An interval-based contingency selection approach considering uncertainty
Author(s) -
Chao Xu,
Wei Gu,
Lizi Luo,
Jianguo Yao,
Shengchun Yang,
Ke Wang,
Dan Zeng,
Miao Fan
Publication year - 2016
Publication title -
turkish journal of electrical engineering and computer sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 30
eISSN - 1303-6203
pISSN - 1300-0632
DOI - 10.3906/elk-1502-108
Subject(s) - interval (graph theory) , ranking (information retrieval) , contingency , selection (genetic algorithm) , computer science , mathematical optimization , contingency table , power flow , bayesian probability , interval arithmetic , electric power system , mathematics , algorithm , data mining , statistics , power (physics) , machine learning , physics , quantum mechanics , mathematical analysis , linguistics , philosophy , combinatorics , bounded function
Static security assessment is affected by uncertainties of load flow distributions introduced by renewable sources. A fast contingency selection approach based on interval theory is proposed in this paper. Firstly, an interval line active flow calculation algorithm is developed to reduce conservation in application of interval mathematics in line flow calculation. Then a novel interval comparison method based on Bayesian probability theory is applied in interval index comparison to give the relative severity information of contingencies. Finally, an approximately consistent ranking method is utilized in contingency ranking to rank screened contingencies. Numerical studies on several IEEE standard test systems and two practical provincial power grids in China under different load and generation conditions have proved that the proposed approach is computationally light and highly accurate under different uncertainties.
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