Oladimeji Ibrahim
@unilorin.edu.ng
Assistant Professor, Faculty of Engineering and Technology
Others
University of Ilorin
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Energy Engineering and Power Technology, Control and Systems Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, and Temitope Ibrahim Amosa
Elsevier BV
A. O. Otuoze, M. W. Mustafa, U. Sultana, E. A. Abiodun, B. Jimada-Ojuolape, O. Ibrahim, I. O. Avazi-Omeiza, and A. I. Abdullateef
African Journals Online (AJOL)
The successful implementation of Smart Grids heavily relies on energy efficiency, particularly through the Advanced Metering Infrastructure (AMI) and Smart Electricity Meters (SEM). However, cyber-attacks pose a threat to SEM, with electricity theft being a primary motivation. Despite the valuable data provided by SEM for analytical purposes, existing methods to identify theft involve cumbersome and costly on-site inspections. This research proposes an electricity theft detection model using the Long Short-Term Memory (LSTM) network. The model employs a collective anomaly approach, defining prediction errors through a threshold and forecast horizon. Suspicious consumption profiles are analysed, and a fuzzy inference system (FIS) implemented in MATLAB 2021b is used to model security risks based on these profiles. The study utilizes energy consumption data from four diverse consumer profiles (consumers 1, 2, 3, and 4) to develop consumer-specific LSTM models for detection and an FIS model for confirmation. Tampered consumer data is identified and confirmed based on selected AMI parameters. While all consumers exhibit suspicious profiles at times, only consumers 2 and 3 are confirmed as engaging in electricity theft. This research provides a robust approach to detecting and verifying fraudulent consumption profiles within the context of AMI, offering a more reliable dimension to theft detection and confirmation.
Temitope Ibrahim Amosa, Patrick Sebastian, Lila Iznita Izhar, Oladimeji Ibrahim, Lukman Shehu Ayinla, Abdulrahman Abdullah Bahashwan, Abubakar Bala, and Yau Alhaji Samaila
Elsevier BV
Oladimeji Ibrahim, Mutiu Shola Bakare, Temitope Ibrahim Amosa, Abdulrahman Okino Otuoze, Waheed Olaide Owonikoko, Esraa Mousa Ali, Lambe Mutalub Adesina, and Olalekan Ogunbiyi
Elsevier BV
Temitope Ibrahim Amosa, Lila Iznita Bt Izhar, Patrick Sebastian, Idris B. Ismail, Oladimeji Ibrahim, and Shehu Lukman Ayinla
Institute of Electrical and Electronics Engineers (IEEE)
The adoption of Electronic Health Record (EHR) and other e-health infrastructures over the years has been characterized by an increase in medical errors. This is primarily a result of the widespread usage of medical acronyms and abbreviations with multiple possible senses (i.e., ambiguous acronyms). The advent of Artificial Intelligence (AI) technology, specifically Natural Language Processing (NLP), has presented a promising avenue for tackling the intricate issue of automatic sense resolution of acronyms. Notably, the application of Machine Learning (ML) techniques has proven to be highly effective in the development of systems aimed at this objective, garnering significant attention and interest within the research and industry domains in recent years. The significance of automating the resolution of medical acronym senses cannot be overstated, especially in the context of modern healthcare delivery with the widespread use of EHR. However, it is disheartening to note that comprehensive studies examining the global adoption of EHR, assessing the impact of acronym usage on medical errors within EHR systems, and reporting on the latest trends and advancements in ML-based NLP solutions for disambiguating medical acronyms remain severely limited. In this current study, we present a detailed overview on medical error, its origins, unintended effects, and EHR-related errors as a subclass of clinical error. Furthermore, this paper investigates the adoption of EHR systems in developed and developing nations, as well as the review concludes with an examination of various artificial intelligence techniques, particularly machine learning algorithms for medical acronym and abbreviation disambiguation in EHRs.
Olatunji Obalowu Mohammed, Mohd Wazir Mustafa, Sani Salisu, Ahsanullah Memon, Saddam Hussain, Abdulrahaman Okino Otuoze, and Oladimeji Ibrahim
Institute of Advanced Engineering and Science
Available transfer capability (ATC) is an important metric used to measure the techno-economic viability of the transmission networks. Several methods have been presented in literature for ATC assessment, however, only some few articles incorporate CBM in ATC calculation and those few papers only considered conventional power generation sources in CBM evaluation. CBM is a function of the reliability of generating units. This paper presents the inter-area CBM calculation in the presence of wind energy source using graph theory technique and the results are incorporated in ATC computation using repeated power flow. CBM is incorporated in ATC computation as non-recallable and recallable power transfers. The results with and without CBM incorporation, in the presence of wind power system, are compared. The contribution of the paper is to study the influence of wind power (WP) integrated CBM on ATC evaluation. The results showed that the incorporation of CBM, in the presence of renewable energy, has a significant influence on ATC, without which ATC would be inaccurately estimated. Simulations using IEEE 24-Bus RTS is used to implement the proposed approach. This approach can be employed by transmission operators to assess the technoeconomic viability of the power network for possible power transactions.
Nor Zaihar Yahaya, Oladimeji Ibrahim, Temitope Ibrahim Amosa, Nordin Saad, and Sheikh Tanzim Meraj
IEEE
A DC-DC converter produces constant output voltage in the face of varying supply voltage, load current change, and circuit element variation. To achieve tight output voltage regulation in the presence of various disturbances, DC-DC converters incorporate a control strategy to regulate power flow and power level. In recent times, several control strategies have been investigated for regulating the action of DC-DC converters, ranging from the conventional frequency domain to time domain design approaches. However, not enough attention is given to the performance of the state feedback controller, especially during rapid load current change in dc-dc converter. In this paper, a full order state-feedback controller was designed, and the performance was investigated for rapid load current change. A state feedback controller was first designed in this work, and then the integrator is introduced to eliminate the inherent steady-state error for improved system robustness to disturbance rejection. The state feedback controller performance was evaluated by subjecting the converter to various step load current changes in which the controller rejected the disturbance faster when compared with the PID controller used as a base controller. The fast transient response will allow the DC-DC converter to accept wider current change from rapidly changing loads and achieve improved output voltage regulation.
Temitope Ibrahim Amosa, Patrick Sebastian, Lila Iznita Izhar, and Oladimeji Ibrahim
IEEE
Variations in visual factors such as illumination, viewpoint, resolution, background, pose, and so on are commonly regarded as significant issues in object re-identification (re-ID). Despite widespread recognition of their importance in determining the performance of an object re-ID model, not enough attention is paid to how these factors affect re-ID systems. One of the major impediments to investigating how these factors affect the performance of re-ID models is the lack of datasets with unbiased distribution of these difficult visual conditions. To make up for the lack of large-scale datasets with a balanced distribution of such photometric and geometric transforms, recent studies suggest using game engines to generate synthetic datasets. This study proposes a quantitative investigation of the impact of two critical visual factors: illumination and Tranfomer-based re-ID models on synthetic dataset.
Temitope Ibrahim Amosa, Patrick Sebastian, Lila Iznita Bt Izhar, and Oladimeji Ibrahim
IEEE
Owing to several breakthroughs in deep-learning research, visual object trackers based on deep learning algorithms have been the de facto method in the tracking community. However, the performance of this category of trackers is largely influenced by the richness and quality of the target feature representation. Thus, to extract features with high discriminative power, special attention must be paid to the feature extraction component of the tracker. Despite the significance of feature extraction paradigm in deep learning-based trackers, limited studies have been dedicated to comparatively examining the feature learning and representation capabilities of various existing deep feature extraction approaches in visual tracking. In this paper, we present a comparative study on two different deep feature extraction methods in visual tracking of industrial robots in video. This work examines and visualizes the feature representation capability of two commonly employed feature extraction methods in deep learning-based tracking; namely, Convolutional Neural Network (CNN)-based and Transformer-based feature extraction methods. To demonstrate the effectiveness of the deep learning-based tracking paradigm, this study adopts a Siamese-based tracker that is trained end-to-end offline with ILSVRC15 datasets as well as a Transformer-based tracking architecture that is also pre-trained on the ImageNet dataset. This study also contributes a dataset consisting of images of industrial robots, which was employed for evaluating the two adopted trackers. From this study, we could conclude that the feature learning and representation of the transformer-based feature extraction pipeline largely improved the overall tracking performance of the tracker.
Mudathir Funsho Akorede, Oladimeji Ibrahim, Abdulrahaman Okino Otuoze, Akinola Sunday Oladeji, Ahmad Opeyemi Zubair, and Muhydeen Oluwafemi Tijani
IEEE
Aggregate Technical, Commercial and Collection (ATC&C) losses in power networks occur due to technical and commercial reasons. These losses not only reduce the system efficiency, but also increase the operational costs of the power distribution companies. To effectively minimize the ATC&C losses, power utilities must first be able to quantify the technical losses (TL) arising from the current flowing through the network elements. This study employs the forward/backward sweep power flow approach to calculate the TL. In the work, a real-life 11 kV radial distribution feeder is used as a case study to evaluate the performance of the algorithm. Two loading scenarios are considered in the study and results of the algorithm, developed in MATLAB, are presented. Numerical results obtained on the case study feeder reveal that the TL is a function of the loading of the network. The feeder when loaded to 65% of capacity recorded a total power losses of 2.4096 MW, which is equivalent to 18.5% of the injected power. On the other hand, the feeder total losses increase to 7.1112 MW, equivalent to 40% of the feeder capacity, when loaded to 90% of its capacity. The two cases result in several bus voltages falling below the lower permissible limit of 0.94 p.u., which is a clear indication that the feeder under study requires a compensation.
Farhan Mumtaz, Nor Zaihar Yahaya, Sheikh Tanzim Meraj, Balbir Singh, Ramani Kannan, and Oladimeji Ibrahim
Elsevier BV
Abdulrahaman Okino Otuoze, Olatunji Obalowu Mohammed, Oladimeji Ibrahim, Sani Salisu, Abioye Abiodun Emmanuel, Ayinde Mohammed Usman, and Abdulhakeem Mohd Dobi
Wiley
Various techniques have been investigated and proposed for core loss minimization in electrical machines. Nevertheless, many of such methods are mostly complicated and not suitable for consideration at a preliminary design stage. In this work, a simplified procedure which uses an analytical approach to minimizing the field's losses of an Axial Flux Permanent Magnet Alternator (AFPMA), is presented. First, the output equation of an AFPMA is referred, and then the minimization of the losses is investigated by analytical differential equations. The result of the derived‐specific magnetic loading is investigated using three different core materials, namely 35RM300, 50JN350, and 65JN800, and is found to reduce with increased frequencies. The 35RM300 core material gives the maximum specific magnetic loading and minimum power loss at investigated frequencies of 50 to 500 Hz. Although the 35RM300 core material gives the best performance, the optimal values are only determined as suitable by the manufacturer's design criteria. This study is a key indicator for a simple and efficient core material selection in the design of a Wind‐Powered AFPMA without the need for complicated analyses at the preliminary design stage.
Esraa Mousa Ali, Nor Zaihar Yahaya, Omar Aqeel Saraereh, Anwar Hamdan Al Assaf, Bilal Hasan Alqasem, Shahid Iqbal, Oladimeji Ibrahim, and Amit V Patel
MDPI AG
A voltage multiplier rectenna is a combination of a voltage multiplier rectifier and an antenna used for the conversion of AC to DC. It is an essential part of the system of RF energy harvesting. Conventional rectennas are characterized by low conversion efficiency. This study presents an analytical novel mode designed for RF energy harvesting systems to study the voltage and current output of rectifier stages for efficiency optimization. The design contains a voltage multiplier rectification circuit with seven stages. The Schottky diode HSMS 285-C was selected for the circuit modeling voltage multiplier circuit. Advanced Design System (ADS) simulation was used to validate the equations of the theoretical model solved with MATLAB code. The fabricated system was tested for an input power range of 10 μW to 100 mW; the maximum output power is 0.2577 mW with maximum efficiency of 29.85%.
Mohammed Ahmed Yagoub, Zheng Tao, and O.M.S.O. Ibrahim
IEEE
In recent years a direct current (DC) micro-grid has been preferred in power systems design, generation, and distribution of DC systems. DC microgrid protection and operation one of the common problems in this type of DC system and there are several studies and scientific papers that have been completed to study this problem and solve it and research is continued to get a suitable solution to this challenge. This paper investigates DC micro-grid protection analysis with different types of faults and the effects on power electronics devices like voltage source converter (VSC), DC-DC converter, and impact in power loads.
M.A. Yagoub, T. Zheng, and O.M.S.O. Ibrahim
Institution of Engineering and Technology
Fault protection for DC Microgrid one of the challenges in the power system. All previous studies focus on protection due to the difficulty of linking DC and AC sources without designing a suitable protection system to operate this network in one network, and this network is called Microgrid (AC or DC). In this paper, a new DC Microgrid is designed. This Microgrid contains wind energy, Photovoltaic System (PV) with batteries, and the main grid (AC). Different types of fault analysis have been disused in this paper, like overcurrent protection, distance protection, and differential protection.
Oladimeji Ibrahim, Waheed Olaide Owonikoko, Abubakar Abdulkarim, Abdulrahman Okino Otuoze, Mubarak Akorede Afolayan, Ibrahim Sani Madugu, Mutiu Shola Bakare, and Kayode Elijah Adedayo
Universiti Putra Malaysia
A mismatch between utility-scale electricity generation and demand often results in resources and energy wastage that needed to be minimized. Therefore, the utility company needs to be able to accurately forecast load demand as a guide for the planned generation. Short-term load forecast assists the utility company in projecting the future energy demand. The predicted load demand is used to plan ahead for the power to be generated, transmitted, and distributed and which is crucial to power system reliability and economics. Recently, various methods from statistical, artificial intelligence, and hybrid methods have been widely used for load forecasts with each having their merits and drawbacks. This paper investigates the application of the fuzzy logic technique for short-term load forecast of a day ahead load. The developed fuzzy logic model used time, temperature, and historical load data to forecast 24 hours load demand. The fuzzy models were based on both the trapezoidal and triangular membership function (MF) to investigate their accuracy and effectiveness for the load forecast. The obtained low Mean Absolute Percentage Error (MAPE), Mean Forecast Error (MFE), and Mean Absolute Deviation (MAD) values from the forecasted load results showed that both models are suitable for short-term load forecasting, however the trapezoidal MF showed better performance than the triangular MF.
Farhan Mumtaz, Nor Zaihar Yahaya, Sheikh Tanzim Meraj, Ramani Kannan, Balbir Singh Mahinder Singh, and Oladimeji Ibrahim
IEEE
In order to fulfill the increasing demands of energy requirements using the eco-friendly methods of energy generation instead of conventional hazardous methods that have caused severe damages globally. Hybrid renewable energy sources (HRES) are utilized for energy generation for developing smart cities and to make the power systems efficient. HRES systems are designed considering the advance requirements of energy consumption. As the technology is evolving, scientists have developed power saving appliances that operates on low level DC voltage. Since different appliances have different DC voltage ratings, to operate them efficiently multi-level DC voltages are often required. Conventional power systems offer single input and single output (SISO) configuration that cannot fulfill the power requirements of domestic and commercially utilized appliances. However, multi-input multi-output (MIMO) configuration is suitable to fulfil the multi-level voltage requirements. DC-DC converters are responsible to deliver the stable output power in HRES systems. This paper presents implementation of MIMO network using buck-boost converters. The proposed system is simulated in MATLAB Simulink with all possible scenarios. To control the operation of a buck-boost converter, individual control technique is integrated to sustain the desired output value during intermittent conditions. For that purpose, proportional integral (PI) is utilized as a control technique, that regulates the operation of a buck-boost converter with different input and output settings.
Lambe Mutalub Adesina, Ademola Abdulkareem, Olalekan Ogunbiyi, and Oladimeji Ibrahim
Elsevier BV
Ibrahim Oladimeji, , Hassan Miya Sabo, Abdulkarim Abubakar, Akorede F. Mudathir, Amuda A.Y. Sulyman, , , , and
International Hellenic University
Thermistors are widely used in temperature measurement due to their fast response, high accuracy, and low cost. However, due to the nonlinear resistance-temperature relationship, there is a need for linearisation in order to design a signal conditioning circuit for accurate temperature measurement. Thus, this paper presents the design of a thermistor signal conditioning circuit based on Wheatstone Bridge. An experiment was conducted on an NTC thermistor to acquire the resistance response to temperature change between 25 oC to 65o C which was in turn used for the model linearization. The obtained parameters from the linearized model are used to design the Wheatstone bridge signal conditioning circuit. The designed measurement system performance evaluation demonstrated a high degree of accuracy with only 1.1 % non-linearity within the specified temperature range.
O. M. S. O Ibrahim, T. Zheng, and X. Zheng
IEEE
the magnetizing inrush current of the power transformer is a significant challenge to be successfully identified by the differential protection relay. In this paper, an approach based on wavelet coefficients energy is presented to successfully identify the inrush currents. The wavelet transform is applied to decompose the differential currents into the details coefficients in several levels of frequency bands; it is observed by inspecting different inrush and internal faults cases, a fault condition is the most probable if a remarkable change in detail coefficients is noticed. This fact is utilized in order to establish a diagnosis criterion, where the relative wavelet energy is defined as a characterizing quantity. The discrimination criteria is based on the energy variation amount, which is monitored comparing the values of the relative wavelet energy in two successive time intervals, where an inrush is detected generally when the difference is not a remarkable quantity. The reliability of the proposed approach is checked through simulation of different transient cases using MATLAB.
Khalid Yahia Ahmed, Nor Zaihar Bin Yahaya, Vijanth Sagayan Asirvadam, Nordin Saad, Ramani Kannan, and Oladimeji Ibrahim
Institute of Electrical and Electronics Engineers (IEEE)
In recent years, power electronic distribution transformers (PEDTs) have become an attractive replacement for conventional transformers. This is due to their smaller size, improved dynamic performance, and better power quality. However, their operation with a conventional controller such as a proportional integral (PI) does not give satisfactory performance. Thus, improved dynamic performance and high power quality of the PEDT can be achieved with an intelligent control. In this paper, a novel design topology and an improved controller for a PEDT are proposed. The proposed controller is based on the adaptive PI-fuzzy logic controller (API-FLC). The FLC is applied to adapt the PI controller gains when there is a sudden change in the system parameters. The PEDT with the novel controller is designed to achieve constant dc link voltages, sinusoidal voltage, and current with unity power factor under different operating conditions. The model is simulated and validated using MATLAB/Simulink software. Different operating conditions, including voltage sag, voltage harmonics, sudden load change, and short circuit, have been investigated. The results obtained with the API-FLC controller give a better dynamic performance and improved power quality when compared to the conventional PI controller. Therefore, the PEDT based on API-FLC has the advantages of eliminating transient power quality problems and improving system efficiency.
Oladimeji Ibrahim, Nor Zaihar Yahaya, and Nordin Saad
Institute of Advanced Engineering and Science
Design of phase-shifted full bridge zero voltage switching DC-DC converter has been very challenging due to circuit parasitic effect on the system dynamics. This paper presents steady-state analysis and iterative approach for the systemic design of phase-shifted full bridge DC-DC converter with improved dynamic performance and satisfactory operational requirement in terms of zero-voltage switching range, operating switching frequency and switching resonance. A 3 kW DC-DC converter is designed using the iterative design approach and the system dynamics performance was investigated in the MATLAB/Simulink environment. The converter zero-voltage switching simulation results were satisfactory with 90% efficiency under full load condition.
Muhammad Wasif Umar, NorZaihar Yahya, Zuhairi Baharuddin, and Oladimeji Ibrahim
IEEE
Switch mode power converters otter an efficient solution for driving high-brightness LEDs in an enormous range of applications. These driving converters usually rely on analog control techniques to ensure the optimal flow of current through the LEDs and provide dimming features. However, due to their inflexibility and non-configurability analog control schemes are not a good option especially in high end applications such as backlighting and automotive lighting. Recently, digital power management of high-brightness LED systems based on microprocessors and digital signal controllers (DSC) has emerged as an alternative to traditional analog control. These control schemes can actually improve overall system performance by adding some extra features like low power consumption, increased system reliability and better design flexibility for a specific application. This paper presents a digital signal controller based control scheme of switching power converter for high-brightness LED applications. A design example based on dc-dc boost topology is presented to provide a useful guide for control design engineers with the perspective of digital power control.
Oladimeji Ibrahim, Nor Zaihar Yahaya, Nordin Saad, and Khalid Y. Ahmed
Institute of Electrical and Electronics Engineers (IEEE)
Controllers are designed to regulate output voltage and improve dynamic performance of dc–dc converter to variable supply voltage, load current or circuit element variation. Conventional controller like PID has narrow dynamics that limit its application to quiescent supply input voltage and load current change. Recent research efforts are exploiting state of the art power electronics devices and high computational speed digital signal processor to improve transient and dynamics performance of power converters through advanced modern control techniques. This paper presents a design and evaluation of observer state output feedback controller for phase-shifted full bridge zero voltage switching dc–dc converter output voltage regulation to widen the supply input voltage. The converter closed-loop control was implemented in MATLAB/Simulink environment and the results demonstrated improved transient response to wider supply voltage and sudden load current change as compared with the conventional PID controller.
K. Y. Ahmed, N. Z. Yahaya, V. S. Asirvadam, K. Ramani, and O. Ibrahim
IEEE
This paper presents a voltage oriented control (VOC) for a three level, three-phase PWM rectifier using a fuzzy logic control strategy. The PI control was replaced by fuzzy control aimed to reduce the total harmonic distortion (THD) on the grid side, to improve the power factor (PF) as well as keep the output DC voltage to the required level when a dynamic disturbance happens. The MATLAB/Simulink and fuzzy logic toolboxes have been used to investigate the steady-state and transient-state behaviors for the proposed controller. As the result shows, it was verified that the fuzzy logic controller is much better than the traditional PI controller, and the fuzzy logic controller provides a stellar performance in the transient state.