A Novel Model for Prediction of Flashover 150kV Polluted Insulator Based on Nonlinear Autoregressive External Input Neural Network
DOI:
https://doi.org/10.33387/protk.v11i3.7344Kata Kunci:
Flashover, Prediction, Contamination, Insulator, Neural Network, ESDD, NSDD.Abstrak
This study aims to use an artificial neural network to forecast the flashover voltage of a polluted high-voltage insulator. Practical tests were conducted on a high-voltage insulator to gather data for the neural network. These tests were carried out with varying levels of real contaminants from used insulators, with each level of contamination measured in milliliters. The collected data provides flashover voltage values corresponding to different pollution amounts and their conductivity in each insulator zone. The Nonlinear Autoregressive External Input Neural Network (NarxNet) is employed to predict the flashover voltage and assess the pollution state of the insulator. The results demonstrate that the NarxNet method achieves a 93.74% accuracy rate in predicting the flashover voltage of high-voltage insulators, compared to the results from practical tests.Unduhan
Referensi
F. Ahmad, “Analysis of Flashover Voltages of Disc Type Insulator under Artificial Pollution Condition,†Int. J. Eng., vol. 29, no. 6, 2016, doi: 10.5829/idosi.ije.2016.29.06c.05.
X.-F. J. Yong-Kun Zhu, Guang Sun, Shu-Yong Gao, Wen-Jiang Shi, Da-Peng Xu, Ming-Xing Yu, “Experimental analysis of the artificial contamination flashover characteristics of long insulator strings in 500 kV transmission lines,†vol. 117, hal. 65–75, 2016, doi: https://doi.org/10.2991/eeeis-16.2017.9.
L. Jin, Z. Tian, J. Ai, Y. Zhang, dan K. Gao, “Condition Evaluation of the Contaminated Insulators by Visible Light Images Assisted with Infrared Information,†IEEE Trans. Instrum. Meas., vol. 67, no. 6, hal. 1349–1358, 2018, doi: 10.1109/TIM.2018.2794938.
F. Aouabed, A. Bayadi, dan R. Boudissa, “Flashover voltage of silicone insulating surface covered by water droplets under AC voltage,†Electr. Power Syst. Res., vol. 143, hal. 66–72, 2017, doi: 10.1016/j.epsr.2016.10.025.
M. Farzaneh dan J. Zhang, “A multi-arc model for predicting AC critical flashover voltage of ice-covered insulators,†IEEE Trans. Dielectr. Electr. Insul., vol. 14, no. 6, hal. 1401–1409, 2007, doi: 10.1109/TDEI.2007.4401222.
X. Qiao, Z. Zhang, X. Jiang, R. Sundararajan, X. Ma, dan X. Li, “AC failure voltage of iced and contaminated composite insulators in different natural environments,†Int. J. Electr. Power Energy Syst., vol. 120, no. October 2019, hal. 105993, 2020, doi: 10.1016/j.ijepes.2020.105993.
Lazreg Taibaoui; Boubakeur Zegnini; Abdelhalim Mahdjoubi, “An Approach To Predict Flashover Voltage on Polluted Outdoor Insulators Using ANN,†2022, doi: 10.1109/SSD54932.2022.9955667.
Y. C. Wang, Y. T. Lin, H. C. Chang, dan C. C. Kuo, “Contamination assessment of insulators using microsystem technology with fuzzy-based approach,†Microsyst. Technol., vol. 27, no. 4, hal. 1759–1772, 2021, doi: 10.1007/s00542-019-04538-5.
A. Mahdjoubi, B. Zegnini, M. Belkheiri, dan T. Seghier, “Fixed least squares support vector machines for flashover modelling of outdoor insulators,†Electr. Power Syst. Res., vol. 173, no. July 2018, hal. 29–37, 2019, doi: 10.1016/j.epsr.2019.03.010.
A. G. Suresh dan P. Dixit, “ANN model to predict critical flashover voltages of polluted porcelain disc insulators,†Int. J. Appl. Eng. Res., vol. 12, no. 11, hal. 2942–2951, 2017.
M. Marich dan H. Hadi, “Evaluation of flashover voltage on polluted insulators with artificial neural network,†J. Electr. Eng., vol. 15, no. 3, hal. 248–253, 2015.
K. Belhouchet, A. Bayadi, dan M. E. Bendib, “Artificial neural networks (ANN) and genetic algorithm modeling and identification of arc parameter in insulators flashover voltage and leakage current,†2015 4th Int. Conf. Electr. Eng. ICEE 2015, 2016, doi: 10.1109/INTEE.2015.7416698.
G. Asimakopoulou, V. Kontargyri, Ch. Elias, G. Tsekouras and F. Asimakopoulou, “A fuzzy logic optimization methodology for the estimation of the critical flashover voltage on insulators,†vol. 81, hal. 580–588, 2010, doi: https://doi.org/10.1016/j.epsr.2010.10.024.
S. A. Bessedik dan H. Hadi, “Prediction of flashover voltage of insulators using least squares support vector machine with particle swarm optimisation,†Electr. Power Syst. Res., vol. 104, hal. 87–92, 2013, doi: 10.1016/j.epsr.2013.06.013.
S. Mohammadnabi dan K. Rahmani, “Influence of humidity and contamination on the leakage current of 230-kV composite insulator,†Electr. Power Syst. Res., vol. 194, no. February, hal. 107083, 2021, doi: 10.1016/j.epsr.2021.107083.
A. A. Salem et al., “Investigation of High Voltage Polymeric Insulators Performance under Wet Pollution,†Polymers (Basel)., vol. 14, no. 6, 2022, doi: 10.3390/polym14061236.
H. Asgari, M. Venturini, X. Q. Chen, dan R. Sainudiin, “Modeling and simulation of the transient behavior of an industrial power plant gas turbine,†J. Eng. Gas Turbines Power, vol. 136, no. 6, hal. 1–10, 2014, doi: 10.1115/1.4026215.
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