Nuriziani Hussin
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Preferred name
Nuriziani Hussin
Official Name
Nuriziani, Hussin
Alternative Name
Hussin, Nuriziani
Hussin, N.
Main Affiliation
Scopus Author ID
26633116700
Researcher ID
DVD-9074-2022

Research Output
Now showing 1 - 3 of 3
  • Publication
    Effect of Pollution Distribution Scenarioes on Flashover Characteristics on Outdoor Insulators
    ( 2020-09-27)
    Salem A.A.
    ;
    Abd-Rahman R.
    ;
    Al-Ameri S.
    ;
    Kamarudin M.S.
    ;
    Jamail N.A.M.
    ;
    Nuriziani Hussin
    ;
    Zainuddin H.
    ;
    Soomro D.M.
    ;
    Mizad M.
    Distribution of the contamination on insulators is often irregular, which threatens the reliability of outdoor insulation. This work aimed to study the influence of pollution distribution, humidity and dry band location with various scenarioes on flashover characteristic of insulators. Flashover tests of cup-pin glass polluted insulators were conducted. Findings indicated the difference between the flashover performances of insulators under different pollution distribution. The flashover characteristics like voltage and current are greatly affected by salt deposit density (SDD), distribution modes, and distribution area. The relation between U50 and SDD has positive power function with more contrast in distribution. Insulators with more regular distribution have lowest flashover voltage and highest critical leakage current. Different distribution modes lead to the change of the conductivity of the contamination layer and the uneven distribution of the current density, which is the main cause that the characteristics of pollution flashover are directly related to the pollution modes.
  • Publication
    Flashover voltage prediction on polluted cup-pin the insulators under polluted conditions
    ( 2021-01-01)
    Salem A.A.
    ;
    Abd-Rahman R.
    ;
    Kamarudin M.S.
    ;
    Othman N.A.
    ;
    Jamail N.A.M.
    ;
    Nuriziani Hussin
    ;
    Haziah Abdul Hamid
    ;
    Rawi I.M.
    The natural pollution which is mainly affected by the weather conditions are the main cause of flashovers on high voltage insulators leading to outages in power systems. In this work, characteristics of flashover for contaminated cup-pin insulators have been studied based on experiential test and a mathematical model. Information from laboratory test combined with new mathematical model results are used to define Artificial Neural Network (ANN) algorithm and Adaptive Neuro-fuzzy Inference System (ANFIS) for calculated the flashover characteristics (current IF and voltage UF). several of experiments and measurement are carried out for 1:1, 5:1, 10:1 and 15:1 ratios of bottom to top surface salt deposit density on contaminated samples (z). Dimensional Analysis Method (DAM) was used to derive new model for the variables which often effective in the flashover phenomenon of polluted insulators. The model was derived by establishment the relationship between flashover voltage UF and current IF, length of pollution layer LP, exposure time t, arc constant A and layer pollution conductivity of insulator σ. The both arc constants A and n is computed using genetic algorithm. Comparative investigates have clearly shown that the approach AI-based method gives the agreeable results compared to the mathematical model.
  • Publication
    Flashover voltage prediction on polluted cup-pin the insulators under polluted conditions
    ( 2021-01-01)
    Salem A.A.
    ;
    Abd-Rahman R.
    ;
    Kamarudin M.S.
    ;
    Othman N.A.
    ;
    Jamail N.A.M.
    ;
    Nuriziani Hussin
    ;
    Haziah Abdul Hamid
    ;
    Rawi I.M.
    The natural pollution which is mainly affected by the weather conditions are the main cause of flashovers on high voltage insulators leading to outages in power systems. In this work, characteristics of flashover for contaminated cup-pin insulators have been studied based on experiential test and a mathematical model. Information from laboratory test combined with new mathematical model results are used to define Artificial Neural Network (ANN) algorithm and Adaptive Neuro-fuzzy Inference System (ANFIS) for calculated the flashover characteristics (current IF and voltage UF). several of experiments and measurement are carried out for 1:1, 5:1, 10:1 and 15:1 ratios of bottom to top surface salt deposit density on contaminated samples (z). Dimensional Analysis Method (DAM) was used to derive new model for the variables which often effective in the flashover phenomenon of polluted insulators. The model was derived by establishment the relationship between flashover voltage UF and current IF, length of pollution layer LP, exposure time t, arc constant A and layer pollution conductivity of insulator σ. The both arc constants A and n is computed using genetic algorithm. Comparative investigates have clearly shown that the approach AI-based method gives the agreeable results compared to the mathematical model.
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