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

M. W., Mustafa and H., Shareef and M. H., Sulaiman and S. N., Abd. Khalid and S. R., Abd. Rahim and Omar, Aliman (2011) An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system. In: 5th International Power Engineering and Optimization Conference (PEOCO 2011), 6-7 June 2011 , Shah Alam, Selangor. pp. 375-380..

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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: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Deregulation; genetic algorithm; proportional sharing method; support vector machine; transmission loss allocation
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 16 Oct 2019 08:07
Last Modified: 16 Oct 2019 08:07
URI: http://umpir.ump.edu.my/id/eprint/26118
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