• DocumentCode
    1500476
  • Title

    Assessing the Vulnerability of a Power System Through a Multiple Objective Contingency Screening Approach

  • Author

    Rocco, Claudio M. ; Ramirez-Marquez, Jose Emmanuel ; Salazar, Daniel E. ; Yajure, Cesar

  • Author_Institution
    Fac. de Ing., Univ. Central de Venezuela, Caracas, Venezuela
  • Volume
    60
  • Issue
    2
  • fYear
    2011
  • fDate
    6/1/2011 12:00:00 AM
  • Firstpage
    394
  • Lastpage
    403
  • Abstract
    This paper introduces a new, alternative approach for the analysis of power systems vulnerability based on a hybrid model that combines elements of the classical Deterministic Network Interdiction Problem (DNIP) with the use of an efficient multi-objective optimization evolutionary algorithm (MOEA). From a power systems perspective, the traditional DNIP is implemented as a surrogate approach to understand the interaction between the power system´s component incapacitation (due to random failures or external attacks), and the system load shedding. The paper recognizes that, when analyzing power system vulnerability, it is possible to have multiple competing objectives and multiple prospective solutions that may change based on the preference of the decision-maker. This multi-objective view of the DNIP in the power systems context is solved using MOEA. As a result, the proposed approach could be used as an initial, straightforward screening approach to identify severe system disturbances. Several examples illustrate that the approach is able to reproduce and improve upon the results presented in previous studies.
  • Keywords
    evolutionary computation; load shedding; optimisation; power system faults; power system reliability; classical deterministic network interdiction problem; hybrid model; multiobjective optimization evolutionary algorithm; multiple objective contingency screening approach; power systems vulnerability; system disturbances; system load shedding; Accuracy; Delta modulation; Genetic algorithms; Load modeling; Mathematical model; Optimization; Power systems; Contingency screening; interdiction; multi-objective evolutionary optimization; power system security;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/TR.2011.2135490
  • Filename
    5753983