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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
Hussain, Shareef, Dr.
|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/|
|Appears in Collections:||Conference Papers|
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