Engineering Management Papers & Publications

This study was conducted to proposea hierarchical temporal memory (HTM) approach for fault detection in the Onitsha-Alaoji transmission line in Nigeria. Using a mixed research method, the study employed the Hawkins HTM model with two objectives and their corresponding research questions. The study gathered primary and secondary data to detect and evaluate faults in the Onitsha-Alaoji transmission line in Nigeria using HTM and compares its efficacy to current fault detection methods. With the use of simulation and descriptive methods of data analysis, results showed that partial discharge (PD) is the fault type that is being detected and it is commonly found as a fault leading to transmission line errors. More so, fault detection simulations were conducted at 40 km using typical power spectral density analysis. The first fundamental shifted from about 10 kHz to roughly 13 kHz during a fault. The HTM model outperformed sequence learning methods, resulting in a 90% mean test classification accuracy (CA) over extreme learning machine(ELM) and online sequential learning–extreme learning machine (OS-ELM), with OS-ELM performing poorly.The study concluded and recommended that the proposed HTM model be used to identify various PD fault types that plague the Onitsha-Alaoji transmission line in Nigeria. With the increased efficacy and reliability of the proposed model compared to existing methods, it is recommended for future implementation in this transmission line and potentially other fault-prone power transmission lines in Nigeria.

FXintegrity Publishing

This study was conducted to optimize the integration of solar-photovoltaic-distributed energy resources (SPVDERs) within the Nigerian power system networks using an AI-based Particle Swarm Optimization (PSO) Algorithm. By employing a mixed research method, primary and secondary data were gathered to calculate flow analysis, NR method's equations, PSO's position update model, particle swarm optimizer algorithm, and application modeling including Solar-PV DER modeling. The AI-based PSO algorithm design was developed for optimizing SPV-DER integration in Nigerian power system networks, and key parameters and variables that needed consideration were identified. The study also established how the performance of the AI-based PSO algorithm could be evaluated and compared with other optimization techniques for SPV-DER integration within Nigerian power system networks. The study's results showed that voltage limits were within acceptable ranges, and solar power contributions were estimated at 880.10MW with 46,718 panels needed. The study concluded and recommended that investing in AI-powered tools for efficient power distribution; monitoring and resource optimization for sustainable energy sources would optimize performance and unleash Nigeria's sustainable energy potential.

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This study was conducted to develop and evaluate the Optimal Poly-1-Order (OP-1) model for approximating solar photovoltaic (PV) power generation. Using a mixed research method, the study employed Ibrahim’s simulation and prediction of grid-connected PV system theory with two objectives and their corresponding research questions. The study gathered primary and secondary data to approximate the implementation of a solar-PV system with an OP-1 model for generating electricity: optimizing energy production, load demands, and financial viability in the medical hostel facility of the University of Port Harcourt, Rivers State, Nigeria. With the use of simulation and descriptive methods of data analysis, results showed that the lighting system had 400 lights, each with 12W power. It operated for a total of 18 hours. Daily power consumption was 36,400 Wh. More so, it showed that 60 fans with 100W power were used during the same hours, resulting in a daily power usage of 108,000 Wh. Based on a comprehensive economic evaluation, the OP-1 solar-PV system was found to be economically viable for powering the medical hostel. The system met electricity demand, resulting in a remarkable 407% ROI and substantial savings for the grid, despite a lower optimized size of 193kW compared to the base peak generation of 383.90k. The study concluded and recommended that the proposed OP-1 Solar-PV power plant can meet the facility's electricity needs with a peak generation of 383.90kW and detailed energy analysis. Deploying this efficient solar-PV setup guarantees reliable and green electricity for the Medical Hostel, slashing the campus's carbon footprint and grid reliance.

FXintegrity Publishing

As the demand for renewable energy continues to rise, it becomes crucial to discover effective ways to enhance grid-connected photovoltaic (PV) battery energy storage systems. The Institute of Petroleum Studies (IPS) complex at the University of Port Harcourt in Rivers State, Nigeria, embarked on a quest to determine the optimal approach for optimizing their PV battery energy storage system. This research aimed to fulfill this need by employing a diverse research methodology, incorporating the innovative MOALO theory. To begin with, the research gathered primary and secondary data to construct models for the power grid, solarPV, and battery. Furthermore, it meticulously analyzed the load profile of the IPS complex, at the University of Port Harcourt. Leveraging the power of the MOALO theory.The researchers accurately sized the system and evaluated the potential outcomes of simultaneously interconnecting all loads. To gauge the system's performance, there was a calculation of various parameters such as economics, random walk, boundary conditioning, entrapping ants, and ant trap development. Remarkably, the outcome showed that the fitness responses between the two trial runs, facilitated by the integration of MOALO, were strikingly similar, revealing a typical concaveconnected shape, which is characteristic of a multi-objective solver. The optimal multi-objective cost implication of the system was estimated to be around 4,300 USD, with a power mismatch performance of approximately -1.7819e+09. Based on these compelling findings, the study concluded that MOALO serves as an impressive optimization tool capable of minimizing power mismatches and optimizing costs. Moreover, it recommended the generation of excess power as a means to achieve sustainability.

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The inclusion of hydroelectric power is crucial to Nigeria's overall energy mix, playing a significant role in electricity generation. However, the Shiroro hydro plant, one of the main facilities located on the Kaduna River, is currently facing operational obstacles due to deteriorating infrastructure and inadequate maintenance practices. To overcome these challenges and improve efficiency within Nigeria's hydroelectric power sector, a hybrid-optimization approach has been proposed. This study sought to enhance the efficiency of the Shiroro hydro plant by implementing this innovative method. To achieve our objectives and address pertinent research questions, a mixed research method combining primary and secondary data was employed. The analysis included hydropower modeling and hydro-turbine input-output modeling. Three optimizer models, namely the particle swarm optimizer (PSO), Ant colony optimizer (ACO), and Artificial bee colony optimizer (ABCO), were utilized to formulate objective functions and task representations. The study involved comparing the daily output and fitness response of the Shiroro hydro plant through swarm optimizer iterations. The findings revealed a clear correlation between the turbine's power output and the water flow rate and water column height, suggesting that altering these factors could significantly improve the plant's performance. The comparison of the PSO, ACO, and ABCO models demonstrated that PSO and ABCO generated optimal or near-optimal solutions, while ACO produced suboptimal results. Consequently, the study concluded that enhancing the Shiroro hydro plant's output was feasible by increasing the water flow rate and column height. Additionally, the utilization of PSO and ABCO models proved to be an effective means of accurately predicting the turbine's output. As a result, the study recommended the integration of hybrid optimization techniques to monitor and identify any deviations in the Shiroro hydro plant's daily power output. This approach would enable prompt maintenance to be carried out, preventing significant damage to the plant. Ultimately, this research contributes valuable insights into improving the efficiency and performance of Nigeria's Shiroro hydro plant.

FXintegrity Publishing

This journal article investigates the evolving landscape of healthcare monitoring systems empowered by Artificial Intelligence (AI). Through an in-depth analysis of recent developments, methodologies, and case studies, the article elucidates the pivotal role of AI in revolutionizing patient care, diagnostics, and overall clinical outcomes.

Dhruvitkumar Talati

Production process in the manufacturing industries has proven wasteful of the resources in the production process over time. integrating of lean principles in the manufacturing activities has brought notable success in a complex and slow production process in an industry. This study aims at integrating of lean principles to a product development process to eliminate break down cases as it makes the process easy as well as speeding up the product development in an automotive industry. Three major phases are applied in product development namely; the early concept phase, middle core design and the launch phase. An exceptional definition of products development of lean principles are applied to come up with an analysis framework. Through interviews, observations, documentation and experience barriers that causes large number of wastes can be established. Lean principles will then be applied to eliminate such causes in the product development and then derive conclusion that shows the industry the process of lean in product development in the entire process

Levi P. Cheworei

This study conducted a simulation-based time-domain short-circuits fault evaluation and protection system reliability analysis in 300 MVA substations with 132 kV transmission lines in Asaba (Ibusa/Asaba), Delta State, Nigeria. The analysis focused on two primary parameters: protection system dependability and selectivity, to determine the conditions necessary for ensuring rapid fault clearance and stable substation operation under line-to-ground, double-line, and three-phase faults. Fault currents, voltages, and relay trip signals were generated and analyzed using MATLAB time-domain simulations. Results indicated that system dependability exceeded 97% and security surpassed 95% when total fault-clearing times remained below 120 ms. Relay coordination intervals of 0.2–0.4s, backup misoperation below 3%, and circuit breaker MTBF above 20,000 h ensured selective fault isolation. Extended fault durations beyond 120ms or improperly coordinated relay settings increased the likelihood of misoperation and voltage instability. It was concluded that uninterrupted substation operation depends on integrating time-domain fault evaluation, coordinated relay settings, and reliable breaker performance into protection management protocols. Accordingly, it was recommended that substation operators maintain precise relay coordination, implement continuous time-domain monitoring, and uphold breaker maintenance schedules. These actions will further enhance the protection reliability, reduce fault propagation risks and support safer, more stable operation of the 132 kV transmission network.

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This study evaluated power system reliability and frequency tolerance requirements for the management of critical-care medical devices at the Niger Delta University Teaching Hospital (NDUTH). The analysis focused on two primary parameters: voltage stability and frequency deviation, to determine the conditions necessary for sustaining Intensive Care Unit (ICU) ventilator uptime and neonatal incubator performance. Voltage and frequency data were collected at regular intervals over a five-month period and analyzed using reliability modeling and MATLAB-simulated multidimensional surface plots. Results indicated that ICU ventilator uptime stabilized at 96.1% when system voltage remained within the 208 and 222V band under controlled load conditions. Neonatal incubator reliability, however, declined sharply when frequency deviation exceeded 0.11Hz, activating maintenance thresholds. Extended voltage dips below 185V and frequency excursions above 0.12Hz were associated with increased likelihood of device failure and elevated corrective maintenance demand. The findings underscored that uninterrupted operation of critical-care devices depends on integrating voltage and frequency reliability metrics into equipment management protocols as conclusion. Accordingly, it was recommended that NDUTH management implement continuous power-quality monitoring, enforce maintenance protocols guided by operational thresholds, and strengthen redundancy measures. These actions will enhance device reliability, reduce service interruptions and support safer, more consistent delivery of critical care in the hospital setting

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