Power Systems & Energy Engineering
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Item DISTRIBUTION SYSTEM RELIABLITY IMPROVEMENT USING DISTRIBUTED GENERATION AND NETWORK RECONFIGURATION Case study: Arbaminch Distribution system(Hawassa University, 2021-10-22) MEKLIT GIRMAPower 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 techniquesItem IDENTIFICATION, CLASSIFICATION AND MITIGATION OF POWER QUALITY ISSUES IN DISTRIBUTION NETWORK USING STOCKWELL TRANSFORM AND DISTRIBUTION STATIC COMPENSATOR (A CASE STUDY OF YIRGALEM SUBSTATION)(Hawassa University, 2022-12-23) Epaphros MengistuPower quality has become a crucial concern recently due to the increase of the consumption of electrical load and the increment in the use of sensitive devices connected to power systems. In spite of that, complexity in modern daily life and the increased usage of semiconductors make non linear load a real threat to power quality level. In order that maintain power quality and to ensure its reliability, power quality disturbances must be identified and classified correctly and precisely. Thus, identification algorithms support decision makers to identified and mitigate the disturbance, and protect the power network from a high level of financial loss. In this thesis study identification, classification and mitigation of power quality issues in Awada industry zone. The measured voltage and current harmonic distortion levels are compared with the IEEE 519-2014 and IEC 61000-2-2 / -3-4 standards. The harmonic voltage distortion level in the factory has found to be well under the limits set by these standards while the current harmonic distortion levels on one of the transformer among four transform exceeds the limits with a maximum percentage total harmonic distortion current value of up to 23.09%. First, an identification process covering the most important and common power quality issues for further analyzed and discussed. Then after, most of the powerful processing algorithms in addition to support vector machine technique was investigated and their results are discussed. SVM then classify complex data and enhancing the evaluation process. This method achieved a sufficient detection algorithm, which overcame the Wavelet, Fourier and Hilbert limitations and resulted in an overall accuracy of 91.08%, 88.91% and 86.8% respectively. This resulted in a substantial improvement in terms of overall accuracy, with more than 97.1% when using Stockwell transform. In addition to the average classification accuracy, other common performance measures computed from the confusion matrix also presented and highest average accuracy of SVM is 98.3%. For mitigating, the current harmonic distortion level in the industry a D-STATCOM in current control mode is designed. The performance of the D-STATCOM is evaluated by simulating the distribution network with and without D-STATCOM. The simulation results show that the source current becomes pure sinusoidal and in-phase with the source voltage within 0.02 second and THDI reduced to 4.36% after the enabled of the D-STATCOM in the systemItem REACTIVE POWER COMPENSATION AND LOAD FREQUENCY CONTROL OF GRID CONNECTED MICRO GRID SYSTEM USING STATIC VAR COMPENSATOR (CASE STUDY: DILLA SUBSTATION)(Hawassa University, 2021-10-28) KUMILACHEW CHANEIn the modern power system, reactive power compensation and load frequency control are two of the main issues. The aim of this thesis is to study reactive power compensation and load frequency control of the grid-connected micro grid system (GCMG) under variable load .In this work, an Artificial Neural Network based Static VAR compensator (ANN-SVC) and Load Frequency Controller (LFC) will be proposed for reactive power compensation and load frequency control of the grid-connected micro grid system, The artificial neural network (ANN) is used to control the the SVC gete signal for proper controlling of the thyristor valve in the circulated system current management. Power system Planning and management provide the strategy for reactive power compensation and load frequency disturbance control. The ANN-controlled SVC is used for managing and compensating of reactive power in the system and LFCis control the system load frequency disturbance and the LFC controlling loop component is control and managed by ANN signal for proper controlling of the load frequency error. The real and reactive powers before applying the SVC at the peak load conditions are 40.56MW and 27.16MVAr, respectively, before reactive power compensation. During contingency conditions, the real and reactive powers are 36.03MW and 30.42MVAr, respectively, and the frequency is highly disturbed for a fraction of a second, but after compensation, the real power is improved to 50.54MW, while the reactive power is reduced to 17.34MVAr. Therefore, real power is improved by 52.18% while reactive power is compensated by 87.02%. The steady-state load frequency error is reduced by 95%, while the system power factor is improved by 94%. A detailed comparative analysis of the proposed ANN-based SVC with the fuzzy-based and multi-objective fire fly (MOFA) algorithm SVC is presented, which shows that the ANN-based SVC has better performance, fast and accuracy, in case of the above justification ANN is more prifereble than MOFA and FUZZY algorithem. The general GCMG structure with the compensation and controlling process was designed by ETAP and MATLAB/SimulinkItem DISTRIBUTION SYSTEM RELIABILITY ASSESSMENT AND ENHANCEMENT BY USING TIE SWITCHES AND SECTIONALIZER’S (CASE STUDY: BULE HORA DISTRIBUTION SYSTEM)(Hawassa University, 2022-10-22) ABABO BIKILAThe majority of outage events experienced by customers are due to electrical distribution failures. Increasing distribution network reliability is a necessity in order to reduce interruption events Unreliable electric power distribution affects daily activity and drags the modern lifestyle. Basically, Power Distribution Reliability has been a major challenge in Bule hora city. The interruptions are caused mainly by the short circuit (SC) and earth fault (EF). Bule hora substation’s System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI) are 341.46 interruptions per customer per year and 666.82 hours per customer per year, respectively. Bule hora substation is not reliable by the standard of Ethiopian Electric Agency (EEA) which has set SAIFI as equal to 20 interruptions per customer per year and SAIDI which is around 25 hours per customer per year. Thus, the objective of the study is to assess the reliability of the existing distribution system and suggest solutions for reliability improvement in heuristic techniques. To limit the scope of the study, 15 kV Bule hora city feeder of the substation has been chosen for reliability enhancement measures. The historical outage interruption data of years 2009-2011 E.C has been used as a base year. The study has evaluated four different mitigation cases to improve the system reliability. From the mitigation cases with the lowest SAIDI, SAIFI and Expected Energy Not Supplied (EENS) at a reasonable cost has been selected. The simulation results have been done with the help of Electrical Transient Analysis Program (ETAP 16.0) software. The result of this thesis work reveals that the reliability of the system has been improved significantly by assessing reliability enhancement solutions that are justified economically and technically. Hence, the overall reliability of Bule hora city feeder indices SAIFI by 83.23%, SAIDI by 89.48% and EENS by 97.51%, have been improved as compared with the existing system for the simulated best option. The economic analysis shows that the selected solution results in a cost saving of 2,105,530.3 ETB per year from the unsold energy of one feeder only with 1.48 payback period investment. Satisfaction of the society has been considered as a priceless benefit as wellItem DISTRIBUTION NETWORK OPTIMIZATION BY OPTIMAL SIZING AND PLACEMENT OF D-STATCOM USING TEACHING AND LEARNING BASED OPTIMIZATION ALGORITHM (CASE STUDY: YIRGALEM SUBSTATION)(Hawassa University, 2021-10-18) AZMERAW ARGAWDistribution system is part of an electric power system which links the high voltage transmission networks with the end consumers. This work offers the way of improving the performance of the distribution network by improving voltage profile and reduction of power loss via injecting reactive power through the network. Optimal siting and sizing of custom power devices in power distribution networks maximizes voltage profile, compensates reactive power, minimizes power loss and enhances voltage profile. The search for optimal size and locations of these devices in radial distribution networks is challenging and requiring robust scheduling. This study is conducted with a focus on Aposto feeder of Yirgalem distribution network. The voltage profiles of most buses are not in an acceptable range, and the voltage stability index of the buses shows that network is prone to voltage stability problem. In this study, it is aimed to find the best optimal D-STATCOM sizing and placement by using Teaching and Learning Based Optimization (TLBO). Results obtained have been compared with those of the conventional optimization techniques reported in literature. For the Aposto feeder 62-bus network, the optimal location and size of D-STATCOM were determined at bus 38 with 1019.18 𝑘𝑉𝑎𝑟, at bus 28 with 942.96 𝑘𝑉𝑎𝑟, at bus 39 with 1074 𝑘𝑉𝑎𝑟 and at bus 25 with 1184 𝑘𝑉𝑎𝑟 by the GA, PSO, GREY WOLF and WHALE OPTIMIZATION method respectively. While the TLBO approach obtained the optimal site and size of the D-STATCOM in the network to be bus 51 and 871.4 𝐾𝑉𝑎𝑟 at normal load condition. As stated, the TLBO method performs better in terms of reducing both real and reactive power losses. The real power loss percentage reduction of the test system is 27.09%, 69.19% and 70.24% whereas the reactive power loss percentage reduction is 30.97%, 68.85% and 69.85% for light load, normal load, and heavy load respectively. Also, the minimum voltage level in the worst case is significantly enhanced from 0.93pu to 0.988pu. The model has been formulated to minimize the total cost of the network by determining the optima of the substation locations and power, the load transfers between the demand centers, the feeder routes and the load flow in the network subject to a set of constraints. As per the economic evaluations, the proposed solution is cost-effective. In this research D-STATCOM control is developed based on artificial intelligent (AI) using artificial neural network (ANN), which depends on optimum values obtained by TLBO. Generally, the simulation results show that the proposed technique is effective to maintain all buses voltage magnitude within the IEEE acceptable limit and to reduce power losses significantlyItem TRANSMISSION LINE VOLTAGE PROFILE IMPROVEMENT AND POWER LOSS REDUCTION BY OPTIMAL PLACEMENT OF STATIC SYNCHRONOUS COMPENSATOR USING TEACHING LEARNING BASED ALGORITHMS(Hawassa University, 2022-03-18) Mulye GetuThe power transmission system transports electric power generated at generation plant to distribution system. The increasing power demand of customers causes the power transmission system to become stressed when connected to distribution system. This leads to voltage instability and, further to, transmission power loss, which can lead to power system malfunction and system collapse. Most bus voltages are not within acceptable limits, and the voltage index of the buses indicates that the network is prone to voltage instability issues. The objective of this thesis is to determine the best placement for a static synchronous compensator (STATCOM), which is one of the Flexible AC Transmission Systems (FACTS) devices, on the Alaba to Bukuluguma Transmission System network to minimize transmission line loss, improve voltage profile, and enhance power transfer capacity. The power flow analysis by Newton Raphson algorithm in MATLAB environment is used and Teaching Learning-based optimization techniques (TLBO) are adopted for optimal sizing and location of the device. The obtained results were compared to those reported in the literature for conventional optimization techniques. The optimal location and size of STATCOM for the Alaba to Bukuluguma transmission network were identified using the genetic algorithm (GA) and particle swarm optimization (PSO) methods accordingly, 25.8MVar at bus 6 and 25.5 MVar, at bus 5 respectively. According to the TLBO technique, bus 4 with 25MVar is the best placement and size of STATCOM in the network. The TLBO approach, as previously indicated, performs better in terms of reducing real and reactive power losses. The test system's real power loss reduction is 39.8 percent, while the reactive power loss reduction is 49.3 percent. In addition, the worst-case minimum voltage level has been enhanced from 0.878pu to 0.953pu. STATCOM control is established in this study utilizing artificial intelligence (AI) and an artificial neural network (ANN), which is based on TLBO's optimal values. In general, simulation results demonstrate that the suggested approach is effective in keeping all bus voltage magnitudes within the IEEE permissible limit while also drastically reducing power losses.Item Impact of Distributed Generation on Distribution Network Protection scheme and Adaptive Protection Coordination using Harris’ Hawks Optimization(Hawassa University, 2022-12-27) ABENEZER KASSA USAMOThe Modern Power System which has grown both in size and complexity, that means requires fast, accurate and reliable Protective schemes for protecting major equipment’s and to maintain system stability and reliability. Distribution networks are evolving into active meshed networks with bidirectional power flow as the penetration of distributed generation (DG) sources is increasing. Interconnecting DG to an existing distribution system provides various benefits to several entities as for example the owner, utility, and the final user. DG provides an enhanced power quality, higher reliability of the distribution system and can peak shaves and fill valleys. Penetration of a DG into an existing distribution system has many impacts on the system, with the power system protection being one of the major issues. This necessitates the use of directional relaying schemes in these emerging active distribution networks. However, conventional directional overcurrent (OC) protection will not be adequate to protect these networks against the stochastic nature of DGs and the changing network architectures. Hence, this study proposes an adaptive directional overcurrent relay algorithm that determines optimal protection settings according to varying fault currents and paths induced by the DGs in active meshed distribution networks. Location and technology of the DG sources are changed to study the effect that these changes may have on the coordination of protective directional over-current relays (DOCR). Results are compared to that of the normal case to investigate the impact of the DG on the short circuit currents flowing through different branches of the network to deduce the effect on protective devices. This study presents an adaptive protection coordination scheme for optimal coordination of DOCRs in interconnected power networks with the impact of DG. The used coordination technique is the Harris Hawks Optimization (HHO), selected due to adaptive & time-varying parameters allows HHO to handle difficulties of search including local optimal solution, multi modality & deceptive optima. Adaptive relaying describes protection schemes that adjust settings and/or logic of operations based on the prevailing conditions of the system. These adjustments can help to avoid relay miss-operation. Adjustments could include, but are not limited to, the logging of data for post-mortem analysis, communication throughout the system, as well changing relay parameters. Several concepts will be discussed, one of which will be implemented to prove the value of the new tools available. The optimal coordination of DOCR is find by with MATLAB code using HHO technique and the adaptive protection scheme model will develop in DIgSILENT/Power Factory. The results validate the ability of the proposed protection scheme to capture the uncertainties of the DGs and determine optimal protection settings, while ensuring minimal operating timeItem IDENTIFICATION, CLASSIFICATION AND MITIGATION OF POWER QUALITY ISSUES IN DISTRIBUTION NETWORK USING STOCKWELL TRANSFORM AND DISTRIBUTION STATIC COMPENSATOR(Hawassa University, 2022-10-16) EPAPHROS MENGISTUPower quality has become a crucial concern recently due to the increase of the consumption of electrical load and the increment in the use of sensitive devices connected to power systems. In spite of that, complexity in modern daily life and the increased usage of semiconductors make non linear load a real threat to power quality level. In order that maintain power quality and to ensure its reliability, power quality disturbances must be identified and classified correctly and precisely. Thus, identification algorithms support decision makers to identified and mitigate the disturbance, and protect the power network from a high level of financial loss. In this thesis study identification, classification and mitigation of power quality issues in Awada industry zone. The measured voltage and current harmonic distortion levels are compared with the IEEE 519-2014 and IEC 61000-2-2 / -3-4 standards. The harmonic voltage distortion level in the factory has found to be well under the limits set by these standards while the current harmonic distortion levels on one of the transformer among four transform exceeds the limits with a maximum percentage total harmonic distortion current value of up to 23.09%. First, an identification process covering the most important and common power quality issues for further analyzed and discussed. Then after, most of the powerful processing algorithms in addition to support vector machine technique was investigated and their results are discussed. SVM then classify complex data and enhancing the evaluation process. This method achieved a sufficient detection algorithm, which overcame the Wavelet, Fourier and Hilbert limitations and resulted in an overall accuracy of 91.08%, 88.91% and 86.8% respectively. This resulted in a substantial improvement in terms of overall accuracy, with more than 97.1% when using Stockwell transform. In addition to the average classification accuracy, other common performance measures computed from the confusion matrix also presented and highest average accuracy of SVM is 98.3%. For mitigating, the current harmonic distortion level in the industry a D-STATCOM in current control mode is designed. The performance of the D-STATCOM is evaluated by simulating the distribution network with and without D-STATCOM. The simulation results show that the source current becomes pure sinusoidal and in-phase with the source voltage within 0.02 second and THDI reduced to 4.36% after the enabled of the D-STATCOM in the system.Item REACTIVE POWER COMPENSATION AND LOAD FREQUENCY CONTROL OF GRID CONNECTED MICRO GRID SYSTEM USING STATIC VAR COMPENSATOR (CASE STUDY: DILLA SUBSTATION(Hawassa University, 2021-03-15) Kumilachew chanen the modern power system, reactive power compensation and load frequency control are two of the main issues. The aim of this thesis is to study reactive power compensation and load frequency control of the grid-connected micro grid system (GCMG) under variable load .In this work, an Artificial Neural Network based Static VAR compensator (ANN-SVC) and Load Frequency Controller (LFC) will be proposed for reactive power compensation and load frequency control of the grid-connected micro grid system, The artificial neural network (ANN) is used to control the the SVC gete signal for proper controlling of the thyristor valve in the circulated system current management. Power system Planning and management provide the strategy for reactive power compensation and load frequency disturbance control. The ANN-controlled SVC is used for managing and compensating of reactive power in the system and LFCis control the system load frequency disturbance and the LFC controlling loop component is control and managed by ANN signal for proper controlling of the load frequency error. The real and reactive powers before applying the SVC at the peak load conditions are 40.56MW and 27.16MVAr, respectively, before reactive power compensation. During contingency conditions, the real and reactive powers are 36.03MW and 30.42MVAr, respectively, and the frequency is highly disturbed for a fraction of a second, but after compensation, the real power is improved to 50.54MW, while the reactive power is reduced to 17.34MVAr. Therefore, real power is improved by 52.18% while reactive power is compensated by 87.02%. The steady-state load frequency error is reduced by 95%, while the system power factor is improved by 94%. A detailed comparative analysis of the proposed ANN-based SVC with the fuzzy-based and multi-objective fire fly (MOFA) algorithm SVC is presented, which shows that the ANN-based SVC has better performance, fast and accuracy, in case of the above justification ANN is more prifereble than MOFA and FUZZY algorithem. The general GCMG structure with the compensation and controlling process was designed by ETAP and MATLAB/SimulinItem IMPACT OF DISTRIBUTED GENERATION ON DISTRIBUTION NETWORK PROTECTION SCHEME AND ADAPTIVE PROTECTION COORDINATION USING HARRIS’ HAWKS OPTIMIZATION(Hawassa University, 2022-07-26) ABENEZER KASSA USAMOThe Modern Power System which has grown both in size and complexity, that means requires fast, accurate and reliable Protective schemes for protecting major equipment’s and to maintain system stability and reliability. Distribution networks are evolving into active meshed networks with bidirectional power flow as the penetration of distributed generation (DG) sources is increasing. Interconnecting DG to an existing distribution system provides various benefits to several entities as for example the owner, utility, and the final user. DG provides an enhanced power quality, higher reliability of the distribution system and can peak shaves and fill valleys. Penetration of a DG into an existing distribution system has many impacts on the system, with the power system protection being one of the major issues. This necessitates the use of directional relaying schemes in these emerging active distribution networks. However, conventional directional overcurrent (OC) protection will not be adequate to protect these networks against the stochastic nature of DGs and the changing network architectures. Hence, this study proposes an adaptive directional overcurrent relay algorithm that determines optimal protection settings according to varying fault currents and paths induced by the DGs in active meshed distribution networks. Location and technology of the DG sources are changed to study the effect that these changes may have on the coordination of protective directional over-current relays (DOCR). Results are compared to that of the normal case to investigate the impact of the DG on the short circuit currents flowing through different branches of the network to deduce the effect on protective devices. This study presents an adaptive protection coordination scheme for optimal coordination of DOCRs in interconnected power networks with the impact of DG. The used coordination technique is the Harris Hawks Optimization (HHO), selected due to adaptive & time-varying parameters allows HHO to handle difficulties of search including local optimal solution, multi modality & deceptive optima. Adaptive relaying describes protection schemes that adjust settings and/or logic of operations based on the prevailing conditions of the system. These adjustments can help to avoid relay miss-operation. Adjustments could include, but are not limited to, the logging of data for post-mortem analysis, communication throughout the system, as well changing relay parameters. Several concepts will be discussed, one of which will be implemented to prove the value of the new tools available. The optimal coordination of DOCR is find by with MATLAB code using HHO technique and the adaptive protection scheme model will develop in DIgSILENT/Power Factory. The results validate the ability of the proposed protection scheme to capture the uncertainties of the DGs and determine optimal protection settings, while ensuring minimal operating time