Electrical Computer Engineering

Permanent URI for this collectionhttps://etd.hu.edu.et/handle/123456789/74

Browse

Now showing 1 - 20 of 69

A MICROGRID ENERGY MANAGEMENT SYSTEM IMPLEMENTSTION USING MIXED-INTEGER LINEAR PROGRAMMING
(Hawassa University, 2020-04-27) SINTAYEHU TERBUSH
The ever continued growth and development of distributed generation (DG) in the electrical grid system led to the increasing expansion of microgrids across the world. Microgrid is distributed power generation units, energy storage devices, and controllable loads with the capability to operate in both grid-connected and island modes. Microgrid's economic operation is achieved through an energy management system that optimally schedules distributed generations and storage devices and continuously balances supply and demand. In this paper, a formulation of optimal unit commitment and dispatch scheduling of DGs in a grid-connected microgrid is presented. Mixed-integer linear programming (MILP) is used to carry out the optimal resource scheduling model. The goal is to reduce the overall operating cost of the system by optimally utilizing an energy storage device and a diesel generator unit by using load and renewable energy generation prediction. Operational constraints such as generation limits of DGs, battery charging/discharging limits, and state of charge (SOC) limits to be satisfied during all intervals of operation. Simulation results indicate that the operational cost of the system is effectively reduced through optimal scheduling of an energy storage system and a diesel Genset unit using the proposed strategy
ARTIFICIAL NEURAL NETWORK BASED FAULT CURRENT MINIMIZATION IN DISTRIBUTION SYSTEM USING SUPERCONDUCTING FAULT CURRENT LIMITER. (CASE STUDY: HOSANNA SUBSTATION-DISTRIBUTION SYSTEM)
(Hawassa University, 2021-08-17) ZENABU DUGUNO WAKERO
High magnitude of short circuit fault current takes place in electric power distribution system. This unexpected high magnitude of short circuit fault current can cause the failure of Hossana substation switchgear equipment’s and even if due to this problem most of industries sharing power from Hossana substation and end users of Hossana substation cannot get power properly. So, fault current minimization in distribution system is a critical issue and to minimize the maximum short circuit fault current in distribution system, superconducting fault current limiter (SFCL) device is applicable in this thesis work. By installing superconducting fault current limiter (SFCL) device to the Hossana substation distribution feeder especially for Gimbichu feeder maximum short circuit fault current to be minimized for different types of short circuit faults like, Line to Ground (L-G) fault, Line to Line (L-L) fault, Double line to Ground (LL-G) fault and balanced three phase faults in distribution feeder. Under this thesis work the case study area focus on Hossana Substation - Distribution system feeders especially from the nine of feeders Gimbichu 15KV feeder. The reason why this feeder is selected is because of this feeder covers long distance approximately 150KM and high system interruption take place frequently. In this thesis work ANN controller is used to control the SFCL device and both ANN controller and SFCL device are modeled in MATLAB/Simulink. After developing SFCL in MATLAB and connect this device to the distribution feeder it is possible check the fault current magnitudes before and after installing SFCL device to the system. Before installing SFCL device to the system the magnitude of short circuit fault current is 20KA to 40KA for L-G fault, L-L fault, LL-G fault and balanced three phase faults in Gimbichu 15 KV feeder. But, after installing SFCL device to the case study area maximum short circuit fault current magnitude become minimized 140A up to 150A for all types of short circuit faults. Finally, the payback period is calculated after installing SFCL device to the 15KV Gimbichu feeder. Therefore, the calculated payback period is 1.14 years i.e., the year of back payment of this thesis work is 1 year,1 month and 21 days
ASSESSMENT AND ENHANCEMENT OF THE TRANSIENT STABILITY OF DFIG BASED WIND FARM USING ANFIS (A Case Study of ADAMA II Wind Farm)
(Hawassa University, 2021-12-18) TESFAYE BELAY
Wind power is the greatest existing and used form of renewable energy in the world. Mixing the different wind farms to the national grid introduces new challenges regarding power system stability, among power system stability concerns; transient stability is one that significantly affects the grid. The objective is to assess and enhance the transient stability of DFIG based on wind farms, to model PI control for speed and slip control generator, to improve transient stability using thyristor control series capacitor (TCSC), to conduct during pre-fault, during fault, and post fault conditions. The methods to gathering data are through review of different papers, by asking the site workers, preparing questions for the worker, and from nameplates of equipment. The result consists of four conditions, the first condition is pre-fault conditions, the systems have no disturbance, the second condition is during a fault condition, all systems are disturbed, the third condition is posted fault conditions in this systems have no disorder and the fourth is the improvement of the systems by using TCSC, TCSC is injecting reactive power to the fault area and remove the fault from the systems or back to normal operations. Generally, stability has contained three scenarios pre-fault, during the fault, and post-fault condition. In Matlab Simulink, the pre-fault and post-fault have no disturbance, but during fault conditions, the systems disturbed and the disturbed systems are solved by TCSC at the improved conditions of the systems.
ASSESSMENT OF RELIABILITY ASPECTS IN POWER DISTRIBUTION SYSTEM AND DEVELOPMENT OF REINFORCEMENT MECHANISMS (CASE STUDY: SHASHEMENE CITY DISTRIBUTION SYSTEM
(Hawassa University, 2019-10-17) KABTAMU KETSELA
A stable and reliable electric power supply system is an inevitable pre-requisite for the technological and economic growth of any nation. Due to this, Ethiopian electric utility (EEU) must strive and ensure that the customers’ reliability requirements, which are met at the lowest possible cost. EEU should have their own reliability improvement strategy depending upon their needs and requirements of their customers. Although there are notcomplete methods in managing all reliability issues, utilities can maximize network performance and better serve customers by carefully addressing trouble prone areas. In order to achieve this objective, reliability factors based reliability analysis is performed under Electrical Power System Analysis (ETAP) software environmentIn this thesis, it is observed that different reliability reinforcement mechanismshas been undertaken to evaluate predictive reliability analysis for the future system. Using line reconductoring for wendogent feeder the SAIFI, SAIDI and EIC reduced by 12%, 7.5% and 32% respectively. For shashemene city feeder using Autoreclosure SAIFI, SAIDI and EIC reduced by 45%, 35% and 35 % respectively. For Arsinegele feeder using separate CB the SAIFI, SAIDI and EIC reduced by 9.7%,6.4% and 8.8% respectively and water pump feeder using covered conductor SAIFI, SAIDI and EIC reduced by 14.9%,9% and 9.8% respectively. Reliability indices of shashemene substation show the substation is unreliable as compared to standard practices and Ethiopia’s reliability requirement
Comparative Analysis and Calibration of Empirical Path loss models at 1800 and 2100 MHz frequency Bands for Hawassa City
(Hawassa University, 2021-10-25)
Due to recent years’ fast development of mobile communication technologies, the demand for high capacity network and excellent quality of service with thorough coverage has become essential. And the basic criteria in planning this type of network is the concept of Path loss. Path loss models estimates the average path loss a signal encounter at a certain distance from a transmitter. But, each kind of path loss propagation model intended to forecast path loss in a specific environment which might be wrong in another environment. Incorrect propagation model might cause low data throughput, poor coverage, poor quality of service, high investment cost and call drops which is clearly being observed in Hawassa City. Therefore, one of the root cause of these problems is the usage of un-calibrated path loss model during the network planning stage. This thesis presents a comparative study of five empirical path loss models according to the measured data collected from selected sites in Hawassa city at 1800 and 2100 MHz frequency bands. The preferred five models for investigation are COST- 231, ECC-33, Hata, SUI, and Ericsson model. A drive test approach was used for data collection and Nemo Handy and Nemo Outdoor were used as measuring a tools for the test. And the measured data were analyzed and extracted to suitable excel form for further analysis using ACTIX analyzer. Error measuring tools such as RMSE, Standard Deviation (SD), Mean Absolute Percentage Error (MAPE), and Mean Absolute Error (MAE) were used to evaluate the closeness of actual measured path loss with the path loss calculated from the listed empirical models in all area types. Then the best suited models were statistically calibrated using the Least Square algorithm to enhance the estimation accuracy. The result shows that, at 1800 Mhz band ECC-33 was the best fit model for Hawassa Urban areas with RMSE of 4.18 and 2.46 before and after calibration respectively whereas Hata was the finest for Sub-urban with RMSE of 7.86 and 5.18 before and after calibration respectively. And at 2100 Mhz band ECC-33 was once again the best fit model for Urban areas with RMSE of 6.15 and 5.28 before and after calibration respectively while Hata model found to be the best model for sub-urban areas with RMSE of 6.11 and 2.86 before and after calibration respectively. Thus, the optimized models are recommended for better deployment and gives an accurate path loss prediction.
Comparative Analysis of Adaptive Filters for Removal of Pink Noise from a Corrupted Speech Signal
(Hawassa University, 2022-10-26) Surafel Demeke Yimer
Noise affects different communication systems during transmission, on channels or reception processes and hence signal quality improvement is required when it is degraded due to various background noises. In this thesis work, Least Mean Square (LMS), Recursive Least Square (RLS), Wiener and Kalman filters are compared for removal of pink noise from a corrupted speech signal to improve some speech qualities using filter length, Signal to Noise Ratio (SNR) and Mean Square Error (MSE), computational complexity, stability and convergence speed parameters. A pure speech signal and pink noise are generated separately, added together and produce a noisy speech signal having different signal to noise ratio levels and then feed to the adaptive filters as an input. The filters then estimate the distorted speech signal and produce a mean square error that has a significant difference for the same input noisy signal. Based on the simulation results obtained, it is concluded that Kalman filter has better MSE performance in terms of filter length, signal to noise ratio and mean square error metrices, since it produces the smallest mean square error followed by wiener, LMS and RLS filters. In terms of computational complexity, stability and convergence speed metrices, Kalman is computationally more complex and has faster convergence rate but LMS is more stable. Hence, we can conclude that, in removing pink noise from a corrupted speech signal Kalman filter has better MSE and faster convergence speed performances even if it is computationally more complex and less stable.
Comparative Performance Analysis of Channel Estimation Techniques for Massive MIMO System
(Hawassa University, 2021-12-17) Ashenafi Gebre
The need for an internet connection is growing universally, so people need much higher data rate connection to meet their need but every physical resource in communication like frequency band, transmit signal strength are finite. Within the given limited resource, higher data speed is accomplished by a new technology called massive Multiple Input Multiple Output (massive MIMO) system. Massive MIMO fulfills the high data rate requirement through antenna diversity gain. It is one of 5G wireless network technology with array antennas at both transmitter and receiver sides to providing high spectral and energy efficiencies. In massive MIMO, the signal obtained by the receiver is in different phase and amplitude from the transmission signal. Therefore, the system quality is highly depending on the accuracy of the channel estimation. Channel estimation plays a significant role in the performances of massive MIMO system because the dimension of the channels matrix is large, phase changes and noises are added when the signals pass through channel, these reduces the efficiencies of the whole system. To solve these problems, this Thesis focuses on the comparative analysis of pilot-based channel estimation schemes for massive MIMO system, which includes: Minimum Mean square Error (MMSE), Element Wise Minimum Mean Square Error (EW-MMSE), Maximum Likelihood (ML) and Least Square (LS) estimator with respect to Normalized Mean square Error (NMSE), Signal to Noise Ratio (SNR), Spectral Efficiency (SE), number of BS antennas, and number of computational complexities. Based on the simulation results, MMSE channel estimator has the best performance, followed by EW-MMSE, ML and LS channel estimators in terms of NMSE and SNR. And depending on the number of computational complexities of each coherent block as a function of BS antennas M with constant UE, the complexity of LS is less than that of MMSE, and it has almost the same complexity as ML and EW-MMSE. And also, according to SE with respect to BS antenna M, the MMSE provides the highest SE using the highest complexity, EW-MMSE and ML achieves a good balance between SE and complexity, and LS has the lowest complexity, but also provides the lowest SE. Finally, the result confirms that MMSE channel estimation technique has the best performance compared to EW-MMSE, ML and LS channel estimators with the cost of high complexity
Damping of Low Frequency Oscillation through Optimal Sizing of Unified Power Flow Controller and Power System Stabilizer Employing Antlion Optimization (Case study: Tana Beles 400kV Transmission Line)
(Hawassa University, 2022-10-23) Endeshaw Solomon
Low frequency oscillations are an inevitable phenomena of power system. Integration of unified power flow controller (UPFC) and power system stabilizer (PSS) can considerably improve the stability by damping out of low frequency oscillation (LFO). This thesis had presented the damping out of LFO through optimal sizing of PSS and UPFC using an Antlion optimization (ALO) approach to improve the transfer capability of North West region of Ethiopian electric network from Tana Beles to Bahirdar 400kV line. The obtained results (minimal damping ratio, eigenvalues and time domain simulation) of the proposed ALO approach were compared with the results of conventional existing system, teaching learning based optimization (TLBO), particle swarm optimization (PSO) and genetic algorithm (GA) to investigate the efficiency of the proposed approach for various operating conditions of the considered electric network. In this thesis UPFC had been compared and selected from various flexible alternating current transmission system (FACTS) devices and filters to show the robustness of the proposed system. Further, the proposed ALO approach had improved the tuning time to estimate the key parameters of PSS and power oscillation damper (POD). Consequently, the settling time, controller gain and time constants of ALO to attain steady state system is small as compared with teaching learning based optimization, genetic algorithm and particle swarm. The nonlinear equation which describes the system had linearized and then placed in state space form to study and analyze the performance of the system by damping out of LFO problems. System eigenvalues obtained from ALO tuned UPFC-PSS and conventional existing system are compared to study the efficiency of the proposed method for various operating conditions. Besides, time domain simulation comparison proves the superiority of the proposed method over the existing system. Finally using PSS only improves the maximum overshoot by 42.2% and settling time of 63.7% but the proposed optimally sized UPFC-PSS employed with ALO method had improved the maximum overshoot by 56.06% and settling time by 78.7% as compared with conventional existing system (base case). Thus, this thesis addressed the mechanism regarding low frequency oscillation in the electric network by incorporating optimal sizing of PSS equipped with UPFC to the system
DESIGN OF DISTRIBUTED ELECTRONIC LOAD CONTROLLER (DELC) FOR MICRO HYDRO POWER TO TRANSFER WASTED POWER TO THE COMMUNITY
(Hawassa University, 2020-10-22) GABREMICHAEL GELESSO
In a Conventional-ELC (C-ELC), usually a chopper with a dump load is used in parallel with the consumer loads to provide regulation of voltage and control of the frequency. However, in the C-ELC configuration excess generated power may be wasted in a dump load. The objective of this research is to design a simplified ELC for the community to transfer the wasted power for domestic consumption in addition to providing voltage regulation. Hence, a new ELC topology is proposed. This topology can be split into two parts. The first part is a regular ELC of low rated power, which should be installed at the generator site and it is responsible for precise voltage and frequency regulation and dealing with unexpected failure conditions. The second one is a simplified and inexpensive ELC, which is installed near the center of the community, is in addition to participation in voltage regulation by maintaining constancy of the load power. This concept is referred to here as the Distributed ELC (DELC). One significant advantage of the proposed DELC approach is that the waste power can be utilized for drinking water with a minimum capacity of 250Kg water per day and minimize health benefits related to drinking water. Simulation results demonstrate that even with unbalanced three-phase loads (assisted with bi-directional switches per-phase), the proposed topology has the capability to regulate voltage from no-load to full load
DESIGN OF FUZZY LOGIC CONTROLLER FOR ANTI-SWAY CONTROL OF TOWER CRANE UNDER DISTURBANCE
(Hawassa University, 2020-08-25) WELDAY MEBRAHTU GEBRESLASSIE
Tower cranes are widely used in constructions and loading unloading systems due to restricted human capability to transport numerous types of loads. Furthermore, in order to transport the load in minimum time from one position to another, load oscillation or sway angle will occur. This undesirable sway causes inaccurate positioning of the load, longer time of task completion, difficult automation by the human operator and damage to the system or the operating environment. This thesis presents the design of optimal motion planning, PID controller and fuzzy logic controller (FLC) for the sway angle control of tower crane system with friction. The optimal motion planning is an algorithm to determine optimal time for acceleration, constant velocity, and deceleration for trolley and jib motions when they are driven under trapezoidal velocity time curve. This algorithm considers the trolley and jib initial positions, final positions and system nature. The Newton’s second law is used to drive the mathematical model of tower crane or rotary crane system and the simulation results are done using MATLAB/Simulink environment. Simulation results are presented in trolley and jib optimal time trajectory tracking capability and load sway angle reduction. The FLC is compared with the classical PID controller in terms of the trolley and jib optimal time velocity, acceleration, magnitude of sway angle, rate of change of sway angle and displacement profile tracking performance under the effect of various trolley displacements. It has been seen that the fuzzy logic controller gives better performance in minimizing the sway angle and tracking the optimal time references of tower crane system than the classical PID controller.
DESIGN OF MODEL REFERENCE ADAPTIVE CONTROL BASED TEMPERATURE CONTROL FOR GLASS MELTING FURNACE
(Hawassa University, 2020-12-23) Mearg Ifewerki Fisaha
The glass manufacturing process is a complex and non-linear process. The quality of the final glass product depends on the temperature profile of the molten glass within a glass melting furnace. Inappropriate variations in the molten glass temperature affect the physical properties of the glass. In order to maintain the quality of the product, the temperature of the molten glass in the furnace must be monitored and controlled by a control system. The designing and testing of a controller require an appropriate process model that describes the process dynamics with enough accuracy. The modeling was distributed by applying energy balance using thermodynamic and energy conservation laws and a state-space model was derived from the energy balance equations. The temperature of glass melting is critical for the assembly of glass containers which are produced in continuous glass melt tank furnaces. Raw materials are continuously charged onto the glass melt to make batch blanket. The temperature of the glass melting determines the quantity of glass in the gob which is placed in the mold and thus affects the quality of the finished container. There are frequent temperatures fluctuations in the glass as it exits the main furnace .The aim of this thesis is to design MIT and lyapunov rule based model reference adaptive control for temperature of glass melting furnace. The controller parameters are adjusted automatically using adaptive adjustment mechanism .In this case the error between reference model output and actual output of the glass melting furnace is minimized. The temperature control of glass furnace based on MIT and lyapunov rule is simulated using MATLAB/ SMULINK and its performance is compared with conventional PID controller. The simulation has shown that performance of the model reference adaptive control (MRAC) is better than PID controller
DESIGN OF MODEL REFERENCE ADAPTIVE CONTROL FOR QUADROTOR UNMANNED AERIAL VEHICLE AT HOVERING CONDITION
(Hawassa University, 2020-10-22) KIDUS GEBREMICHAEL GEBREGZIABHER
In this thesis, we have considered the detail dynamic and kinematics mathematical modeling of 6DOF quadrotor UAV VTOL. Quadrotors are brush less direct current motors important device in terms of mechanical design and aerodynamic configuration. Quadrotors are under actuated vehicle which have four inputs and six outputs. The nonlinear model of the quadrotor unmanned aerial vehicle is linearized using the jacobian method of linearization at the selected operating points. For controlling of roll, pitch and yaw and altitude subsystems of quadrotor at hovering point, we have designed four model reference adaptive control (MRAC) based on the gradient method of adaptation mechanism. The reference model for each subsystem of the quadrotor unmanned aerial vehicle were chosen with a very small overshoot and zero steady state error. So that the output of the plant model tracks the reference model output. Finally, the sustainability and success of the designed controller (MRAC) are tested by MATLAB Simulink platform simulations was perform for different adaptation gain. The values of adaptation gain from 10 up to 200 gives a satisfactory result based on the desired performance
Design of Wavelength Division Multiplexing based Passive Optical Network Transmission System using Heterodyne Receiver for 5G Transport
(Hawassa University, 2022-12-11) Wondmagegn Wana
Fifth Generation network standard has put higher peak data rate (10x) and very low latency requirements (1/10) as compared to its predecessor 4G network. In any mobile network implementation, the transport network is critical component for delivering the intended services. The demand for high data rate in 5G requires massive capacity upgrade in the transport network. On the other hand, latency in 4G and older technologies is too much as compared to 5G requirements. Hence Building low-latency and high-capacity transport networks is vital for new high-speed cellular technologies. Optical fiber-based technologies are essential to meet the high bandwidth demands of 5G transport Network. The two contending optical technologies for 5G transport are point-to-point (P2P) fiber access and point-to-multipoint (P2MP). P2P fiber access has low fiber efficiency and requires infrastructure installation for new deployment. Point-to multipoint fiber has high fiber efficiency as compared to P2P. Among the P2MP fiber options, TDM-PON uses dynamic bandwidth allocation (DBA) to multiplex services which introduces 1ms delay. On the other hand, WDM-PON doesn't require DBA, thus is a good candidate for low latency services. Studies on WDM-PON are using homodyne receiver. The proposed network was simulated in Opti Wave Optisystem simulation software. In this thesis, a new 2.4 Tbps WDM-PON based network using heterodyne receivers was built as solution for 5G transport network requirements. The performance of the new system was compared with back to-back model using BER and OSNR. An OSNR of 15.4 is required to obtain a BER of 10−3 dB for Heterodyne System while an OSNR of 14.8 dB is required for Back-to-Back System which is 0.6 dB higher. The results obtained from the Heterodyne system simulation are very close to the result found in case of back-to-back system. Hence, the WDM Dual Polarization 8-PSK PON system with heterodyne receiver can be used in 5G transmission
DESIGNING OF MODEL REFERENCE ADAPTIVE CONTROL SYSTEM FOR CONTINUOUS STIRRED TANKER REACTOR
(Hawassa University, 2020-10-28) BERIHU BERHE WUYU
Continuous Stirred Tank Reactor (CSTR) is the significant process which plays an extensive role in chemical processing and chemical industries. In this process, like temperature of reaction and concentration of reaction are to be controlled. Since most of chemical process are multi input multi output (MIMO) system, it is important to design decoupling system and to find relative gain array (RGA) for the purpose of avoiding the interaction and to select best pairing respectively among the input output relationship. Because control of MIMO systems are usually much more difficult as compared to the SISO case especially for adaptive control system. This thesis deals with the operation, mathematical modeling and controller design for the jacketed continuous stirred tank reactor. PID and model reference adaptive control (MRAC) Controller are designed to control the reactant mixture temperature and concentration of continuous stirred tank reactor. The transient and steady state performances of the MRAC are compared with PID controller. The simulation has shown that the control performance of model reference adaptive control (MRAC) is better and effective than PID controller
“DETECTION, CLASSIFICATION AND MITIGATION OF POWER QUALITY DISTURBANCE: A CASE STUDY ON THE 15KV DISTRIBUTION FEEDER 6(R4-G5) AT HAWASSA SUBSTATION”
(Hawassa University, 2025-12-19) DAWIT DABA
Modern power systems face several difficulties due to power quality disturbances, such as voltage sags and swells, which call for effective detection, classification, and mitigation techniques. In order to fully address these problems, this study offers an integrated strategy that combines modern machine learning methods with optimization techniques. Artificial Neural Networks (ANN) trained and refined with MATLAB's Classification Learner Toolbox are used for detection and classification after features are extracted from voltage/current signals. This thesis was carried out on one of the Hawassa Feeder-6 (R4-G5) 15 kV distribution feeders utilizing distribution network analysis and MATLAB simulation. The purpose of power flow analysis is to ascertain the active and reactive power flows on the distribution lines, as well as the voltage magnitude and phase angle at each bus (node) in the system. Power quality disturbances are divided into four distinct wavelet filter levels using Debechesh-4 (Db-4). This enables the improvement of an approximate and detailed coefficient distribution in addition to the extraction of features such as the mean, maximum, and lowest values of the disturbances for power quality disruptions. The classification efficacy of neural networks (ANN) and support vector machines (SVMs) is 100%. Finally, a dynamic voltage restorer (DVR) is positioned optimally using the Grasshopper Optimization (GOA) techniques. Power loss decreased from 1913.3 kW (active) and 1202.4 kVAR (reactive) to 295.534 kW and 261.803 kVAR when GOA was used, and the voltage profile was increased from 70% to 98.5% and lowered the voltage swell from 110% to 98%, and also, by applying different kinds of faults, easily tested the voltage sag and swell by using DVR integrated with wavelet transforms algorithm. This reduces the possible influence on delicate systems and equipment while simultaneously enhancing the power supply's quality
DISTRIBUTION SYSTEM RELIABILITY ENHANCEMENT BY ASSET MANAGEMENT STRATEGIES FOR NETWORK RECONFIGURATION (ACASE STUDY OF NEKEMTE CITY DISTRIBUTION NETWORK
(Hawassa University, 2020-10-19) TADESSE GAROMA JAWI
Assets aging, corrosion, deterioration and slow replacement rate causes derating of the distribution system reliability and frequently damage and burn for the assets. They cause system power outage in radial distribution system in which a single power supplies the whole system. Thus, the objective of the study is to enhance the distribution system reliability by asset management strategies for network reconfiguration. Nekemte city is located in western Ethiopia, Oromia Region, East Wollaga Zone at latitude 9°5′N, and longitude of 36°33′E . Nekemte city distribution network is selected as a case study area in order to collect and analysis asset management strategy (in appendix (A) and reliability data (Appendix (B). The study is limited to circuit breakers (15Kv), transformers (15/0.4Kv) and OH lines (15Kv) assets. Age and health condition data’s of assets are collected to evaluate each asset’s health index. Health index is used to decide the proper maintenance and replacement strategy for present and future. As the result of asset management strategy, two (2)circuit breakers, seventy seven(77) transformers and forty point one (40.1) km of distribution overhead line requires replacement strategy and five (5) transformers and point seven(0.7) Km of distribution overhead line requires preventive maintenances. The placement and populations of automatic reclosers, sectionalizing switches and automation switches are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for network reconfiguration. Since, GA is better for local optima solution and PSO is better for Global Optima solution, it is better if the results of both compared. In this thesis using PSO is better result than GA result. GA and (PSO) are developed in MATLAB R2016a software as shown in Appendix (C) and Appendix (D) respectively. PSO results five (5) sectionalizing switches, seven (7) Automations switches and eighteen (18) reclosers and their respective position in distribution line. DIgSILENT Power Factory 15.1.7 software is used to demonstrate and simulate distribution system to assess reliability Index. Using Asset management strategy for network reconfiguration the distribution system, SAIFI is improve by 84.56 percentage from 87.2 to 13.461 per customer year, SAIDI is improved by 98.27 percentages from 5889.86 to 101.565 hours per customer year. ENS improved by 98.24 percentages from 119.407 to 3.913MWh per year, and EIC improved by 98.24 percentages from 11.942 to 0.21 and save 11.732 M$ in a year. These work have Payback period of 1.742, therefore it is economically feasible if implemented
DISTRIBUTION SYSTEM RELIABILITY IMPROVEMENT USING DISTRIBUTED GENERATION AND NETWORK RECONFIGURATION
(Hawassa University, 2021-10-28) MEKLIT GIRMA
Power supply reliability is the basic issue for economic and technology development of the country. The sufficient or adequate and secure supply of power will assure the reliability of the system. Unreliability of the system occur due to high outage frequency and duration, system overload and unsecure system or protection system. When the distribution system is reliable, it has capacity to meet the demand of customer and operate under adverse condition. Arbaminch distribution system has encountered frequent power interruption and power quality problem. The interruptions are mainly caused by system overload and short circuit fault. The reliability of the distribution system is assessed based on the data from Ethiopian Electric Power Corporation. Arbaminich substation of feeder -05 is selected as case study, which has high rate of interruption. Feeder -05 has SAIDI value of 236.8386 Hr./cust. /yr. and SAIFI of 221.6338 f/cust. /yr. The reliability indexes values of feeder -05 are not within the ranges of bench marks of reliability requirement. This thesis focused on reliability improvement of distribution system with better placement of distributed generation and network reconfiguration. Particle swarm optimization algorithm is used for placement of DG, size and network reconfiguration. The algorithm is done using MATLAB 2016 software. Based on the availability in the area, efficiency, cost and emission level, Solar and Microturbine sources are used as distributed generation. The suitable site and size of DG are found at bus 10 with suitable size 4.5 MW. For network reconfiguration sectionalizing switch is used. Before reconfiguration the switch was placed at bus 20, 21, 22,23 and 24. During network reconfiguration switch changed to bus 3, 4,12,24 and 31. The reliability indices SAFI, SAIDI and EENS value improved by 82.81%,78.89% and 78.10% respectively after DG with reconfiguration used. Expected interruption cost before applying the proposed method is 9,758,852$ /year. After the proposed method used expected interruption cost reduced to 2,995,270$ /year. This indicates that, 6,763,582 $/year is saved after using the proposed techniques
ENERGY EFFICIENCY ANALYSIS OF COMPRESSIVE SENSING BASED COOPERATIVE SPECTRUM SENSING IN COGNITIVE RADIO
(Hawassa University, 2020-10-22) TSEGA TEKLEWOLD TEKLEMARIAM
A range is a scant and valuable asset and a matter of worry with the quickly developing wireless communications. Wireless communication industries are increasing at a very fast pace as the wireless technologies are attracting the interest of many users, so the demand increases and researchers are looking for alternative adaptive measures. The essential usefulness to empower dynamic range access for CR is wideband spectrum sensing to discover more temporarily available frequency bands to fulfill the growing needs of wireless services. Also, the need to occasionally detect and an expansion in the quantity of channels to be detected further builds the energy interest. Thus, one of the principal challenges that limit the implementation of cognitive radio networks especially in the battery-powered terminal is due to its high energy consumption. Consequently, energy-proficient CSS in a CR network utilizing the CS based maximum minimum subband ED is the focal point of this thesis. The number of participating CRs in the cooperative spectrum sensing, sensing duration, data transmission duration, and fusion threshold play vital roles in designing an energy-efficient CSS system. In other words, increasing the number of participating CRs in the system leads to an increase in both consumed energy during CSS process and delay time; moreover, longer sensing time duration increases detection precision, but on the other hand, decreases spectrum efficiency and increases the consumed energy during sensing phases (i.e., sensing overhead).In the essence of above-mentioned facts, tackling a trade-off between performance improvement and overhead is our main focus research point in this thesis. Evaluation and analysis of performance are done by using MATLAB software. The simulation result shows that the Compressive sensing-based Max-Min subband ED has better performance than traditional Max-Min subband ED based on Shannon-Nyquist sampling theorem. Also, it shows that strategies remarkably increase the energy efficiency of the cooperative system; furthermore, it is shown optimality of Majority rule over other two hard decision fusion rules. Finally, optimization of sensing time, number of sensing users and fusion threshold for a cognitive radio is considered. Finally, the energy efficiency is enhanced by 74.6% when compared with the conventional energy detection-based EE
ENHANCING LOW VOLTAGE RIDE THROUGH CAPABILITY OF DFIG BASED WIND TURBINE: A CASE STUDY OF ADAMA-II WIND TURBINE
(Hawassa University, 2019-08-18) FSAHA MEBRAHTU
Doubly fed induction generators (DFIG) based wind turbines (WT) are major sources of energy generation around the world. One of such energy source is wind generation, which is very much popular now days. It utilizes doubly fed induction generator (DFIG) to generate electricity in generation mode. But sometimes wind turbines are disconnected from the power system in the event of grid faults. To avoid grid instability as well as to ensure the secure and reliable operation of the power systems, all wind turbines must stay connected with the grid during faults and capable to ensure the operation of the utility grid side during voltage sags in the event of a fault that is performed by analyzing the low voltage ride through (LVRT) capability of DFIG based wind turbines.. DFIG is very sensitive to any grid disturbances, if a severe voltage dip occurred due to grid fault, high currents will pass through stator and rotor windings and also a very high DC voltage would be induced in converter circuit, which may lead to damage the converter circuit and the DFIG windings. A crowbar protections system is essential to avoid the disconnection of the doubly fed induction wind generators from the network during faults and to protect the DFIG from the dangerous effects of the electrical fault. Accordingly, Ethiopia have been started to expand its energy generation by installing renewable energy source like wind farm. Presently, Ethiopia has installed wind farms like Ashegoda, Adama-I and Adama-II. The Adama-II wind farm project has 153 MW with 102 units, each of with generation capacity of 1.5 MW. This work focused on the improvement of low voltage ride through capability (LVRT) of Adama-II wind turbines. In this thesis a crowbar protection system is used to improve the power system fault ride through capability of DFIG of Adama-II. During the symmetrical fault using crowbar protection the value of crowbar current at time three 3 seconds is overshoot to 3000 A and it will reduce to the original condition after 100 ms. Also the value of stator voltage, stator flux during faulty and symmetrical conditions before the fault and after are the same, but during the voltage dip the stator flux is decreased and the stator voltage is also reduced. The dynamic behavior of DFIG under normal and various grid fault conditions are simulated and analyzed to provide the recommendations. MATLAB/Simulink software is utilized for the development of proposed system
EVALUATING CRYPTOGRAPHIC ALGORITHMS OF AUDIO AND VIDEO DATA FOR SYSTEM RESOURCE CONSTRAINED OF IoT DEVICES
(Hawassa University, 2019-10-27) WAGARI BERHANU
We are living in an internet period in which digital data exchange in electronic way has progressed tremendously and securing information has become a challenge. Unless a creative means of securing information has been developed, the problem will be vast and limitless. In a bid to keep the pace of the era, cryptography plays an important role in information security systems. Cryptography is a process of creating information indecipherable to an unauthorized person. It is quite a well-known fact that IoT (Internet of Things) is a system of interrelated computing devices or digital machines is the ability to transfer data over a network. the devices that used in IoT is low power devices for this reason, the system resource is one sever issues. To do so various cryptographic algorithms used in IoT devices. Meanwhile, these algorithms consume a significant amount of computing resources such as CPU time, memory and computation time. This thesis provides evaluating AES, Blowfish, RSA, Trivium and Elliptic Curve Cryptosystems based on system resource usage to securing IoT device communications on the basis of encryption time, decryption time, throughput, CPU time, power efficiency and memory usage in audio and video data using Java as the programming language to develop algorithms. The result obtained shows that AES has better performance with encryption time, decryption time, throughput rate, CPU time, power efficiency and memory usage with audio and video files in various format