Universiti Teknologi Malaysia Institutional Repository

Determination of generators' contributions to loads in pool based power system using least squares support vector machine

Mustafa, Mohd. Wazir and M. H., Sulaiman and H., Shareef and S. N., Abd Khalid (2010) Determination of generators' contributions to loads in pool based power system using least squares support vector machine. In: PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts, 2010, Shah Alam, Malaysia.

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Official URL: http://dx.doi.org/10.1109/PEOCO.2010.5559183

Abstract

This paper attempts to allocate the generators' contributions to loads in pool based power system by incorporating the Least Squares Support Vector Machine (LS-SVM). The idea is to use supervised learning approach to train the LS-SVM. The technique that uses proportional tree method (PTM) which is applying the convention of proportional sharing principle is utilized as a teacher. Based on converged load flow and followed by PTM for power tracing procedure, the description of inputs and outputs of the training data for the LS-SVM are created. The LS-SVM will learn to identify which generators are supplying to which loads. The proposed technique is demonstrated using IEEE 14-bus system to illustrate the effectiveness of the LS-SVM technique compared to that of the PTM. The comparison result with Artificial Neural Network (ANN) technique is also will be discussed.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:artificial neural network (ANN), least squares support vector machine (LS-SVM), pool based power system, proportional tree method (PTM), supervised learning
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:27115
Deposited By: Liza Porijo
Deposited On:27 Jul 2012 07:15
Last Modified:27 Jul 2012 07:15

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