Literature DB >> 26172758

Robustness of power systems under a democratic-fiber-bundle-like model.

Osman Yağan1.   

Abstract

We consider a power system with N transmission lines whose initial loads (i.e., power flows) L(1),...,L(N) are independent and identically distributed with P(L)(x)=P[L≤x]. The capacity C(i) defines the maximum flow allowed on line i and is assumed to be given by C(i)=(1+α)L(i), with α>0. We study the robustness of this power system against random attacks (or failures) that target a p fraction of the lines, under a democratic fiber-bundle-like model. Namely, when a line fails, the load it was carrying is redistributed equally among the remaining lines. Our contributions are as follows. (i) We show analytically that the final breakdown of the system always takes place through a first-order transition at the critical attack size p(☆)=1-(E[L]/max(x)(P[L>x](αx+E[L|L>x])), where E[·] is the expectation operator; (ii) we derive conditions on the distribution P(L)(x) for which the first-order breakdown of the system occurs abruptly without any preceding diverging rate of failure; (iii) we provide a detailed analysis of the robustness of the system under three specific load distributions-uniform, Pareto, and Weibull-showing that with the minimum load L(min) and mean load E[L] fixed, Pareto distribution is the worst (in terms of robustness) among the three, whereas Weibull distribution is the best with shape parameter selected relatively large; (iv) we provide numerical results that confirm our mean-field analysis; and (v) we show that p(☆) is maximized when the load distribution is a Dirac delta function centered at E[L], i.e., when all lines carry the same load. This last finding is particularly surprising given that heterogeneity is known to lead to high robustness against random failures in many other systems.

Year:  2015        PMID: 26172758     DOI: 10.1103/PhysRevE.91.062811

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  Mapping heterogeneities through avalanche statistics.

Authors:  Soumyajyoti Biswas; Lucas Goehring
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2018-11-26       Impact factor: 4.226

2.  Optimizing the robustness of electrical power systems against cascading failures.

Authors:  Yingrui Zhang; Osman Yağan
Journal:  Sci Rep       Date:  2016-06-21       Impact factor: 4.379

3.  Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows.

Authors:  A Moussawi; N Derzsy; X Lin; B K Szymanski; G Korniss
Journal:  Sci Rep       Date:  2017-09-15       Impact factor: 4.379

4.  Modelling cascading failures in networks with the harmonic closeness.

Authors:  Yucheng Hao; Limin Jia; Yanhui Wang; Zhichao He
Journal:  PLoS One       Date:  2021-01-25       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.