Saeh, I. S. and Khairuddin, A. (2009) Decision tree for static security assessment classification. In: 2009 International Conference on Future Computer and Communication. IEEE Computer Soc, pp. 681-684. ISBN 978-076953591-3
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Official URL: http://dx.doi.org/10.1109/ICFCC.2009.64
This paper addresses the on going work of the application of Machine Learning on Static Security Assessment of Power Systems. Several techniques, which have been applied for static Security Assessment .A Decision Tree types comparison for the purpose of static security assessment classification is discussed and the comparison results from these methods on operating point are presented. Decision Tree examines whether the power system is secured under steadystate operating conditions.DT gauges the bus voltages and the line flow conditions. Using minimum number of cases from the available large number of contingencies in terms of their impact on the system security is the methodology that has been developed. Newton Raphson load flow analysis method is used for training and test data. The input variables to the network are loadings of the lines and the voltage magnitude of the load buses. The algorithms are initially tested on the 5 IEEE bus systems. The results obtained indicate that DT method is comparable in accuracy and computational time to the Newton Raphson load flow method.
|Item Type:||Book Section|
|Additional Information:||2009 International Conference on Future Computer and Communication, ICFCC 2009; Kuala Lumpar; 3 April 2009 through 5 April 2009|
|Uncontrolled Keywords:||decision trees, machine learning,static security assessment|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Deposited By:||Ms Zalinda Shuratman|
|Deposited On:||02 Aug 2011 09:06|
|Last Modified:||02 Aug 2011 09:06|
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