Applied Mechanics and Materials Vol. 932

Abstract: This research presents a technical and economic assessment of a hybrid energy system for electricity generation, accessibility, sustainability and consumption in rural and semi urban locations in Nigeria. The aim is to determine the sizes, technical and economic considerations of the hybrid microgrid renewable energy infrastructure that could be suitable for 40 rural and semi-urban locations selected to cut across the Federal Capital Territory (FCT) and all the 36 states in the country. The cost of the components of the hybrid system and the energy generated per renewable energy (RE) source from the microgrid are determined for all the locations. The projected yearly electricity generated for each location for the hybrid system were determined using the hybrid optimization of multiple electric renewables (HOMER) energy modelling software for a period of 10 years from 2024 to 2033. TheWorld Bank population growth rate of 2.5% was used to estimate the population each year and the associated load demand. Each location was assumed to have a minimum electric load of 0.76 kWh per day per person. To simulate longterm continuous implementation of the hybrid system, average solar irradiation, wind speed and available biomass resources for the selected locations were used. The mean annual wind speed ranged from 3.45 to 7.15 m/s. The solar radiation ranged from 4.43 to 6.24 kWh/m2/day. The per capita net present cost (NPC) ranged from 776.37 to 4130.21 USD per kWh, while the cost of energy (COE) ranged from 0.00196 to 0.0231 USD /kWh, respectively for the period. The results show that Nigeria as a country has ample renewable energy resource availability to meet minimum electric power demand for the locations consdered.With a strong political determination, optimal utilization of these renewable resources (solar, wind and biomass) can be actualized. Researchers, Industrialists, Policy Makers and the Nigerian government should therefore take advantage of these abundant renewable energy resources in the country to develop a sustainable energy generation and consumption plan through its maximum utilization.

Abstract: This research developed a performance improvement of power transmission system to enhance performance during line disturbance using model Predictive control (MPC) control scheme. This research work was implemented using MATLAB 2023a. However, the parameters of these controllers are usually adjusted based on a linearized model of the power system, which typically depends on the system's operating point or state. To assess the performance of the developed scheme, multiple simulation studies were carried out under conditions where the voltage magnitude of the infinite bus and the transmission line reactance changed due to faults at the infinite bus and sending terminals. The results from the waveform analyses indicate that the dynamic characteristics of the system under investigation have significantly improved. settling time, at post fault of the transmission and from fault recovery settled time to its stable state value of 1.8sec compared to 2.8sec with minimal control effort that fluctuated between faults and system stability before settling time at the shortest time value of 2. 6305s in 2.42s compared to 4.28, in 1.92s compared, and 3.32s.

Abstract: Consequent upon the inestimably magnificent rise in the necessity to considerably minimize the worrisome menace of global dependency on fossil fuels (such as coal, oil and gas), combat the pollution caused by green house gas emission emanating from same and lead a crusade against energy insecurity; the renewable energy sources (RES) became a panacea to the incessant imbalance between the ever- increasing demand and meagre supply of energy throughout the entire universe. Nevertheless, the output of RES is characterized with some unpleasant traits which include intermittency coupled with variability and unpredictability since it is largely constrained by annual weather pattern thereby inflicting a very severe injury on transient and steady state stability, reliability and profitability index. Thus, the certainty that this attributes do not only possess a gigantic capability to render synchronization futile but also initiate regular system collapse in the grid network cannot be over-emphasized, especially if the necessary precautionary measures are not taken into consideration. Therefore, this research work provides a compact review on the impacts of integration of large scale renewable energy sources into grid-connected power system. The methodology would involve an elucidative investigation of the associated benefits and obstacles after which possible mitigations to the challenges are accorded an extensive analysis while useful inferences are drawn meticulously leading to qualitative conclusions and useful recommendations from the results and findings so obtained.

Abstract: Predicting accurate electricity consumption on electrical distribution network is essential for efficient energy management, particularly in institutional settings where demand fluctuates due to population growth and weather variations. Traditional prediction models often lack real-time accessibility. This study presents a browser-based simulation model for monthly electricity consumption using historical data and dynamic weather inputs, implemented with HTML, CSS, and JavaScript. The model generates forecasts by applying statistically plausible variations (±5%) to historical consumption patterns, integrated with simulated weather data for real-time scenario testing. Compared to complex machine learning approaches, this lightweight solution offers enhanced scalability, remote accessibility, and instant updates without server dependencies which makes it more applicable for smart grid systems and utility management. Results demonstrate its utility as a practical tool for preliminary energy trend analysis, supporting integration with cloud-based data sources. This research will contribute to accessible energy forecasting tools and provides a practical tool for optimizing electricity consumption on electrical distribution network in institutional environments and for institutional planning.

Abstract: One of the key factors that hinder satisfactory performance of metal oxide surge arresters (MOSAs) against the damaging effects of overvoltage transients is accurate representation of their dynamic behaviour. Therefore, this study analysed dynamic characteristics of MOSA using IEEE and Fernández-Díaz equivalent circuits with ABB MWK surge arrester used as a test case. The impulse current input to the equivalent circuits was modelled using Gaussian equation. Simulations were done and residual voltage and quenching time of the models for impulse currents inputs of 1, 5, 10 and 20 kA respectively were determined. The obtained residual voltages were compared with the manufacturer’s standard in the test arrester datasheet. Residual voltages of 115, 128, 137 and 157 kV respectively were obtained for 1, 5, 10 and 20 kA impulse currents impressed on both IEEE and Fernández-Díaz models. While 115 and 128 kV residual voltages respectively tallied with the manufacturer’s standard for 1 and 5 kA impulse currents, 137 and 157 kV residual voltages were found to exceed the standard for 10 and 20 kA impulse currents respectively. The quenching time for the voltage surge resulting from 1, 5, 10 and 20 kA currents injection on both adopted models were 0.2, 0.22, 0.225 and 0.23 ms respectively with no damping observed in the voltage response of Fernández-Díaz model unlike in the IEEE model. The study indicated that Fernández-Díaz model produced a better MOSA dynamic response for the study.

Abstract: An efficient grounding system design for safe fault current discharge requires the knowledge of soil resistivity. This study analysed the dependency of soil resistivity (ρ_s) on some soil factors such as soil texture (ST), moisture content (MC), temperature (T) and depth (D) for optimal grounding system operation. Two seasonal measurements of ρ_s were conducted during rainy season (July 2023) and dry season (January 2024) at six different sites in Federal University of Agriculture, Abeokuta (FUNAAB), Ogun State, Nigeria as a case study. Using Herojat Rhomega-smart resistivity meter, the ρ_s at the sites was measured via Wenner method. The ST and MC were determined via laboratory analysis of five 5 kg samples of soil from each site at the D values generated by the meter while T was measured using a thermometer. The ρ_s dependency on MC, T and D at each site was modelled using multiple linear regression (MLR). Coefficient of determination (R²) was used to determine MC, T and D contributions to ρ_s. The obtained results revealed that the measured ρ_s at the six sites over the study period was a function of ST, MC, T and D. The developed MLR models for the sites for both rainy and dry seasons showed that MC, T and D collectively influenced the ρ_s value better than the individual factors owing to higher value of multiple R² observed. The outcomes of this study could be adopted as good reference points for further soil resistivity analysis and grounding system installation for FUNAAB.

Abstract: This study presents the design and implementation of an automated flap folding system for a carton sealer machine in a beverage manufacturing industry in Indonesia. The system addresses the inefficiencies of the manual folding process. The design focuses on affordability by employing a fully electric system, eliminating the need for additional compressors and air tubes. Fabrication utilizes materials available in the company's workshop, with a total cost of IDR 7,243,452. Testing reveals that the system's maximum capacity is 36 cartons per minute, surpassing the current capacity of the carton sealer machine. This results in a production increase from 19 cartons per minute to 30 cartons per minute (58%). Additionally, this research offers substantial cost savings compared to purchasing new carton sealers with automatic flap folders, with potential savings of IDR 45,000,000 per machine if the system is mass-produced.

Abstract: Company XYZ, a toy manufacturing company, is pursuing a 40% reduction in manual material handling labor by 2030 through the implementation of autonomous mobile robots (AMRs). This study applies an integrated Analytical Hierarchy Process (AHP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) approach to select the optimal AMR, supported by discrete-event simulation modeling in FlexSim to validate designs prior to investment. A cost-benefit analysis, including Benefit-Cost Ratio (BCR), Internal Rate of Return (IRR), and Payback Period, demonstrates the economic feasibility of the proposed solution. Simulation results suggest a configuration of three AMRs to meet cycle-time targets with a projected labor cost reduction of 47%. This work contributes a validated methodology for robot selection, system design, and investment decision-making in manufacturing environments.

Abstract: Dynamic robots capable of navigating confined and unpredictable environments are increasingly needed in industrial applications. This study aimed to design and evaluate a two-legged wheeled self-balancing robot platform to achieve stable and efficient motion in narrow and dynamic settings. The robot was built using an Arduino Mega 2560 microcontroller, MPU6050 IMU sensor, TD8129MG servo motors, and LN298N motor drivers, with balance maintained by a proportional-integral-derivative (PID) controller. Static stability tests confirmed reliable balance at a -2.00° pitch angle with optimized PID gains of K_p = 120, K_i = 0.1, and K_d = 150. Dynamic experiments under duty cycles of 59%, 78%, and 98% showed that the 78% configuration provided the optimal compromise, enabling smooth motion at 0.23 m/s with minimal oscillations, while lower duty cycles caused instability and higher cycles introduced excessive vibrations. These results demonstrate that the developed robot effectively balances speed and stability, offering a compact and maneuverable solution for industrial tasks in constrained spaces. The study concludes that this platform provides a strong foundation for practical applications, with future work directed toward advanced control strategies and autonomous navigation to enhance adaptability and energy efficiency in real-world environments.