Universiti Teknologi Malaysia Institutional Repository

An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system

Mustafa, Mohd. Wazir and Sulaiman, M. H. and Shareef, H. and Abdul Khalid, Saifulnizam and Abd. Rahim, S. R. and Alima, O. (2011) An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system. In: 2011 5th International Power Engineering and Optimization Conference, PEOCO 2011 - Program and Abstracts. IEEE Explorer, pp. 375-380. ISBN 978-145770354-6

[img] PDF (Abstract)
69Kb

Official URL: http://dx.doi.org/10.1109/PEOCO.2011.5970400

Abstract

This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). The idea is to use GA as an optimizer to find the optimal values of hyper-parameters of LS-SVM and adopt a supervised learning approach to train the LS-SVM model. The well known proportional sharing method (PSM) is used to trace the loss at each transmission line which is then utilized as a teacher in the proposed hybrid technique called GA-SVM method. Based on load profile as inputs and PSM output for transmission loss allocation, the GA-SVM model is expected to learn which generators are responsible for transmission losses. In this paper, IEEE 14-bus system is used to show the effectiveness of the proposed method.

Item Type:Book Section
Uncontrolled Keywords:deregulation, genetic algorithm, proportional sharing method, support vector machine, transmission loss allocation
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:28650
Deposited By: Liza Porijo
Deposited On:09 Nov 2012 01:36
Last Modified:09 Nov 2012 01:36

Repository Staff Only: item control page