Assessment of power grid vulnerabilities accounting for stochastic loads and model imprecision
Rocchetta, Roberto and Patelli, Edoardo (2018) Assessment of power grid vulnerabilities accounting for stochastic loads and model imprecision. Electrical Power and Energy Systems, 98. pp. 219-232. ISSN 0142-0615 (https://doi.org/10.1016/j.ijepes.2017.11.047)
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Abstract
Vulnerability and robustness are major concerns for future power grids. Malicious attacks and extreme weather conditions have the potential to trigger multiple components outages, cascading failures and large blackouts. Robust contingency identification procedures are necessary to improve power grids resilience and identify critical scenarios. This paper proposes a framework for advanced uncertainty quantification and vulnerability assessment of power grids. The framework allows critical failure scenarios to be identified and overcomes the limitations of current approaches by explicitly considering aleatory and epistemic sources of uncertainty modelled using probability boxes. The different effects of stochastic fluctuation of the power demand, imprecision in power grid parameters and uncertainty in the selection of the vulnerability model have been quantified. Spectral graph metrics for vulnerability are computed using different weights and are compared to power-flow-based cascading indices in ranking N-1 line failures and random N-k lines attacks. A rank correlation test is proposed for further comparison of the vulnerability metrics. The IEEE 24 nodes reliability test power network is selected as a representative case study and a detailed discussion of the results and findings is presented.
ORCID iDs
Rocchetta, Roberto and Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247;-
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Item type: Article ID code: 70373 Dates: DateEvent30 June 2018Published14 December 2017Published Online30 November 2017AcceptedSubjects: Science > Mathematics Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 31 Oct 2019 12:57 Last modified: 19 Nov 2024 23:39 URI: https://strathprints.strath.ac.uk/id/eprint/70373