PREDICTION OF CRITICAL FLASHOVER VOLTAGE OF POLLUTED INSULATORS UNDER SEC AND RAIN CONDITIONS USING ANFIS
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Keywords:High Voltage, Flashover, Modelling, Polluted Insulator, ANFIS, GMDL, LSSVM
High voltage insulators are critical components of high voltage electric power transmission networks. Any failure in the satisfactory performance of high voltage insulators would result in significant capital loss, since various industries rely on the availability of an uninterrupted power supply. With the growth in transmission line voltage, the relevance of insulator contamination study has grown significantly. The researchers established a modeling to evaluate the flashover behavior of contaminated high voltage insulators and to uncover the physical factors that drive this phenomena. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model to estimate the critical flashover voltage (FOV) under rain and sec condition . The approach takes as input variable insulator properties such as diameter, height, creepage distance, and the number of pieces on an insulator chain, the data sets used to train and test the network are drawn from experimental results gathered from the literature. The approach's validity was tested by testing numerous insulators with varying shapes. The accuracy and quality of ANFIS are demonstrated by a comparison with the Grouping Multi-Duolateration Localization (GMDL) technique and LS-SVM. Furthermore, ANFIS provides a good estimate of findings that are confirmed by experimental experiments.
Benguesmia, Hani, Nassima M’Ziou, and Ahmed Boubakeur. "Experimental study of pollution effect on the behavior of high voltage insulators under alternative current." Frontiers in Energy 15.1 (2021): 213-221.
Terrab, Hocine, and Abdelhafid Bayadi. "Experimental study using design of experiment of pollution layer effect on insulator performance taking into account the presence of dry bands." IEEE Transactions on Dielectrics and Electrical Insulation 21.6 (2014): 2486-2495.
Liu, Lin, et al. "Investigation on surface electric field distribution features related to insulator flashover in SF 6 gas." IEEE Transactions on Dielectrics and Electrical Insulation 26.5 (2019): 1588-1595.
Salem, Ali A., and R. Abd-Rahman. "A review of the dynamic modelling of pollution flashover on high voltage outdoor insulators." Journal of Physics: Conference Series. Vol. 1049. No. 1. IOP Publishing, 2018.
Salem, Ali A., et al. "The leakage current components as a diagnostic tool to estimate contamination level on high voltage insulators." IEEE Access 8 (2020): 92514-92528.
Gencoglu, Muhsin Tunay, and Murat Uyar. "Prediction of flashover voltage of insulators using least squares support vector machines." Expert Systems with Applications 36.7 (2009): 10789-10798.
Rizk, Farouk AM. "Mathematical models for pollution flashover." Electra 78.5 (1981): 71-103.
Montoya, Gerardo, Isaıas Ramırez, and Jorge I. Montoya. "Measuring pollution level generated on electrical insulators after a strong storm." Electric Power Systems Research 71.3 (2004): 267-273.
Taibaoui Lazreg, Boubakeur Zegnini, and Abdelhalim Mahdjoubi. "An Approach To Predict Flashover Voltage on Polluted Outdoor Insulators Using ANN." In: 2022 19th International Multi-Conference on Systems,Signals & Devices (SSD). IEEE, pp.1842-1847.
MAHDJOUBI, Abdelhalim, ZEGNINI, Boubakeur, BELKHEIRI, Mohammed, et al. Fixed least squares support vector machines for flashover modelling of outdoor insulators. Electric Power Systems Research, 2019, vol. 173, p. 29-37.
Jang, J-SR. "ANFIS: adaptive-network-based fuzzy inference system." IEEE transactions on systems, man, and cybernetics 23.3 (1993): 665-685.
Jang.J.S.R.,Sun, C.T. : Neuro-Fuzzy modeling and control., Proceedings of the IEEE., 83.3, 378–406. 1995
Sugeno, Michio, and G. T. Kang. "Structure identification of fuzzy model." Fuzzy sets and systems 28.1 (1988): 15-33.
Takagi, Tomohiro, and Michio Sugeno. "Fuzzy identification of systems and its applications to modeling and control." IEEE transactions on systems, man, and cybernetics1 (1985): 116-132.
Erenturk, Koksal. "Adaptive-network-based fuzzy inference system application to estimate the flashover voltage on insulator." Instrumentation Science and Technology 37.4 (2009): 446-461.
Mahdjoubi, Abdelhalim, Boubakeur Zegnini, and Mohammed Belkheiri. "Prediction of critical flashover voltage of polluted insulators under sec and rain conditions using least squares support vector machines (LS-SVM)." Diagnostyka 20 (2019).