks. 5,9…”

Section: Introductionmentioning

confidence: 99%

A literature review on network reliability analysis and its engineering applications

Gaur

Yadav

Soni

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The system reliability is defined as = 1 − Pr( ). (6) This binary definition provides only partial information on the system performance and it is dependent on the definition of the . It is introduced here to facilitate the use of classical reliability importance measures.…”

Section: Network Reliability Definitionmentioning

confidence: 99%

“…Several studies applied IMs specifically to network reliability analysis for electrical power systems [e.g., 4,[5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Reliability and Component Importance in Networks Subject to Spatially Distributed Hazards Followed by Cascading Failures

Scherb

Garrè

Straub

2017

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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We investigate reliability and component importance in spatially distributed infrastructure networks subject to hazards characterized by large-scale spatial dependencies. In particular, we consider a selected IEEE benchmark power transmission system. A generic hazard model is formulated through a random field with continuously scalable spatial autocorrelation to study extrinsic common-cause-failure events such as storms or earthquakes. Network performance is described by a topological model, which accounts for cascading failures due to load redistribution after initial triggering events. Network reliability is then quantified in terms of the decrease in network efficiency and number of lost lines. Selected importance measures are calculated to rank single components according to their influence on the overall system reliability. This enables the identification of network components that have the strongest effect on system reliability. We thereby propose to distinguish component importance related to initial (triggering) failures and component importance related to cascading failures. Numerical investigations are performed for varying correlation lengths of the random field to represent different hazard characteristics. Results indicate that the spatial correlation has a discernible influence on the system reliability and component importance measures, while the component rankings are only mildly affected by the spatial correlation. We also find that the proposed component importance measures provide an efficient basis for planning network improvements.

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“…Shubin et al [18] discussed component reliability importance indices with respect to the changes of the optimal component sequencing. Daemi and Ebrahimi [19] presented a novel approach for the determination of reliability importance measures in electric transmission systems implementing the Bayesian network. Hilber and Bertling [20] proposed a method for defining the importance of individual components in a network with respect to total interruption cost.…”

Section: Introductionmentioning

confidence: 99%

FOR Allocation to Distribution Systems based on Credible Improvement Potential (CIP)

Tiwary¹,

Arya²,

Arya³

et al. 2016

J. Inst. Eng. India Ser. B

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This paper describes an algorithm for forced outage rate (FOR) allocation to each section of an electrical distribution system subject to satisfaction of reliability constraints at each load point. These constraints include threshold values of basic reliability indices, for example, failure rate, interruption duration and interruption duration per year at load points. Component improvement potential measure has been used for FOR allocation. Component with greatest magnitude of credible improvement potential (CIP) measure is selected for improving reliability performance. The approach adopted is a monovariable method where one component is selected for FOR allocation and in the next iteration another component is selected for FOR allocation based on the magnitude of CIP. The developed algorithm is implemented on sample radial distribution system.

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Evaluation of Components Reliability Importance Measures of Electric Transmission Systems Using the Bayesian Network

Cited by 15 publications

References 9 publications

A literature review on network reliability analysis and its engineering applications

A literature review on network reliability analysis and its engineering applications

Reliability and Component Importance in Networks Subject to Spatially Distributed Hazards Followed by Cascading Failures

FOR Allocation to Distribution Systems based on Credible Improvement Potential (CIP)

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