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artificial intelligence blackout critical problems decision trees electric power system interconnection electric power system security emergency emergency conditions hybrid artificial neural network kohonen network kohonen neural networks large-scale blackout large-scale emergency learning systems multiagent control multilayers network security network technologies neural networks operational security power security power system random forests security monitoring

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... ISBN (print): 9781479976. DOI: 10.1109/PTC.2015.7232460 Voltage collapse is a critical problem that impacts power system operational security. Timely and accurate assessment of voltage security is necessary to detect alarm states in order to prevent a large-scale blackout. This paper presents an on-line voltage security assessment scheme using periodically updated random forest-based decision trees. We demonstrated the proposed method on the modified 53-bus IEEE power system. Results are presented ...

... hybrid artificial neural network for voltage security evaluation in a power system // IYCE 2015 - Proceedings: 2015 5th International Youth Conference on Energy. 2015. 1 p. ISBN (print): 9781467371. DOI: 10.1109/IYCE.2015.7180828 A majority of recent large-scale blackouts have been the consequence of instabilities characterized by sudden voltage collapse phenomena. This paper presents a method for voltage instability monitoring in a power system with a hybrid artificial neural network which consist ...

... preventing large-scale emergencies in electric power systems // Proc. of the 4-th International Youth Conference on Energy. Siófok, Hungary Hungary. 06-08 June 2013. 1 p. ISBN (print): 9781467355. DOI: 10.1109/IYCE.2013.6604142 Recent examples of large-scale blackouts in North American 2003, Moscow in 2005 and Europa in 2003 and 2006 have clearly demonstrated that secure operation of large interconnected power systems cannot be achieved without full understanding of the system behavior during ...