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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science

Hashim Hizam

Universiti Putra Malaysia

Author-ID : 2397762

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 4 Documents Claim Missing Document

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Articles

Transmission line fault identification and classification with integrated FACTS device using multiresolution analysis and naïve bayes classifier Elhadi Emhemed Aker; Mohammad Lutfi Othman; Ishak Aris; Noor Izzri Abdul Wahab; Hashim Hizam; Osaj Emmanuel
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

This paper is present a novel approach for solving the pending under-reach problem encountered by distance relay protection scheme in the 3rd zones protection coverage for a midpoint STATCOM compensated transmission lines. The propose transmission line model is develop in Matlab for analyzed feature extraction using Discrete Wavelet multiresolution analysis approach. Extracted feature from standard deviation and entropy energy contents of SLG transient faults current at location beyond the integrated STATCOM used for machine learning algorithm model building using WEKA software. The Naïve Bayes classifier model perform best with robustness prediction and detection of faults with quick convergence even with less training data. The outperformance of the proposed classifier has been 100 % for the relay algorithm modification for under-reach problem elimination in 3rd zones protection coverage.

Feasibility analysis of standalone PV powered battery using SEN for Smart Grid Syed Zahurul Islam; Mohammad Lutfi Othman; Norman Mariun; Hashim Hizam; Nur Ayuni
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

In Smart Grid (SG) communication network, sensors integrated communication radios namely ZigBee, Wi-Fi, and Bluetooth are becoming urgent and crucial part of SG wireless communication. Sensor nodes are generally battery powered. With the enhancement and huge utilization of sensor technologies, batteries have not been improved significantly at the same pace. However, batteries are essential to power the sensor nodes and there is no alternative of this energy bank. Therefore, to provide seamless power to the nodes is a challenge when the nodes are meant for integrating distributed renewable generations for years. Necessitate of the battery replacement is not often cost effective when the batteries are drained out. This paper presents a feasibility study of standalone Photovoltaic (PV) powered battery using Sensors-radios integrated Embedded Node (SEN) for SG application. In this study, we have analyzed charging characteristics of a lead-acid battery that can be recharged during day time by a PV module. The aim of this research is to testify the two simultaneous jobs- (i) the battery is sufficient to power Sensors-ZigBee integrated Arduino (SZA) for at least one day operation, (ii) scrutiny the optimal size of PV for recharging the battery considering three different day variations- average, cloudy, and full rainy day. The result from real data analysis reveals that the module is sufficient to recharge the battery on an average day; however, it is not sufficient for full cloudy or full rainy day. Finally, a mathematical model is obtained from regression analysis that shows battery internal resistance is exponential to voltage on both full cloudy and rainy day, but it is linear on average day.

Adaptive ANN based differential protective relay for reliable power transformer protection operation during energisation Azniza Ahmad; Mohammad Lufti Othman; Kurreemun Khudsiya Bibi Zainab; Hashim Hizam; Norhafiz Azis
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Power transformer is the most expensive equipment in electrical power system that needs continuous monitoring and fast protection response. Differential relay is usually used in power transformer protection scheme. This protection compares the difference of currents between transformer primary and secondary sides, with which a tripping signal to the circuit breaker is asserted. However, when power transformers are energized, the magnetizing inrush current is present and due to its high magnitude, the relay mal-operates. To prevent mal-operation, methods revolving around the fact that the relay should be able to discriminate between the magnetizing inrush current and the fault current must be studied. This paper presents an Artificial Neural Network (ANN) based differential relay that is designed to enable the differential relay to correct its mal-operation during energization by training the ANN and testing it with harmonic current as the restraining element. The MATLAB software is used to implement and evaluate the proposed differential relay. It is shown that the ANN based differential relay is indeed an adaptive relay when it is appropriately trained using the Network Fitting Tool. The improved differential relay models also include a reset part which enables automatic reset of the relays. Using the techniques of 2nd harmonic restraint and ANN to design a differential relay thus illustrates that the latter can successfully differentiate between magnetizing inrush and internal fault currents. With the new adaptive ANN-based differential relay, there is no mal-operation of the relay during energization. The ANN based differential relay shows better performance in terms of its ability to differentiate fault against energization current. Amazingly, the response time, when there is an internal fault, is 1 ms compared to 4.5 ms of the conventional 2nd harmonic restraint based relay.

Faults Signature Extraction in Wind Farm Integrated Transmission Line Topology Osaji Emmanuel; Mohammad Lutfi Othman; Hashim Hizam; Muhammad M. Othman; Elhad Akar E.; Okeke Chidiebere A.; Nwagbara Samuel O.
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp246-253

The integration of Renewable Green Energy Sources (RGES) like Wind Farm Generators (WFG), and Photo Voltaic (PV) systems into convention power system as a future solution to the increase in global energy demands, generation cost reduction, and limited climate impact. The innovation introduced protection compromise challenges in power system due to in-feeds fault current penetration from RGES on existing system, leading to an undesired trip of the healthy section of TL, equipment damages, and safety failure. A comparison study of extracted faults signature from two proposed Transmission Line (TL) network topologies with and without WFG integration, for onward fault identification, and classification model design. Descrete wavelet multiresolution Analysis (DWMRA) of extracted one-cycle fault signal signatures from 11 faults type’s scenarios in Matlab. Result demonstrated a unique fault signatures across all simulated faults scenarios harness for future work of an adaptive unit protection model for this new area of DG integration.

Co-Authors Azniza Ahmad Elhad Akar E. Elhadi Emhemed Aker Ishak Aris Kurreemun Khudsiya Bibi Zainab Mohammad Lufti Othman Mohammad Lutfi Othman Muhammad M. Othman Noor Izzri Abdul Wahab Norhafiz Azis Norman Mariun Nur Ayuni Nwagbara Samuel O. Okeke Chidiebere A. Osaj Emmanuel Osaji Emmanuel Syed Zahurul Islam

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