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Availability importance measures of components in smart electric power grid systems.

Authors :
Zheng, Junjun
Okamura, Hiroyuki
Pang, Taoming
Dohi, Tadashi
Source :
Reliability Engineering & System Safety. Jan2021, Vol. 205, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• A hierarchical availability model of a smart electric power grid is presented. • BDD representation for FTs of system with two power supply modes are introduced. • Components and systems availabilities are mathematically demonstrated. • BDD-based importance analysis is proposed to quantify component importance. • Numerical results indicate the crucial components with the proposed approach. The emergence of the smart grid has brought great innovation in the new distribution power system, facilitated a green and sustainable energy-based society, and mitigated the growing energy crisis. The smart grid is regarded as the next generation electrical power grid. It not only improves the power distribution systems with the techniques of distributed generation, but also makes the systems more complicated than the traditional ones. Thus it is important to evaluate the availability of smarts grids and to indicate the vulnerable parts of the systems. In this paper, a hierarchical model consisting of a layered fault tree (FT) and continuous-time Markov chains (CTMCs) is presented to model a smart grid system with two different power supply modes. We also analyze the component importance of the system, aiming to find the weak parts of the system thereby improving the system design. The importance analysis of components is based on parametric sensitivities and binary decision diagram (BDD) representation for the FTs. In a numerical illustration, we quantify the availability of the system with two power supply modes and also evaluate the importance of all components in the system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09518320
Volume :
205
Database :
Academic Search Index
Journal :
Reliability Engineering & System Safety
Publication Type :
Academic Journal
Accession number :
146910765
Full Text :
https://doi.org/10.1016/j.ress.2020.107164