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
Link To Document :
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