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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Ayokunle Awelewa
Covenant University
Computer Science & IT Electrical & Electronics Engineering

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Power distribution system fault monitoring device for supply networks in Nigeria Olalekan Kabiru Kareem; Aderibigbe Adekitan; Ayokunle Awelewa
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (796.939 KB) | DOI: 10.11591/ijece.v9i4.pp2803-2812

Abstract

Electric power is the bedrock of our modern way of life. In Nigeria, power supply availability, sufficiency and reliability are major operational challenges. At the generation and transmission level, effort is made to ensure status monitoring and fault detection on the power network, but at the distribution level, particularly within domestic consumer communities there are no fault monitoring and detection devices except for HRC fuses at the feeder pillar. Unfortunately, these fuses are sometimes replaced by a copper wire bridge at some locations rendering the system unprotected and creating a great potential for transformer destruction on overload. This study is focused on designing an on-site power system monitoring device to be deployed on selected household entry power cables for detecting and indicating when phase off, low voltage, high voltage, over current, and blown fuse occurs on the building’s incomer line. The fault indication will help in reducing troubleshooting time and also ensure quick service restoration. After design implementation, the test result confirms design accuracy, device functionality and suitability as a low-cost solution to power supply system fault monitoring within local communities.
State of charge estimation based on a modified extended Kalman filter Koto Omiloli; Ayokunle Awelewa; Isaac Samuel; Oghorchukwuyem Obiazi; James Katende
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5054-5065

Abstract

The global transition from fossil-based automobile systems to their electric-driven counterparts has made the use of a storage device inevitable. Owing to its high energy density, lower self-discharge, and higher cycle lifetime the lithium-ion battery is of significant consideration and usage in electric vehicles. Nevertheless, the state of charge (SOC) of the battery, which cannot be measured directly, must be calculated using an estimator. This paper proposes, by means of a modified priori estimate and a compensating proportional gain, an improved extended Kalman filter (IEKF) for the estimation task due to its nonlinear application and adaptiveness to noise. The improvement was achieved by incorporating the residuals of the previous state matrices to the current state predictor and introducing an attenuating factor in the Kalman gain, which was chosen to counteract the effect of the measurement and process noise resulting in better accuracy performance than the conventional SOC curve fitting-based estimation and ampere hour methods. Simulation results show that the standard EKF estimator results in performance with an error bound of 12.9% due to an unstable start, while the modified EKF reduces the maximum error to within 2.05% demonstrating the quality of the estimator.
Progressive energy management technique for smart load control Timilehin Sanni; Mobolade Olawale; Amarachi Attah; Anthony Adoghe; Ayokunle Awelewa
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 5: October 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i5.25861

Abstract

Electricity demand is rapidly increasing in many countries especially because of the increase in smart appliances, smart cities, and communities. The use of electricity ranges from agricultural load, to commercial and industrial load, and also residential load which account for the largest contributor to the increase in peak demand. Thus, residential consumers play a massive role in the national demand for electrical energy and power. The increased demand puts increasing pressure on the energy suppliers who force consumers to cope with short peaks. The need arises for an energy management technique to reduce energy consumption by allowing for consumer load control. The method explores using a Raspberry Pi to collect and evaluate the energy consumed over time and allow consumers access to directly control their home appliances. A more accurate load curve is deduced using the new readings gotten from the end-users. The data obtained from the proposed system is sent to a progressive web application that allows users manage their energy consumption.
Co-Authors Aderibigbe Adekitan Amarachi Attah Anthony Adoghe Isaac Samuel James Katende Koto Omiloli Mobolade Olawale Oghorchukwuyem Obiazi Olalekan Kabiru Kareem Timilehin Sanni