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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science

H. A. Hamid

Universiti Malaysia Perlis (UniMAP)

Author-ID : 2464488

Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document

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Modelling and simulation of online partial discharge measurement for medium voltage power cable A. Z. Abdullah; M. Isa; M. N. K. H. Rohani; H. A. Hamid; M. H. Amlus; N. Azizan
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents the modelling of the online partial discharge (PD) measurement of the medium voltage (MV) power cable. Recently, PD monitoring trends are rapidly increasing due to high demand on reliable systems. Degradation are mainly due to the presence of PD in the high voltage power equipment used. PD measurement is therefore a highly recommended task to early detection of the degradation insulation for high voltage (HV) equipment in order to avoid breakdowns. Real network modelling is necessary to improvise system design in order to find the efficiency in a real power system network. In this paper, modelling focuses on a real distribution network by applying Rogowski coil (RC) as a detection sensor to trigger PD activity. The simulation is performed to determine the functionality and reliability of the system with the RC application in the network. The analysis is performed in the ATP-EMTP and MATLAB Simulink software environments. In addition, this paper contributed to justify the approach of a simplified PD sensor and measurement system. This PD measurement system provides a complete solution in the context of condition-oriented monitoring for the ability to apply the RC to trigger PD activity in the power distribution network.

An alternative approaches to predict flashover voltage on polluted outdoor insulators using artificial intelligence techniques Ali. A. Salem; Rahisham Abd Rahman; M. S. Kamarudin; N. A. Othman; N. A. M. Jamail; H. A. Hamid; M. T. Ishak
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents an alternative approach for predicting critical voltage of pollution flashover by using Artificial Intelligence (AI) technique. Data from experimental works combined with the theoretical results from well-known theoretical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining critical voltage of flashover. Series of laboratory testing and measurement are carried for 1:1, 1:5 and 1:10 ratios of top to bottom surface salt deposit density on cup and pin insulators. Insulators variables such as height H, diameter D, form factor F, creepage distance L, equivalent salt deposit density (ESDD) and flashover voltage correction are identified and used to train the AI network. Comparative studies have evidently shown that the proposed (AI) technique gives the satisfactory results compared to the analytical model and test data with the Coefficient of determination R-Square value of more than 97%.

Co-Authors A. N. Nanyan A. Z. Abdullah Ali. A. Salem H. S. A. Halim M. H. Amlus M. Isa M. N. K. H. Rohani M. S. Kamarudin M. T. Ishak N. A. M. Jamail N. A. Othman N. Azizan Rahisham Abd Rahman S. N. M. Arshad

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Journal : Bulletin of Electrical Engineering and Informatics