Data-mining-based approach for predicting the power system post-contingency dynamic vulnerability status-Reference-Cited by-同舟云学术

Data-mining-based approach for predicting the power system post-contingency dynamic vulnerability status

Published:2014-08-11 Issue:10 Volume:25 Page:2515-2546
ISSN:2050-7038
Container-title:International Transactions on Electrical Energy Systems
language:en
Short-container-title:Int. Trans. Electr. Energ. Syst.

Author:

Cepeda Jaime C.¹,Rueda José L.²^ORCID,Colomé Delia G.³,Erlich István⁴

Affiliation:

1. Corporación Centro Nacional de Control de Energía-CENACE; Av. Atacazo and Panamericana Sur km 0 171112 Quito Ecuador

2. Department of Electrical Sustainable Energy; Delft University of Technology; Mekelweg 4 2628 CD Delft The Netherlands

3. Instituto de Energía Eléctrica; Universidad Nacional de San Juan; Av. Libertador 1109 (O) 5400 San Juan Argentina

4. Institute of Electrical Power Systems; University Duisburg-Essen; Bismarckstr. 81 47057 Duisburg Germany

Funder

German Academic Exchange Service

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Reference47 articles.

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3. Cepeda JC Colomé DG Castrillón NJ Dynamic Vulnerability Assessment due to Transient Instability based on Data Mining Analysis for Smart Grid Applications IEEE PES ISGT-LA Conference 2011

4. Savulescu SC et al. Real-Time Stability Assessment in Modern Power System Control Centers 2009

5. Huang Z Zhang P et al. Vulnerability Assessment for Cascading Failures in Electric Power Systems IEEE PES Power Systems Conference and Exposition 2009

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