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

Mohd Wazir Mustafa; Saifulnizam Abd Khalid; Mohd Herwan Sulaiman; Siti Rafidah Abd Rahim; Omar Aliman; Hussain Shareef

doi:10.1109/INECCE.2011.5953853

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

Mohd Wazir Mustafa, Saifulnizam Abd Khalid, Mohd Herwan Sulaiman, Siti Rafidah Abd Rahim, Omar Aliman, Hussain Shareef

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	InECCE 2011 - International Conference on Electrical, Control and Computer Engineering
Pages	76-81
Number of pages	6
DOIs	https://doi.org/10.1109/INECCE.2011.5953853
Publication status	Published - 2011
Externally published	Yes
Event	1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011 - Kuantan, Malaysia Duration: Jun 21 2011 → Jun 22 2011

Publication series

Name	InECCE 2011 - International Conference on Electrical, Control and Computer Engineering

Conference

Conference	1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011
Country/Territory	Malaysia
City	Kuantan
Period	6/21/11 → 6/22/11

Keywords

continuous genetic algorithm (CGA)
least squares support vector machine (LS-SVM)
pool based power system
proportional sharing principle (PSP)

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/INECCE.2011.5953853

Cite this

Mustafa, M. W., Khalid, S. A., Sulaiman, M. H., Rahim, S. R. A., Aliman, O., & Shareef, H. (2011). Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm. In InECCE 2011 - International Conference on Electrical, Control and Computer Engineering (pp. 76-81). Article 5953853 (InECCE 2011 - International Conference on Electrical, Control and Computer Engineering). https://doi.org/10.1109/INECCE.2011.5953853

Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm. / Mustafa, Mohd Wazir; Khalid, Saifulnizam Abd; Sulaiman, Mohd Herwan et al.
InECCE 2011 - International Conference on Electrical, Control and Computer Engineering. 2011. p. 76-81 5953853 (InECCE 2011 - International Conference on Electrical, Control and Computer Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mustafa, MW, Khalid, SA, Sulaiman, MH, Rahim, SRA, Aliman, O & Shareef, H 2011, Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm. in InECCE 2011 - International Conference on Electrical, Control and Computer Engineering., 5953853, InECCE 2011 - International Conference on Electrical, Control and Computer Engineering, pp. 76-81, 1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011, Kuantan, Malaysia, 6/21/11. https://doi.org/10.1109/INECCE.2011.5953853

Mustafa MW, Khalid SA, Sulaiman MH, Rahim SRA, Aliman O, Shareef H. Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm. In InECCE 2011 - International Conference on Electrical, Control and Computer Engineering. 2011. p. 76-81. 5953853. (InECCE 2011 - International Conference on Electrical, Control and Computer Engineering). doi: 10.1109/INECCE.2011.5953853

Mustafa, Mohd Wazir ; Khalid, Saifulnizam Abd ; Sulaiman, Mohd Herwan et al. / Tracing the real power transfer of individual generators to loads using least squares support vector machine with continuous genetic algorithm. InECCE 2011 - International Conference on Electrical, Control and Computer Engineering. 2011. pp. 76-81 (InECCE 2011 - International Conference on Electrical, Control and Computer Engineering).

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abstract = "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.",

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AB - 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.

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

Abstract

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Keywords

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