Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique

Mohd Wazir Mustafa, Mohd Herwan Sulaiman, Saifulnizam Abd Khalid, Hussain Shareef

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

    5 Citations (Scopus)

    Abstract

    This paper proposes a new hybrid technique, Continuous Genetic Algorithm and Least Squares Support Vector Machine to allocate the real power transfer from generators to loads, namely CGA-LSSVM. CGA is used to obtain the optimal value of hyper-parameters of LS-SVM and supervised learning approach is adopted in the training of LSSVM model. The technique that uses proportional sharing principle (PSP) is utilized as a teacher. Based on load profile of the system and followed by PSP technique for power tracing procedure, the description of inputs and outputs of the training data are created. The CGA-LSSVM is expected to be able to assess which generators are supplying to which specific 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 languageEnglish
    Title of host publicationPECon2010 - 2010 IEEE International Conference on Power and Energy
    Pages12-17
    Number of pages6
    DOIs
    Publication statusPublished - 2010
    Event2010 IEEE International Conference on Power and Energy, PECon2010 - Kuala Lumpur
    Duration: 29 Nov 20101 Dec 2010

    Other

    Other2010 IEEE International Conference on Power and Energy, PECon2010
    CityKuala Lumpur
    Period29/11/101/12/10

    Fingerprint

    Supervised learning
    Support vector machines
    Genetic algorithms

    Keywords

    • Continuous genetic algorithm (CGA)
    • Least Squares Support Vector Machine (LS-SVM)
    • Proportional sharing principle (PSP)

    ASJC Scopus subject areas

    • Energy Engineering and Power Technology

    Cite this

    Mustafa, M. W., Sulaiman, M. H., Khalid, S. A., & Shareef, H. (2010). Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique. In PECon2010 - 2010 IEEE International Conference on Power and Energy (pp. 12-17). [5697549] https://doi.org/10.1109/PECON.2010.5697549

    Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique. / Mustafa, Mohd Wazir; Sulaiman, Mohd Herwan; Khalid, Saifulnizam Abd; Shareef, Hussain.

    PECon2010 - 2010 IEEE International Conference on Power and Energy. 2010. p. 12-17 5697549.

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

    Mustafa, MW, Sulaiman, MH, Khalid, SA & Shareef, H 2010, Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique. in PECon2010 - 2010 IEEE International Conference on Power and Energy., 5697549, pp. 12-17, 2010 IEEE International Conference on Power and Energy, PECon2010, Kuala Lumpur, 29/11/10. https://doi.org/10.1109/PECON.2010.5697549
    Mustafa MW, Sulaiman MH, Khalid SA, Shareef H. Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique. In PECon2010 - 2010 IEEE International Conference on Power and Energy. 2010. p. 12-17. 5697549 https://doi.org/10.1109/PECON.2010.5697549
    Mustafa, Mohd Wazir ; Sulaiman, Mohd Herwan ; Khalid, Saifulnizam Abd ; Shareef, Hussain. / Real power transfer allocation via continuous genetic algorithm-least squares support vector machine technique. PECon2010 - 2010 IEEE International Conference on Power and Energy. 2010. pp. 12-17
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