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Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm

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Main Authors: Mohd Wazir, Mustafa, Dr., Saifulnizam, Abd. Khalid, Dr., Mohd Herwan, Sulaiman, Siti Rafidah, Abd Rahim, Omar, Aliman, Hussain, Shareef, Dr.
Other Authors: wazir@fke.utm.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2011
Subjects:
Continuous genetic algorithm (CGA)
Least squares support vector machine (LS-SVM)
Pool based power system
Proportional sharing principle (PSP)
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/16297
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spelling my.unimap-162972011-11-24T04:42:27Z Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm Mohd Wazir, Mustafa, Dr. Saifulnizam, Abd. Khalid, Dr. Mohd Herwan, Sulaiman Siti Rafidah, Abd Rahim Omar, Aliman Hussain, Shareef, Dr. wazir@fke.utm.my nizam@fke.utm.my mherwan@unimap.edu.my rafidah@unimap.edu.my omaraliman@ump.edu.my shareef@eng.ukm.my Continuous genetic algorithm (CGA) Least squares support vector machine (LS-SVM) Pool based power system Proportional sharing principle (PSP) Link to publisher's homepage at http://ieeexplore.ieee.org/ 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. 2011-11-24T04:42:26Z 2011-11-24T04:42:26Z 2011-06-21 Working Paper p. 76-81 978-1-6128-4228-8 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5953853 http://hdl.handle.net/123456789/16297 en Proceedings of the 1st International Conference on Electrical, Control and Computer Engineering 2011 (InECCE 2011) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Continuous genetic algorithm (CGA)
Least squares support vector machine (LS-SVM)
Pool based power system
Proportional sharing principle (PSP)
spellingShingle Continuous genetic algorithm (CGA)
Least squares support vector machine (LS-SVM)
Pool based power system
Proportional sharing principle (PSP)
Mohd Wazir, Mustafa, Dr.
Saifulnizam, Abd. Khalid, Dr.
Mohd Herwan, Sulaiman
Siti Rafidah, Abd Rahim
Omar, Aliman
Hussain, Shareef, Dr.
Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 wazir@fke.utm.my
author_facet wazir@fke.utm.my
Mohd Wazir, Mustafa, Dr.
Saifulnizam, Abd. Khalid, Dr.
Mohd Herwan, Sulaiman
Siti Rafidah, Abd Rahim
Omar, Aliman
Hussain, Shareef, Dr.
format Working Paper
author Mohd Wazir, Mustafa, Dr.
Saifulnizam, Abd. Khalid, Dr.
Mohd Herwan, Sulaiman
Siti Rafidah, Abd Rahim
Omar, Aliman
Hussain, Shareef, Dr.
author_sort Mohd Wazir, Mustafa, Dr.
title Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
title_short Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
title_full Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
title_fullStr Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
title_full_unstemmed Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
title_sort tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/16297
_version_ 1643791482347323392
score 13.222552

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