Scholarly Publication

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    Synchrophasor-Based Dynamic Thermal Rating System for Sustainable Cyber- Physical Power Systems
    (CRC press, Tailor and Francis group, 2023) Jimada-Ojuolape, Bilkisu; Teh, Jiashen; Arowolo, Olaolu Micheal
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    Reliability Enhancement of Synchrophasor-Based DTR system considering N-1 contingency for PMU placement
    (IEEE, 2022-01-03) Jimada-Ojuolape, Bilkisu
    The cyber power network has become more intelligent and efficient because of the integration of information and communication technology (ICT) infrastructure. By combining intelligent infrastructure such as phasor measurement units (PMUs), smart sensors, and other two-way communication and monitoring capabilities, this enhances reliability and sustainability. They do, however, have some disadvantages, such as component and communication network failures, as well as cyber breaches, which might compromise the existing network's reliability. Dynamic Thermal Rating (DTR) systems which is a smart grid technology, improves existing line ratings by allowing them to be increased based on several parameters without violating line safety requirements. Thus, this paper presents a DTR system that uses PMUs to implement Wide Area Monitoring (WAM) functions and investigates the impact of PMU failures and line outages on cyber-physical network reliability. The study uses a Monte Carlo simulation- based method to carry out the investigation on the IEEE RTS while considering the impacts of seven and thirteen PMUs. The test network is modified to emphasize the benefits of ICTs and the findings show that using PMUs enhances reliability greatly. While the use of seven PMUs offers reliability improvement by 53.15%, the use of 13 PMUs offers more significant improvement (by 95.79%) because a single line outage will not affect network observability.
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    Detection and Confirmation of Electricity Thefts in Advanced Metering Infrastructure by Long Short- Term Memory and Fuzzy Inference System Models
    (NIGERIAN JOURNAL OF TECHNOLOGICAL DEVELOPMENT, 2024) Otuoze, Abdulrahman; Mustafa, M; Sultana, U; Abiodun, E; Jimada-Ojuolape, Bilkisu; Ibrahim, O; Avazi-Omeiza, I; Abdullateef, A
    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.
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    Enhancing Human Identification Systems Through Bi-modal Fusion Using Negative Selection Algorithm
    (COVENANT JOURNAL OF ENGINEERING TECHNOLOGY, 2024-02-27) Balogun, Monsurat O; Jimada-Ojuolape, Bilkisu; Odeniyi, Latifat A
    The Negative Selection Algorithm (NSA) is a computational technique inspired by the human immune system and widely used in various fields like intrusion detection, network security, data mining, and pattern recognition. However, its effectiveness in human identification has not been thoroughly explored. This study focuses on utilizing NSA for human image classification, specifically in a bi-modal system combining physiological traits (faces and fingerprints) and behavioral traits (signatures and voices), as well as a uni-modal system using all features. The research collected 2400 images from 200 individuals, pre-processed images, and salient features selected for easy classification. NSA was used for image classification in both bi-modal and uni-modal systems. The results demonstrated NSA's effectiveness, particularly in the bi-modal system. The biometric system that fused behavioral traits exhibited high accuracy, with true positive and true negative rates of 141% and 144%, respectively, and an overall accuracy of 95%. The system is based solely on physiological traits and achieved slightly lower accuracy rates at 89%. Furthermore, among the uni-modal systems, the voice-based system stood out with a true positive rate of 131% and an accuracy of 88.33%. These findings emphasize the advantages of combining different biometric traits, showcasing the potential for increased accuracy in identification systems. The study highlights NSA's role in enhancing classification accuracy, suggesting the developed biometric systems could significantly improve the performance and reliability of various integrated identification systems.
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    Development of a GSM based Vehicle Demobilizer and Tracking System
    (ABUAD Journal of Engineering Research and Development (AJERD), 2023) Jimada-Ojuolape, Bilkisu; Spencer, Oluwafunto; Balogun, Monsurat
    Vehicle hijacking remains a pervasive global issue, posing heightened risks, especially when owners face armed hijackers. Concurrently, the disposal of old mobile phones contributes significantly to the escalating electronic waste (e-waste) challenge, emphasizing the imperative of responsible recycling practices. Addressing these concerns, this paper introduces a GSM-based vehicle demobilizer and tracking system, utilizing a cost-effective mobile phone connected to the device through a SIM card and operating with an NE 555 timer IC in bistable mode. In the event of a hijacking, a call to the mobile phone triggers the device, halting the vehicle. In the prototype design presented in this paper, the result of the output is represented by an LED to show that the circuitry actually works. When the device was tested, the LED illuminated when a call was placed to the mobile phone connected to the device which signifies that the circuit works and can achieve its purpose. The resulting design also shows that the vehicle owner can prevent his car from being stolen away even after it has been hijacked without self-endangerment and within a short time frame.