Operational resilience assessment of power systems under extreme weather and loading conditions

Mathaios Panteli, Pierluigi Mancarella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In the traditional reliability assessment of power systems, the effect of real-time operating conditions on components' reliability is usually ignored. Nevertheless, as highlighted by historical electrical and weather emergencies, the conditions that power system components experience, i.e. weather and loading conditions, have a significant effect on their reliability. This paper describes an approach for considering the effect of real-time operating conditions when assessing the operational resilience of power systems, with focus on the impact of wind and loading conditions on the failure probability of transmission lines. The concept of fragility curves is used, which express the failure probability of the lines as a function of the wind speed and their loading. The approach is illustrated using a simplified 29-bus version of the Great Britain transmission network. The simulations results help quantify how less resilient the network becomes for extreme wind and loading conditions.

Original languageEnglish
Title of host publication2015 IEEE Power and Energy Society General Meeting, PESGM 2015
PublisherIEEE Computer Society
Volume2015-September
ISBN (Electronic)9781467380409
DOIs
Publication statusPublished - 30 Sep 2015
EventIEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States
Duration: 26 Jul 201530 Jul 2015

Other

OtherIEEE Power and Energy Society General Meeting, PESGM 2015
CountryUnited States
CityDenver
Period26/07/1530/07/15

Keywords

  • Real-time conditions
  • Reliability
  • Resilience
  • Resiliency

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  • Cite this

    Panteli, M., & Mancarella, P. (2015). Operational resilience assessment of power systems under extreme weather and loading conditions. In 2015 IEEE Power and Energy Society General Meeting, PESGM 2015 (Vol. 2015-September). [7286087] IEEE Computer Society. https://doi.org/10.1109/PESGM.2015.7286087