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

M. W. Mustafa, M. H. Sulaiman, H. Shareef, S. N.Abd Khalid, S. R.Abd Rahim, O. Alima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2011 5th International Power Engineering and Optimization Conference, PEOCO 2011 - Program and Abstracts
Pages375-380
Number of pages6
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 5th International Power Engineering and Optimization Conference, PEOCO 2011 - Shah Alam, Selangor, Malaysia
Duration: Jun 6 2011Jun 7 2011

Publication series

Name2011 5th International Power Engineering and Optimization Conference, PEOCO 2011 - Program and Abstracts

Conference

Conference2011 5th International Power Engineering and Optimization Conference, PEOCO 2011
Country/TerritoryMalaysia
CityShah Alam, Selangor
Period6/6/116/7/11

Keywords

  • Deregulation
  • genetic algorithm
  • proportional sharing method
  • support vector machine
  • transmission loss allocation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology

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