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This dissertation aims to address two optimization problems involving power system reliabilty analysis, namely multi-area power system adequacy planning and transformer maintenance optimization. A new simulation method for power system reliability evaluation is proposed. The proposed method provides reliability indexes and distributions which can be used for risk assessment. Several solution methods for the planning problem are also proposed. The first method employs sensitivity analysis with Monte Carlo simulation. The procedure is simple yet effective and can be used as a guideline to quantify effectiveness of additional capacity. The second method applies scenario analysis with a state-space decomposition approach called global decomposition. The algorithm requires less memory usage and converges with fewer stages of decomposition. A system reliability equation is derived that leads to the development of the third method using dynamic programming. The main contribution of the third method is the approximation of reliability equation. The fourth method is the stochastic programming framework. This method offers modeling flexibility. The implementation of the solution techniques is presented and discussed. Finally, a probabilistic maintenance model of the transformer is proposed where mathematical equations relating maintenance practice and equipment lifetime and cost are derived. The closed-form expressions insightfully explain how the transformer parameters relate to reliability. This mathematical model facilitates an optimum, cost-effective maintenance scheme for the transformer.

This dissertation aims to address two optimization problems involving power system reliabilty analysis, namely multi-area power system adequacy planning and transformer maintenance optimization. A new simulation method for power system reliability evaluation is proposed. The proposed method provides reliability indexes and distributions which can be used for risk assessment. Several solution methods for the planning problem are also proposed. The first method employs sensitivity analysis with Monte Carlo simulation. The procedure is simple yet effective and can be used as a guideline to quantify effectiveness of additional capacity. The second method applies scenario analysis with a state-space decomposition approach called global decomposition. The algorithm requires less memory usage and converges with fewer stages of decomposition. A system reliability equation is derived that leads to the development of the third method using dynamic programming. The main contribution of the third method is the approximation of reliability equation. The fourth method is the stochastic programming framework. This method offers modeling flexibility. The implementation of the solution techniques is presented and discussed. Finally, a probabilistic maintenance model of the transformer is proposed where mathematical equations relating maintenance practice and equipment lifetime and cost are derived. The closed-form expressions insightfully explain how the transformer parameters relate to reliability. This mathematical model facilitates an optimum, cost-effective maintenance scheme for the transformer.

abstract: The power system is the largest man-made physical network in the world. Performing analysis of a large bulk system is computationally complex, especially when the study involves engineering, economic and environmental considerations. For instance, running a unit-commitment (UC) over a large system involves a huge number of constraints and integer variables. One way to reduce the computational expense is to perform the analysis on a small equivalent (reduced) model instead on the original (full) model. The research reported here focuses on improving the network reduction methods so that the calculated results obtained from the reduced model better approximate the performance of the original model. An optimization-based Ward reduction (OP-Ward) and two new generator placement methods in network reduction are introduced and numerical test results on large systems provide proof of concept. In addition to dc-type reductions (ignoring reactive power, resistance elements in the network, etc.), the new methods applicable to ac domain are introduced. For conventional reduction methods (Ward-type methods, REI-type methods), eliminating external generator buses (PV buses) is a tough problem, because it is difficult to accurately approximate the external reactive support in the reduced model. Recently, the holomorphic embedding (HE) based load-flow method (HELM) was proposed, which theoretically guarantees convergence given that the power flow equations are structure in accordance with Stahl’s theory requirements. In this work, a holomorphic embedding based network reduction (HE reduction) method is proposed which takes advantage of the HELM technique. Test results shows that the HE reduction method can approximate the original system performance very accurately even when the operating condition changes. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

Wind generation has become one of the most popular choices of technology for adding new generation capacity to power systems worldwide. Several factors have contributed to the increased integration of wind generation, including environmental concerns and the continual increase in fossil fuel prices. As well, recent regulations have moved toward limitations on greenhouse gases, especially in the European Union (EU). Similar laws are currently under consideration in the US and other parts of the world. Other factors have also promoted the use of wind energy, such as advances in manufacturing and control technology and the attractiveness of wind as a “green” source of energy. The large-scale integration of wind power into an electricity system introduces planning and operational challenges because of the intermittent nature of wind speed and the difficulty involved in predicting it. For these reasons, wind energy is often considered an unreliable energy source. Additional problems are associated with the integration of large-scale wind farms into an electrical grid, among which wind power fluctuation is the most challenging. To maximize the penetration level of wind energy in a grid, a reliable technology must be developed in order to eliminate or at least decrease wind power fluctuation. The primary goal of this thesis was to develop methods of maximizing the penetration level of wind energy conversion systems (WECSs) into a grid, which requires mitigating wind power fluctuation. A robust control technique has therefore been developed for mitigating wind power fluctuation. This control technique exploits historical environmental data collected over a number of years in order to evaluate the profile of the output power of a variety of wind energy conversion systems (WECSs). The developed control technique was applied to Types A and C WECSs modifying the pitch angle controller of Type A WECS and the back-to-back converter control of Type C WECS. The Attachment of a storage device to the WECSs after the control technique is applied was investigated from both an economic and a technical point of view. The optimum sizing and siting of the wind energy conversion system equipped with the proposed control technique was also studied. This research is expected to contribute to the advancement of WECS technology by presenting a feasible solution to the problems associated with the integration of large-scale WECSs into electrical grids.

Wind generation has become one of the most popular choices of technology for adding new generation capacity to power systems worldwide. Several factors have contributed to the increased integration of wind generation, including environmental concerns and the continual increase in fossil fuel prices. As well, recent regulations have moved toward limitations on greenhouse gases, especially in the European Union (EU). Similar laws are currently under consideration in the US and other parts of the world. Other factors have also promoted the use of wind energy, such as advances in manufacturing and control technology and the attractiveness of wind as a “green” source of energy. The large-scale integration of wind power into an electricity system introduces planning and operational challenges because of the intermittent nature of wind speed and the difficulty involved in predicting it. For these reasons, wind energy is often considered an unreliable energy source. Additional problems are associated with the integration of large-scale wind farms into an electrical grid, among which wind power fluctuation is the most challenging. To maximize the penetration level of wind energy in a grid, a reliable technology must be developed in order to eliminate or at least decrease wind power fluctuation. The primary goal of this thesis was to develop methods of maximizing the penetration level of wind energy conversion systems (WECSs) into a grid, which requires mitigating wind power fluctuation. A robust control technique has therefore been developed for mitigating wind power fluctuation. This control technique exploits historical environmental data collected over a number of years in order to evaluate the profile of the output power of a variety of wind energy conversion systems (WECSs). The developed control technique was applied to Types A and C WECSs modifying the pitch angle controller of Type A WECS and the back-to-back converter control of Type C WECS. The Attachment of a storage device to the WECSs after the control technique is applied was investigated from both an economic and a technical point of view. The optimum sizing and siting of the wind energy conversion system equipped with the proposed control technique was also studied. This research is expected to contribute to the advancement of WECS technology by presenting a feasible solution to the problems associated with the integration of large-scale WECSs into electrical grids.

Along with the increasing scale of the power system and stressed operation in the transmission network, the stability margin is reduced considerably. As a traditional solution, the constructions of new transmission lines and generators sometimes are constrained by local environmental and regulatory constraints. Another characteristic of a modern network is the higher number of transmission inter-connections which appear in the large-scale power system. As an economic benefit, inter-connection can reduce the cost of electricity and enhance system reliability [1]. Those inter-connected tie lines are operated normally under heavy flow to maximize the usage benefit. This characteristic contributes to the complexity of operating and controlling the system. In recent years, along with the development of power electronic devices, the Flexible AC Transmission Systems (FACTS) has been used in the system as an alternative solution. It can maximize the usage benefit of the HV transmission line and make the large-scale power system more controllable. By using FACTS devices, the system can survive serious system contingencies with real-time control action, instead of providing a large steady state stability margin. Therefore, the system transfer capacity can be significantly increased. Electromechanical oscillations are observed in today's power system; such oscillations are recognized as a major concern in power system operation. Once begun, the oscillations may continue for a while before being halted by the damping torque from the system, or they may continue to grow (inadequate damping) and eventually cause system instability by losing synchronicity. The traditional and widely applied solution for oscillation damping is the Power System Stabilizer (PSS), which is efficient in damping local mode oscillation and inter-area oscillation in certain conditions. In recent years, research and development of the application of FACTS devices in suppressing system oscillations, especially for inter-area mode oscillation damping, has attracted increasing interest [1]. The primary objective of this thesis is to design robust FACTS controllers for enhancing power system dynamic stability by damping low frequency electromechanical oscillations. Recently, various nonlinear control techniques have been applied in power system control. The performance of nonlinear controllers is influenced by the parameter uncertainty and external disturbance. This thesis will present a novel approach of a robust Variable Structure Control (VSC)-based FACTS controller for damping multi-mode oscillations. Robust performances of the proposed controllers in different power systems are demonstrated by computer simulation.

Thesis (MScEng)--University of Stellenbosch, 2001. / ENGLISH ABSTRACT: Recent advances in semiconductor technology extended the economic power range for DC transmission to just a few MW. Network planners need tools to compare AC and DC alternatives in order to find the best technical and economic solution for a specific network. TESAT, a software analysis tool, is developed to determine the optimum conductor and line technology for a network. Voltage regulation problems are identified and can be solved with network devices which have the potential to solve network problems more effectively and economically than ever before. PSAT, another software analysis tool developed in previous research, is used to model networks and support technologies. Hence, with the aid of TESAT and PSAT, line and support technologies are combined in an attempt to find the most effective solution in terms of cost and technical performance. This is demonstrated with the aid of a case study. Furthermore, interfaces between PSAT and the real world are developed. This includes an extension to the input interface of PSAT that calculates the equivalent impedances of a transmission line automatically, as well as an interface to share data between ReticMaster and PSAT. A dispersed generation and support technology database is also developed as an extension to the output interface ofPSAT. / AFRIKAANSE OPSOMMING: Onlangse vooruitgang in halfgeleiertegnologie het tot gevolg dat GS transmissie ekonomies is vir slegs 'n paar MW. Netwerkbeplanners benodig gevolglik pakette om WS en GS alternatiewe te vergelyk vir 'n spesifieke netwerk. In hierdie tesis is 'n analitiese sagteware-pakket (TESAT) dus ontwikkelom die optimale geleier en lyntegnologie VIr 'n netwerk te bepaal. Spanningsregulasie-probleme word geïdentifiseer en opgelos met netwerktoestelle wat die potensiaal het om netwerkprobleme meer doeltreffend en ekonomies as ooit tevore op te los. PSAT, 'n ander analitiese sagteware-pakket wat in vorige navorsing ontwikkel is, word dan ook gebruik om netwerke en steuningstegnologieë te modelleer. Dus word PSA T en TESA T gebruik om lyn- en steuningstegnologieë te kombineer. Die doel hiervan is om die mees doeltreffende oplossing in terme van kostes en tegniese werksverrigting te vind. Dit word met behulp van 'n gevallestudie gedemonstreer. Verder word koppelvlakke tussen PSA T en die eksterne wêreld ontwikkel. Dit sluit in: (a) 'n uitbreiding van die intreekoppelvlak van PSAT wat die ekwivalente impedansie vir 'n transmissielyn outomaties bereken; (b) die koppelvlak om data te deel tussen PSAT en ReticMaster. 'n Verspreide generasie- en steuningstegnologie databasis is uiteindelik ook ontwikkel as 'n uitbreiding van die uittreekoppelvlak van PSAT.

The role of electric power systems has grown steadily in both scope and importance over time making electricity increasingly recognized as a key to social and economic progress in many developing countries. In a sense, reliable power systems constitute the foundation of all prospering societies. The constant expansion in electric power systems, along with increased energy demand, requires that power systems become more and more complex. Such complexity results in much uncertainty which demands comprehensive reliability and security assessment to ensure reliable energy supply. Power industries in many countries are facing these challenges and are trying to increase the computational capability to handle the ever-increasing data and analytical needs of operations and planning. Moreover, the deregulated electricity markets have been in operation in a number of countries since the 1990s. During the deregulation process, vertically integrated power utilities have been reformed into competitive markets, with initial goals to improve market efficiency, minimize production costs and reduce the electricity price. Given the benefits that have been achieved by deregulation, several new challenges are also observed in the market. Due to fundamental changes to the electric power industry, traditional management and analysis methods cannot deal with these new challenges. Deterministic reliability assessment criteria still exists but it doesn’t satisfy the probabilistic nature of power systems. In the deterministic approach the worst case analysis results in excess operating costs. On the other hand, probabilistic methods are now widely accepted. The analytical method uses a mathematical formula for reliability evaluation and generates results more quickly but it needs accurate and a lot of assumptions and is not suitable for large and complex systems. Simulation based techniques take care of much uncertainty and simulates the random behavior of the system. However, it requires much computing power, memory and other computing resources. Power engineers have to run thousands of times domain simulations to determine the stability for a set of credible disturbances before dispatching. For example, security analysis is associated with the steady state and dynamic response of the power system to various disturbances. It is highly desirable to have real time security assessment, especially in the market environment. Therefore, novel analysis methods are required for power systems reliability and security in the deregulated environment, which can provide comprehensive results, and high performance computing (HPC) power in order to carry out such analysis within a limited time. Further, with the deregulation in power industry, operation control has been distributed among many organizations. The power grid is a complex network involving a range of energy resources including nuclear, fossil and renewable energy resources with many operational levels and layers including control centers, power plants and transmission and distribution systems. The energy resources are managed by different organizations in the electricity market and all these participants (including producers, consumers and operators) can affect the operational state of the power grid at any time. Moreover, adequacy analysis is an important task in power system planning and can be regarded as collaborative tasks, which demands the collaboration among the electricity market participants for reliable energy supply. Grid computing is gaining attention from power engineering experts as an ideal solution to the computational difficulties being faced by the power industry. Grid computing infrastructure involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid computing technology offers potentially feasible support to the design and development of grid computing based infrastructure for power system reliability and security analysis. It can help in building infrastructure, which can provide a high performance computing and collaborative environment, and offer an optimal solution between cast and efficiency. While power system analysis is a vast topic, only a limited amount of research has been initiated in several places to investigate the applications of grid computing in power systems. This thesis will investigate probabilistic based reliability and security analysis of complex power systems in order to develop new techniques for providing comprehensive result with enormous efficiency. A review of existing techniques was conducted to determine the computational needs in the area of power systems. The main objective of this research is to propose and develop a general framework of computing grid and special grid services for probabilistic power system reliability and security assessment in the electricity market. As a result of this research, grid computing based techniques are proposed for power systems probabilistic load flow analysis, probabilistic small signal analysis, probabilistic transient stability analysis, and probabilistic contingencies analysis. Moreover, a grid computing based system is designed and developed for the monitoring and control of distributed generation systems. As a part of this research, a detailed review is presented about the possible applications of this technology in other aspects of power systems. It is proposed that these grid based techniques will provide comprehensive results that will lead to great efficiency, and ultimately enhance the existing computing capabilities of power companies in a cost-effective manner. At a part of this research, a small scale computing grid is developed which will consist of grid services for probabilistic reliability and security assessment techniques. A significant outcome of this research will be the improved performance, accuracy, and security of data sharing and collaboration. More importantly grid based computing will improve the capability of power system analysis in a deregulated environment where complex and large amounts of data would otherwise be impossible to analyze without huge investments in computing facilities.

The role of electric power systems has grown steadily in both scope and importance over time making electricity increasingly recognized as a key to social and economic progress in many developing countries. In a sense, reliable power systems constitute the foundation of all prospering societies. The constant expansion in electric power systems, along with increased energy demand, requires that power systems become more and more complex. Such complexity results in much uncertainty which demands comprehensive reliability and security assessment to ensure reliable energy supply. Power industries in many countries are facing these challenges and are trying to increase the computational capability to handle the ever-increasing data and analytical needs of operations and planning. Moreover, the deregulated electricity markets have been in operation in a number of countries since the 1990s. During the deregulation process, vertically integrated power utilities have been reformed into competitive markets, with initial goals to improve market efficiency, minimize production costs and reduce the electricity price. Given the benefits that have been achieved by deregulation, several new challenges are also observed in the market. Due to fundamental changes to the electric power industry, traditional management and analysis methods cannot deal with these new challenges. Deterministic reliability assessment criteria still exists but it doesn’t satisfy the probabilistic nature of power systems. In the deterministic approach the worst case analysis results in excess operating costs. On the other hand, probabilistic methods are now widely accepted. The analytical method uses a mathematical formula for reliability evaluation and generates results more quickly but it needs accurate and a lot of assumptions and is not suitable for large and complex systems. Simulation based techniques take care of much uncertainty and simulates the random behavior of the system. However, it requires much computing power, memory and other computing resources. Power engineers have to run thousands of times domain simulations to determine the stability for a set of credible disturbances before dispatching. For example, security analysis is associated with the steady state and dynamic response of the power system to various disturbances. It is highly desirable to have real time security assessment, especially in the market environment. Therefore, novel analysis methods are required for power systems reliability and security in the deregulated environment, which can provide comprehensive results, and high performance computing (HPC) power in order to carry out such analysis within a limited time. Further, with the deregulation in power industry, operation control has been distributed among many organizations. The power grid is a complex network involving a range of energy resources including nuclear, fossil and renewable energy resources with many operational levels and layers including control centers, power plants and transmission and distribution systems. The energy resources are managed by different organizations in the electricity market and all these participants (including producers, consumers and operators) can affect the operational state of the power grid at any time. Moreover, adequacy analysis is an important task in power system planning and can be regarded as collaborative tasks, which demands the collaboration among the electricity market participants for reliable energy supply. Grid computing is gaining attention from power engineering experts as an ideal solution to the computational difficulties being faced by the power industry. Grid computing infrastructure involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid computing technology offers potentially feasible support to the design and development of grid computing based infrastructure for power system reliability and security analysis. It can help in building infrastructure, which can provide a high performance computing and collaborative environment, and offer an optimal solution between cast and efficiency. While power system analysis is a vast topic, only a limited amount of research has been initiated in several places to investigate the applications of grid computing in power systems. This thesis will investigate probabilistic based reliability and security analysis of complex power systems in order to develop new techniques for providing comprehensive result with enormous efficiency. A review of existing techniques was conducted to determine the computational needs in the area of power systems. The main objective of this research is to propose and develop a general framework of computing grid and special grid services for probabilistic power system reliability and security assessment in the electricity market. As a result of this research, grid computing based techniques are proposed for power systems probabilistic load flow analysis, probabilistic small signal analysis, probabilistic transient stability analysis, and probabilistic contingencies analysis. Moreover, a grid computing based system is designed and developed for the monitoring and control of distributed generation systems. As a part of this research, a detailed review is presented about the possible applications of this technology in other aspects of power systems. It is proposed that these grid based techniques will provide comprehensive results that will lead to great efficiency, and ultimately enhance the existing computing capabilities of power companies in a cost-effective manner. At a part of this research, a small scale computing grid is developed which will consist of grid services for probabilistic reliability and security assessment techniques. A significant outcome of this research will be the improved performance, accuracy, and security of data sharing and collaboration. More importantly grid based computing will improve the capability of power system analysis in a deregulated environment where complex and large amounts of data would otherwise be impossible to analyze without huge investments in computing facilities.