Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 208, Issue -, Pages -Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2022.107867
Keywords
Porcelain insulator; Pollution distribution; Flashover voltage; Artificial neural network; Fuzzy logic
Categories
Funding
- Malaysia Ministry of Education [05E68]
- Universiti Teknologi Malaysia (UTM) [05E68]
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This study investigates the impact of various factors on the flashover voltage of an 11 kV porcelain insulator and proposes a hybrid model that can predict the insulator's flashover voltage and condition.
The current work investigates the flashover voltage of an 11 kV porcelain insulator against changes in the location of the dry band, salt deposit density, humidity, non-uniform pollution degree, and polluted surface area. Generally, the flashover voltage of the polluted insulator dropped sharply compared to that of the clean insulator. Specifically, under salt deposit density (SDD) of 0.03 mg/cm(2), the flashover voltages of scenarios A (full pollution), B (dry band 1), C (dry band 2), and D (dry band 3) decrease by 26%, 19%, 10%, and 2%, respectively, compared to 43.70 kV flashover voltage of the clean insulator. With an increase in SDD, the flashover voltage under all scenarios decreases steadily, with the median flashover voltage of scenario A being the lowest at 17.52 kV. The flashover voltage under all scenarios also varies with changes in the humidity level, non-uniform pollution degree and polluted surface area. Subsequently, an artificial neural network (ANN) and fuzzy logic (FL) hybrid model is proposed to predict the flashover voltage and condition of the insulator, where the model successfully yields the insulator condition index between 0 and 100% to indicate the pollution severity of the insulator.& nbsp;
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