Electrical and Computer Engineering
Permanent URI for this collectionhttps://repository.mu.edu.et/handle/123456789/426
Browse
11 results
Search Results
Item Design and Optimization of Bamboo/Glass Fiber Reinforced Epoxy Composites for Sustainable Wall Panel Application(Mekelle University, 2024-11-12) Tedros TilahunEstimating the angle of arrival (AoA) of a coming signal can accomplished using various methods. In most cases algorithms are used for such purposes. However, algorithms are naturally complicated and expensive, and also cause a degradation in system performance. Therefore, other methods such as, 1800-hybrid rat race (HRR) coupler can be applied for effectively estimating the AOA of a coming signal. In this thesis work, an 1800 HRR coupler integrated with a 2x1 closely-spaced patch antenna array and a negative permeability metamaterial was studied for estimating AoA of a coming signal. The 1800 HRR was made up of a ring metallic sheet integrated with four additional branches placed at the edges of it. It operates at 10 GHz so as to make compatible with the 2x1 patch antenna array’s operating frequency. The simulation results show, the 1800 HRR coupler is characterized by 00- phase at the sum (Σ)-port while 1800 phase shift at the difference (Δ) port at the given operating frequency. In order to integrate with the 1800 HRR, a 2x1 array patch antenna with an inter - element distance of 0.6λ (where λ is the operating wave length) was designed. The antenna array workes at 10GHz with a maximum simulated gain of 8.824 dB while keeping the mutual coupling to a minimum of -23 dB. To further achieving miniaturization, the inter-element distance reduced to 0.4λ. The simulation result shows a resonance at 10 GHz frequency and maximum gain of 7.8 dB while the mutual coupling increased to -9 dB. The 2x1 patch antenna array with inter - element distance of 0.6λ -1800 HRR coupler system was able to estimate the AoA of the received signal from 00 to 190 with error of less than 50. While with a reduced inter – element distance to 0.4λ, the system was able to estimate signals from 00 to 500 with error of less than 50. Upon integrating split ring resonator (SRR) met materials, mutual coupling reduced to -15.6 dB without affecting the AOA of the system. This study was able to estimate AOA in a wide range of an incoming signal while keeping the inter – element distance smaller. The proposed design can be applied in radar system applications where accurate estimation of AOA of an incoming signal is needed such as in target tracking, surveillance, and navigation missions.Item Design of an Adaptive Neuro-Fuzzy Inference System Controller for Temperature and Concentration Control in a MIMO Continuous Stirred Tank Reactor (CSTR)(Mekelle University, 2025-04-07) Ybrah ZemchealThe Continuous Stirred Tank Reactor (CSTR) is a critical unit in chemical processing industries, where precise control of process variables is essential for optimal product quality and efficiency. Among the key variables, temperature and concentration are particularly important to regulate. However, chemical processes often exhibit nonlinear and multivariable behavior, making conventional controllers less effective in real-time operation (PID control in CSTR exhibits sluggish or oscillatory responses for feed concentration, slow response to variable water flow, Poor robustness for uncertain parameters (e.g., reaction rates, heat transfer coefficients), perform poorly due to cross-coupling effects, less nonlinearity handling due to reaction kinetics. Challenges such as dynamic process variations, reactant nonlinearities, fluctuating environmental conditions, and diverse disturbances further complicate control. Additionally, most industrial chemical processes are multi-input multi-output (MIMO) systems, necessitating advanced control strategies and decoupling techniques. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed as an advanced control approach to enhance system performance and accuracy compared to conventional controllers. ANFIS integrates the structured knowledge representation of fuzzy logic with the adaptive learning capabilities of neural networks, offering improved control for complex systems. The performance of ANFIS is evaluated against a traditional PID controller through offline simulations using MATLAB/Simulink. The results demonstrate that ANFIS outperforms PID control in key performance metrics, including overshoot, rise time, settling time, and system stability. Furthermore, ANFIS exhibits superior disturbance rejection capabilities, making it a more robust solution for CSTR control in industrial applications.Item Load Frequency Control of Small Hydro Power Plant Based on Artificial Neural Network with Tuned PID Controller(Mekelle University, 2025-04-10) Rigbey HailetsionElectricity propels the advancement of society and economy, fueling sectors such as healthcare, education, and industries. Real-time adjustments in power generation are made by load frequency control to stabilize frequency and voltage, a critical factor for uninterrupted power supply. An innovative approach suggests the integration of artificial neural networks and PID controllers for enhancing the performance of small hydropower plants. The core objective of the research is to create an ANN combined with tuned PID for regulating load frequency in small hydro power plants. The thesis elaborates on the limitations of conventional PID controllers and the flexibility of the ANN-based strategy, outlining the process of plant modeling and controller configuration. Both Proportional-Integral-Derivative (PID) controllers and ANN with Tuned PID controllers are commonly employed techniques. While PID controllers offer stability, the ANN with Tuned PID controllers exhibit superior adaptability and quicker responses to dynamic variations, thereby enhancing the efficiency of the SHP. Using the ANN-tuned PID controller results in significant improvements in several areas. The settling time is notably enhanced, decreasing by 74.36% compared to the untuned PID controller and 50.88% compared to the tuned PID controller. The overshoot is greatly reduced, showing a decrease of 96.29% compared to the untuned controller and 90.26% compared to the tuned controller, indicating much better stability. Additionally, the peak time increases slightly by 2.78% compared to the untuned controller and 2.14% compared to the tuned controller, demonstrating minimal delay in reaching the maximum value. These changes highlight faster, more accurate, and stable system responses with advanced tuning techniques.Item Fuzzy Sliding Mode Control for Dynamic Walking Assistance in Lower Limb Exoskeletons(Mekelle University, 2025-04-23) Tsega Hailemariam GebrecherkosIn recent years, the development of wearable exoskeleton robots has gained significant attention due to their potential to assist individuals with mobility impairments. These robotic systems are designed to enhance, assist, or restore motor functions, particularly for those with disabilities or injuries affecting the lower limbs. However, controlling lower limb exoskeletons presents substantial challenges due to the nonlinear dynamics of human gait and the need for adaptation to varying user requirements and environmental conditions. This thesis proposes a Fuzzy Sliding Mode Control (FSMC) strategy as an advanced hybrid control solution for a 2-DOF lower limb exoskeleton robot designed to assist dynamic walking. The key novelty of the proposed method lies in the integration of fuzzy logic into the sliding mode control framework, where the fuzzy inference system dynamically adjusts the control gains based on real-time tracking errors and their rates of change. This adaptive mechanism enables FSMC to strike a balance between the high robustness of sliding mode control and the smooth response characteristics of fuzzy logic systems.The proposed FSMC was benchmarked against classical Sliding Mode Control (SMC) and Quasi-SMC across multiple walking scenarios, including variations in walking speed and random stop-start motions. Unlike conventional SMC methods—which often struggle with nonlinearities, parameter uncertainties, and gait variability—the FSMC approach offers superior adaptability. Simulation results demonstrate that FSMC outperforms classical SMC and Quasi-SMC in both tracking accuracy and robustness. Under increased walking speeds, FSMC exhibited the lowest increase in error (5.57% in Case 1, 9.68% in Case 2) compared to 186.16% and 116% for SMC, and 169% and 162% for Quasi-SMC, respectively. In random motion scenarios, FSMC achieved the lowest sum of squared tracking errors, confirming its effectiveness under dynamic conditions. Furthermore, FSMC significantly reduced control signal chattering, which not only improves tracking but also reduces mechanical wear, enhancing the exoskeleton’s longevity. In conclusion, this study demonstrates that FSMC is a superior control strategy for lower limb exoskeletons operating under uncertain and dynamic walking conditions. Its ability to combine adaptability, robustness, and smoothness makes it a strong candidate for future real-time implementations and clinical applications in mobility assistance and gait rehabilitationItem Medium Voltage Distributed Network Performance Optimization by Reliability Centered Maintenance Prioritization of Distributed Feeders and DG Integration(Mekelle University, 2024-10-25) Rahwa BerhaneIn today's world, virtually every human activity relies on electricity, either directly or indirectly. Reliable electric power is essential for our daily activities, and this power is delivered through a distribution network. However, numerous issues prevent the continuous supply of electricity to end-users. The main problem on the distribution network are lack of planned preventive maintenance, improper feeder size selection, over load and lack of DG. To address these issues, this work employs a reliability-centered prioritization of feeders for maintenance and integrate a solar PV system to the distribution network using the Electrical Transient Analyzer Program (ETAP) to improve the reliability and availability of electric power. A comprehensive reliability analysis for identifying a feeder R5 as a case study sample, making it the case study for Reliability improvement. By integrating, a DG in the selected feeder results a significant improvement in reliability indices. The System Average Interruption Duration Index (SAIDI) was reduced from 735.43 hours/customer/year to 369.413 hours/customer/year, and the System Average Interruption Frequency Index (SAIFI) decreased from 293.259 per year to 200.30 per year. These reductions represent decreases of 49.77% and 31.7%, respectively. Furthermore, the Expected Energy Not Supplied (EENS) dropped from 46,107.5 MWh to 23106.71 MWh, and the Expected Outage Cost (ECOST) decreased from $2,019,508.5 to $1,012,073.898, indicating an improvement in cost-worth reliability indices and the network's revenue. The reduced reliability indices demonstrate the enhanced performance of the distribution network from a reliability perspective. Implementing a reliability-centered maintenance for the feeders in the conventional distribution network would also improve the reliability of Mekelle city distribution network.Item Efficiency Improvement in MV Distribution System through Feeder Reconfiguration (Case Study: Adwa Distribution System)(Mekelle University, 2025-04-07) Yosef AmahaThe electric power industry is increasingly challenged by rising load demand, aging infrastructure, and the complex spatial distribution of electrical loads, all of which undermine distribution system efficiency. These are especially pronounced in radial networks, where high technical losses and voltage deviations compromise power quality and reliability. Adwa feeder, a 15 kV radial distribution system in Ethiopia, embodies these concerns, with technical losses reaching 940.84 kW, voltage levels dropping to 0.83 per unit, and line loading peaking at 148.14 percent. This study explores feeder reconfiguration using Particle Swarm Optimization (PSO) to improve energy efficiency, voltage stability, and line overloading under varied load conditions. Load flow analysis was conducted using the Backward/Forward Sweep method in MATLAB under peak, medium, and minimum loading conditions, with total demands of 7,839 kW, 4,710 kW, and 2,160 kW, respectively. PSO identified an optimal switching scheme by opening sectionalizing switches 52 and 71, keeping tie switches 79 and 82 open, and closing 80 and 81. The optimized configuration reduced peak losses by 35.7%, lowering them to 604.87 kW and improving minimum bus voltage to 0.9161 per unit. For medium and minimum loads, losses dropped from 570 kW to 370 kW and from 140 kW to 90 kW, respectively, improvements of 35% and 36% with corresponding voltage profile enhancements. To validate robustness, Monte Carlo simulations (1,000 iterations, ±10% load variation, ±0.05 PF deviation) confirmed the optimized topology sustained losses near 605 kW and voltages above 0.9 per unit under uncertainty. Furthermore, upgrading the most overloaded segment (Line 1–2) to an AAC 150 conductor further improves losses to 524.32 kW. While this upgrade alone provided an 8.6% gain beyond reconfiguration, the combined effect achieved a total loss reduction of 44.3% from the original case. These results demonstrate that intelligent feeder reconfiguration, enhanced by PSO and supported by probabilistic analysis, provides a scalable, cost-effective solution for improving performance in radial distribution networks like Adwa's.Item OPTIMAL DISTRIBUTED GENERATION INTEGRATION PLANNING (CASE STUDY: SHIRE CITY POWER DISTRIBUTION SYSTEM)(Mekelle University, 2025-05-21) TSIGE ABRHAThis thesis examines the challenges of power distribution in Shire City, Tigray, Ethiopia, where rapid urban growth driven by industrial, commercial, and residential expansion has increased electricity demand. This rising demand is causing voltage degradation and higher power losses, raising significant stress on the existing infrastructure. The study forecasts future load requirements and explores the addition of renewable energy sources like solar and wind to optimize the distribution network, ensuring a sustainable and reliable power supply. The study uses advanced econometric methods to forecast future load requirements. The results show that peak load demand will rise from 17.29 MW in 2024 to 31.39 MW by 2043, driven by population and economic growth. This increase necessitates significant improvements to both generation and distribution infrastructure. The study further explores the integration of DG to mitigate power losses and improve voltage stability. Optimal distributed generation (DG) integration, as shown by the analysis, yields a significant 91% decrease in active and a 90.84% decrease in reactive power losses while simultaneously optimizing voltage profiles. Cost estimation for the 8.2 MW DG system, comprising photovoltaic and wind technologies, was found to be $3,233,880, with a return on investment expected in 3.77 years. This research demonstrates that integrating DG into the Shire City distribution network offers a viable solution to meet rising electricity demand, reduce power losses, and enhance system stabilityItem Loss Reduction and Voltage Stability Enhancement of Distribution Network through Optimal Allocation of Distribution STATCOM Case Study: (Axum Distribution Network)(Mekelle University, 2025-06-05) Luel AweteheyThis thesis presents the way of improving the performance of the distribution network by improving the voltage profile and reduces the power loss by integrating D-STATCOM to Axum K4 distribution feeder. D-STATCOM is commonly used in the distribution system for reactive power compensation so that it improves voltage profile, reduces power losses and improves the system voltage stability. The study of this work was conducted on Axum distribution K4 feeder it consists of a total number of Fifty-nine–bus feeders, of which bus-1 is taken as a reference node or slack bus, the other 47 nodes are connected to loads through step-down distribution transformer, and the remaining 12 nodes are common coupling nodes. The voltage profiles of most buses are not in an acceptable range, and the voltage stability index of the buses shows that the network is prone to voltage stability problems. The active and reactive power loss of feeder is 131.72KW and 111.35KVAr respectively. The optimal D-STATCOM allocation in electric distribution system enhances maximizing energy utilization, feeder loss reduction, and voltage stability and profile improvement. To allocate power control variable in the best possible location and with proper size two solution methods are applied. As the first method, the weakest bus of the system was selected for the optimal placement of D-STATCOM using bus based voltage stability index analysis. In the second method, particle swarm optimization (PSO) was applied for selecting optimal placement and size of DSTATCOM. The PSO optimization algorithm formulates a problem by considering system loss reduction, enhancement of voltage profile and voltage stability index of the operated network. A direct load flow analysis also carried out for the purpose of total system loss and bus voltage magnitude determination before and after compensation with D-STATCOM. The optimal allocation problem was tested in different system case based on the number and size of D-STATCOM. By comparing the net cost of D-STATCOM in relation to total system loss reduction single D-STATCOM installation has a better system. After the installation of single D-STATCOM with an optimal allocation through the feeder. The voltage profile of the system improved between 0.95-1.05p.u. The voltage stability index of the operated network increases as compared with base case stability. The active and reactive power loss through the line reduced to 25.03% and 25.25% respectivelyItem Design and Analysis of Solar water pumping system for Agricultural Farming of Sweet Potato(Mekelle University, 2025-04-07) Tsegabrhan GebretsadkanQuality of life, sustainable development, and economic progress are all largely influenced by energy. The shift to renewable energy sources has become essential in light of the growing global energy crisis, which is characterized by rising demands and the depletion of fossil fuel resources. Solar energy is one of the most promising of these, especially when it comes to solving important issues with agricultural methods.The design and study of a solar photovoltaic (PV) irrigation pumping system for sweet potato growing in the Abraha-Atsbeha hamlet are the focus of this thesis. Because they rely on expensive and environmentally damaging diesel pumping equipment, local farmers today confront many challenges. To address these challenges, the research begins with a comprehensive review of existing literature on solar irrigation technology, identifying key gaps and challenges in the field. Building on this foundation, a conceptual design for the PV irrigation system is developed, incorporating essential components such as the PV array, pump, storage tank, and control systems tailored to the specific needs of sweet potato cultivation. A detailed computer model of the proposed system is created and simulated using advanced software tools, including CROWAT, MATLAB, PSIM, HOMER, PVSyst, EasyEDA, and Drawing.io. Benchmarking exercises are conducted to evaluate the system's efficiency across varying climatic conditions by adjusting parameters like temperature and solar irradiance. The findings highlight the effectiveness of the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm in optimizing power output and ensuring efficient operation. According to the results, the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm is a good way to maximize power output and operational efficiency. In summary, a comparative study shows that the solar-powered irrigation system has several benefits over conventional diesel systems, such as decreased carbon emissions and operating expenses. The potential of solar technology to revolutionize farming methods, enhance food security, and support a sustainable energy emphasized by is this studyItem Reliability Enhancement of Distribution System by Using Feeder Reconfiguration (Case Study: Mekelle City Distribution System)(Mekelle University, 2025-04-04) Meron DebruEquipment failures and customer interruptions are the primary factors that affect distribution reliability. In many developing nations, including Ethiopia, reliability modeling and evaluation of distribution networks receive less attention "compared to" generating and transmitting systems. Since electric power is now used directly or indirectly for many of our activities, the utility should provide dependable electricity every day of the year to meet consumer demands and enable employees to do their jobs as efficiently as possible. However, several fault types affect the power supply’s reliability and quality. Power quality issues and interruptions are common in Mekelle distribution substation. Short-circuit faults, whether permanent or transient, system overloading and other factors are the primary causes of these interruptions. As a result, consumers are not receiving reliable power. The main goal of this work is the enhancement of the 15 kV side Mekelle distribution networks at a reasonable cost. Because several factors are causing power outages that mostly affect the 15 kV side. The reliability assessment has been done on fifteen feeders of the 15 kV Mekelle city distribution network. A reliability assessment of feeders on the 15 kV side has been carried out in order to assess the effectiveness of the current system and predict upcoming reliability evaluations. All the interruption data of five years (2011 E.C. up to 2015 E.C.) has been used which have been collected from Mekelle substation as well as north region Ethiopian electric power. Different alternatives have been assessed using ETAP 19.0.1 software method and the alternative with low SAIDI, SAIFI and EENS with a reasonable cost has been preferred. The reliability of Mekelle city distribution network has been enhanced significantly by implementing auto-reclosers that are justified economically. Even if the ambiguity of the input data is taken into account, SAIFI has been reduced by 59% as compared with the average reliability indices values of the existing system. In the similar way SAIDI and EENS have been decreased by 61% and 78.1% respectively.