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Title: Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
Authors: Mohd Wazir, Mustafa, Dr.
Saifulnizam, Abd. Khalid, Dr.
Mohd Herwan, Sulaiman
Siti Rafidah, Abd Rahim
Omar, Aliman
Hussain, Shareef, Dr.
???metadata.dc.contributor.url???: wazir@fke.utm.my
nizam@fke.utm.my
mherwan@unimap.edu.my
rafidah@unimap.edu.my
omaraliman@ump.edu.my
shareef@eng.ukm.my
Keywords: Continuous genetic algorithm (CGA);Least squares support vector machine (LS-SVM);Pool based power system;Proportional sharing principle (PSP)
Issue Date: 21-Jun-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 76-81
Series/Report no.: Proceedings of the 1st International Conference on Electrical, Control and Computer Engineering 2011 (InECCE 2011)
Abstract: This paper attempts to trace the real power transfer of individual generators to loads in pool based power system by incorporating the hybridization of Least Squares Support Vector Machine (LS-SVM) with Continuous Genetic Algorithm (CGA)- CGA-LSSVM. The idea is to use CGA to find the optimal values of regularization parameter, γ and Kernel RBF parameter, σ2, and adapt a supervised learning approach to train the LS-SVM model. The technique that uses proportional sharing principle (PSP) is utilized as a teacher. Based on converged load flow and followed by PSP technique for power tracing procedure, the description of inputs and outputs of the training data are created. The CGA-LSSVM will learn to identify which generators are supplying to which loads. In this paper, the 25-bus equivalent system of southern Malaysia is used to illustrate the effectiveness of the CGA-LSSVM technique compared to that of the PSP technique.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org/
URI: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5953853
http://hdl.handle.net/123456789/16297
ISBN: 978-1-6128-4228-8
Appears in Collections:Conference Papers

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