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Time-dependent resilience assessment and improvement of urban infrastructure systems
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10.1063/1.4737204
/content/aip/journal/chaos/22/3/10.1063/1.4737204
http://aip.metastore.ingenta.com/content/aip/journal/chaos/22/3/10.1063/1.4737204
View: Figures

Figures

Image of FIG. 1.
FIG. 1.

Typical performance response curve of an infrastructure system following the occurrence of a hazard.

Image of FIG. 2.
FIG. 2.

A geographical representation of the power transmission grid in Harris County, Texas.

Image of FIG. 3.
FIG. 3.

Flow chart to simulate estimates of real system performance curves P(t) and target performance curves TP(t) during a future period 0 to Tf.

Image of FIG. 4.
FIG. 4.

(a) The logarithmic transformation of resilience –log10(1 − R(Tf )) under several typical values of post-blackout improvement rate, u. The error bars with 98% confidence intervals are also displayed. (b) Resilience with Tf  = 1 and 10 under different post-blackout improvement rates, u.

Image of FIG. 5.
FIG. 5.

Resilience variation for Tf  = 1 and 10 under different SA parameter settings, with u = 1.01: (a) initial failure probability p 0, (b) OPF dispatch probability δ, and (c) emergency response time te . The error bars with 98% confidence intervals are also displayed.

Image of FIG. 6.
FIG. 6.

Hourly load profiles for load substations with and without demand management.

Image of FIG. 7.
FIG. 7.

(a) Logarithmic form of resilience –log10(1 − R(Tf )) under traditional load profile and several typical daily load profiles with demand management; (b) Resilience variation at Tf  = 1 and 10 under demand management with distinct average daily load profiles, 〈L〉.

Image of FIG. 8.
FIG. 8.

(a) Logarithmic form of resilience –log10(1 − R(Tf )) under several typical ndg numbers of distributed generators with the random deployment strategy, including ndg = 0, 5, 15, 25, which account for 0%, 8.8%, 26.3%, and 43.9% of the total number of load substations, respectively; (b) resilience variation at Tf  = 1 and 10 under random deployment strategy S1 and minimum network efficiency strategy S2 with different numbers of distributed generators, ndg.

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/content/aip/journal/chaos/22/3/10.1063/1.4737204
2012-08-16
2014-04-25
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Time-dependent resilience assessment and improvement of urban infrastructure systems
http://aip.metastore.ingenta.com/content/aip/journal/chaos/22/3/10.1063/1.4737204
10.1063/1.4737204
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