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Evaluating the effect of resource constraints on resilience of bulk power system with an electric power restoration model

Evaluating the effect of resource constraints on resilience of bulk power system with an electric... Although reliability standards for electric power systems are well accepted, methods and metrics are not established for evaluating the effects of large-scale disruptions that exceed N – 1 criteria for bulk power systems. This paper introduces a model for simulating restoration of bulk power systems following such disruptions. The model allows analysts to simulate disruption of a bulk power system by designating system components as damaged or non-functional. The analyst further defines recovery resource availability and restoration priorities. The model then compares resource requirements to constraints to calculate the timeline of repair completion and the dynamic restoration of power across the network. Resilience metrics quantify the impacts and costs of the disruption to the utility. These quantities enable the analyst to evaluate how proposed system improvements affect restoration and resilience of the bulk power system. The paper concludes with an illustrative case study on a simplified seven-bus system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of System of Systems Engineering Inderscience Publishers

Evaluating the effect of resource constraints on resilience of bulk power system with an electric power restoration model

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1748-0671
eISSN
1748-068X
DOI
10.1504/IJSSE.2014.060883
Publisher site
See Article on Publisher Site

Abstract

Although reliability standards for electric power systems are well accepted, methods and metrics are not established for evaluating the effects of large-scale disruptions that exceed N – 1 criteria for bulk power systems. This paper introduces a model for simulating restoration of bulk power systems following such disruptions. The model allows analysts to simulate disruption of a bulk power system by designating system components as damaged or non-functional. The analyst further defines recovery resource availability and restoration priorities. The model then compares resource requirements to constraints to calculate the timeline of repair completion and the dynamic restoration of power across the network. Resilience metrics quantify the impacts and costs of the disruption to the utility. These quantities enable the analyst to evaluate how proposed system improvements affect restoration and resilience of the bulk power system. The paper concludes with an illustrative case study on a simplified seven-bus system.

Journal

International Journal of System of Systems EngineeringInderscience Publishers

Published: Jan 1, 2014

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