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Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network

Electrical power system lines sometimes pass along the coastal regions and transverse through the industrial areas of the Peninsular Malaysia. The phenomenon of salt blown from the sea to the land at the coastal area was causing salt deposition to the transformer bushing which contaminating the bush...

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Main Authors:	Dahlan N.Y., Kasuan N., Ahmad A.S.
Other Authors:	24483200900
Format:	Conference paper
Published:	2023
Subjects:	ANN HMLP Insulators Leakage current MRPE Regression analysis Bushings Coastal zones Industrial electronics Leakage currents Metal analysis Neural networks Statistics Coastal area Coastal regions Electrical power system High voltage insulators Hybrid multilayered perceptron network Industrial area Insulator flashover Malaysia Meteorological effects Meteorological parameters Power station Real measured data Recursive prediction Salt deposition Suspension types Transformer bushings Learning algorithms
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id	my.uniten.dspace-30643
record_format	dspace
spelling	my.uniten.dspace-306432023-12-29T15:50:45Z Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network Dahlan N.Y. Kasuan N. Ahmad A.S. 24483200900 35423888200 7202040740 ANN HMLP Insulators Leakage current MRPE Regression analysis Bushings Coastal zones Industrial electronics Leakage currents Metal analysis Neural networks Regression analysis Statistics ANN Coastal area Coastal regions Electrical power system High voltage insulators HMLP Hybrid multilayered perceptron network Industrial area Insulator flashover Malaysia Meteorological effects Meteorological parameters Power station Real measured data Recursive prediction Salt deposition Suspension types Transformer bushings Learning algorithms Electrical power system lines sometimes pass along the coastal regions and transverse through the industrial areas of the Peninsular Malaysia. The phenomenon of salt blown from the sea to the land at the coastal area was causing salt deposition to the transformer bushing which contaminating the bushing surfaces and produced leakage current. Hence, it triggering to insulator flashover and finally the hot power arc will damage the bushing. This paper estimates leakage current level by modeling it as a function of various meteorological parameters using Hybrid Multilayered Perceptron Networks (HMLP) with Modified Recursive Prediction Error (MRPE) learning algorithms. The results are also compared with the regression analysis done previously. Meteorological parameters and leakage current data are based on the real measured data collected at YTL Paka Power Station in Terengganu. � 2009 IEEE. Final 2023-12-29T07:50:45Z 2023-12-29T07:50:45Z 2009 Conference paper 10.1109/ISIEA.2009.5356498 2-s2.0-76449086772 https://www.scopus.com/inward/record.uri?eid=2-s2.0-76449086772&doi=10.1109%2fISIEA.2009.5356498&partnerID=40&md5=af7b0c4312ef0afffb4b3990d7ea6d47 https://irepository.uniten.edu.my/handle/123456789/30643 1 5356498 35 40 Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	ANN HMLP Insulators Leakage current MRPE Regression analysis Bushings Coastal zones Industrial electronics Leakage currents Metal analysis Neural networks Regression analysis Statistics ANN Coastal area Coastal regions Electrical power system High voltage insulators HMLP Hybrid multilayered perceptron network Industrial area Insulator flashover Malaysia Meteorological effects Meteorological parameters Power station Real measured data Recursive prediction Salt deposition Suspension types Transformer bushings Learning algorithms
spellingShingle	ANN HMLP Insulators Leakage current MRPE Regression analysis Bushings Coastal zones Industrial electronics Leakage currents Metal analysis Neural networks Regression analysis Statistics ANN Coastal area Coastal regions Electrical power system High voltage insulators HMLP Hybrid multilayered perceptron network Industrial area Insulator flashover Malaysia Meteorological effects Meteorological parameters Power station Real measured data Recursive prediction Salt deposition Suspension types Transformer bushings Learning algorithms Dahlan N.Y. Kasuan N. Ahmad A.S. Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
description	Electrical power system lines sometimes pass along the coastal regions and transverse through the industrial areas of the Peninsular Malaysia. The phenomenon of salt blown from the sea to the land at the coastal area was causing salt deposition to the transformer bushing which contaminating the bushing surfaces and produced leakage current. Hence, it triggering to insulator flashover and finally the hot power arc will damage the bushing. This paper estimates leakage current level by modeling it as a function of various meteorological parameters using Hybrid Multilayered Perceptron Networks (HMLP) with Modified Recursive Prediction Error (MRPE) learning algorithms. The results are also compared with the regression analysis done previously. Meteorological parameters and leakage current data are based on the real measured data collected at YTL Paka Power Station in Terengganu. � 2009 IEEE.
author2	24483200900
author_facet	24483200900 Dahlan N.Y. Kasuan N. Ahmad A.S.
format	Conference paper
author	Dahlan N.Y. Kasuan N. Ahmad A.S.
author_sort	Dahlan N.Y.
title	Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
title_short	Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
title_full	Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
title_fullStr	Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
title_full_unstemmed	Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network
title_sort	modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using hmlp neural network
publishDate	2023
_version_	1806428452572626944
score	13.211869

Modelling of various meteorological effects on leakage current level for suspension type of high voltage insulators using HMLP neural network

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