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.

The work presented in this thesis was concerned with the implementation of a damage control method for U.S. Navy shipboard power systems (SPS). In recent years, the Navy has been seeking an automated damage control and power system management approach for future reconfigurable shipboard power systems. The methodology should be capable of representing the dynamic performance (differential algebraic description), the steady state performance (algebraic description), and the system reconfiguration routines (discrete events) in one comprehensive tool. The damage control approach should also be able to improve survivability, reliability, and security, as well as reduce manning through the automation of the reconfiguration of the SPS network. To this end, this work implemented a damage control method for a notional Next Generation Integrated Power System. This thesis presents a static implementation of a dynamic formulation of a new damage control method at the DC zonal Integrated Flight Through Power system level. The proposed method used a constrained binary genetic algorithm to find an optimal network configuration. An optimal network configuration is a configuration which restores all of the de-energized loads that are possible to be restored based on the priority of the load without violating the system operating constraints. System operating limits act as constraints in the static damage control implementation. Off-line studies were conducted using an example power system modeled in PSCAD, an electromagnetic time domain transient simulation environment and study tool, to evaluate the effectiveness of the damage control method in restoring the power system. The simulation results for case studies showed that, in approximately 93% of the cases, the proposed damage algorithm was able to find the optimal network configuration that restores the power system network without violating the power system operating constraints.

In shipboard power systems (SPS), it is important to provide continuous power to vital loads so that their desired missions can be completed successfully. Several components exist between the primary source and the vital load such as transformers, cables, or switching devices. These components can fail due to mechanical stresses, electrical stresses, and overloading which could lead to a system failure. If the normal path to a vital load cannot supply power to it, then it should be powered through its alternate path. The process of restoring, balancing, and minimizing power losses to loads is called network reconfiguration. Prognostics is the ability to predict precisely and accurately the remaining useful life of a failing component. In this work, the prognostic information of the power system components is used to determine if reconfiguration should be performed if the system is unable to accomplish its mission. Each component will be analyzed using the Weibull Distribution to compute the conditional reliability from present time to the end of the mission. To determine if reconfiguration is needed, all components to a given load will be utilized in structure functions to determine if a load will be able to survive during a time period. Structure functions are used to show how components are interconnected, and also provide a mathematical means for computing the total probability of a system. This work will provide a method to compute the conditional survivability to a given load, and the results indicate the top five loads that have the lowest conditional survivability during a mission in known configuration. The results show the computed conditional survivability of loads on an all electric navy ship. The loads conditional survivability is computed on high/medium voltage level and a low voltage level to show how loads are affected by failing components along their path.

To evaluate the strategy of reliability enhancement for an existing industrial power system , the Benefit-Cost ratio of all possible improvement scenarios have to be investigated . This thesis presents a quantitative and systematic method to solve the Benefit-Cost ratio of network restructure for reliability enhancement . This method can provide a simple and effective tool for planning reliability improvement in the industry power systems. Up to now , many methodologies have been developed to solve the service reliability for distribution power systems . In this thesis , the reliability indices of industrial power systems are calculated to evaluate the service quality . According to the result of reliability analysis and the corresponding cost of loss of load for each load bus , the annual power outage cost is derived for each scenario of system restructure. By integrating the power outage cost and the corresponding investment cost , the optimal reliability enhancement is determined by the best strategy with the Benefit-Cost ratio.

This paper is to investigate the impact of temperature sensitivity to the load profiles of power system by artificial neural networks (ANN). The load survey study is performed to derive the typical load patterns of the residential, commercial, and industrial customers respectively. By executing the training process of customer power consumption and temperature, the ANN model is created to derive the temperature sensitivity of power consumption for each customer class, which is then used to solve the impact of temperature rise to system power profiles. According to the system load composition and temperature sensitivity of power consumption by each customer class, the hourly increase of system power loading due to 1¢J temperature rise is solved. To study the temperature effect to the system reliability, the ¡§IEEE Reliability Test System¡¨ is selected as test system for power system reliability analysis. Based on the temperature sensitivity of power consumption for each customer class and load composition of each load bus. The power demand is updated with the temperature rise. The temperature sensitivity of commercial customers is very significant because of the high air conditioner loading. When the system load composition is most composed of commercial customers, the power demand are due to temperature rise will have very critical impact to system reliability. On the other hand, the tempearture rise will have less impact of reliability analysis for the system which serves high percentage of industrial customers. It is concluded that the research of temperature sensitivity on power consumption can provide important information for system reliability analysis. Better substation planning and system capacity expansion can be obtained to meet system reliability criterion by taking into account the temperature effect to system loading.

Instrument transformers are a crucial component of power system protection. They supply the protection system with scaled-down replicas of current and voltage signals present in a power network to the levels which are safe and practical to op- erate with. The conventional instrument transformers are based on electromagnetic coupling between the power network on the primary side and protective devices on the secondary. Due to such a design, instrument transformers insert distortions in the mentioned signal replicas. Protective devices may be sensitive to these distortions. The inuence of distortions may lead to disastrous misoperations of protective devices. To overcome this problem, a new instrument transformer design has been devised: optical sensing of currents and voltages. In the theory, novel instrument transform- ers promise a distortion-free replication of the primary signals. Since the mentioned novel design has not been widely used in practice so far, its superior performance needs to be evaluated. This poses a question: how can the new technology (design) be evaluated, and compared to the existing instrument transformer technology? The importance of this question lies in its consequence: is there a necessity to upgrade the protection system, i.e. to replace the conventional instrument transformers with the novel ones, which would be quite expensive and time-consuming? The posed question can be answered by comparing inuences of both the novel and the conventional instrument transformers on the protection system. At present, there is no systematic approach to this evaluation. Since the evaluation could lead to an improvement of the overall protection system, this thesis proposes a comprehensive and systematic methodology for the evaluation. The thesis also proposes a complete solution for the evaluation, in the form of a simulation environment. Finally, the thesis presents results of evaluation, along with their interpretation.

The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of a Shipboard Power System (SPS) are critical to the mission of a Navy ship, especially under battle conditions. When a weapon hits the ship in the event of battle, it can cause severe damage to the electrical systems on the ship. Researchers in the Power System Automation Laboratory (PSAL) at Texas A&M University have developed methods for performing reconfiguration of SPS before or after a weapon hit to reduce the damage to SPS. Reconfiguration operations change the topology of an SPS. When a system is stressed, these topology changes and induced dynamics of equipment due to reconfiguration might cause voltage instability, such as progressive voltage decreases or voltage oscillations. SPS stability thus should be assessed to ensure the stable operation of a system during reconfiguration. In this dissertation, time frames of SPS dynamics are presented. Stability problems during SPS reconfiguration are classified as long-term stability problems. Since angle stability is strongly maintained in SPS, voltage stability is studied in this dissertation for SPS stability during reconfiguration. A test SPS computer model, whose simulation results were used for stability studies, is presented in this dissertation. The model used a new generalized methodology for modeling and simulating ungrounded stiffly grounded power systems. This dissertation presents two new indices, a static voltage stability index (SVSILji) and a dynamic voltage stability index (DVSI), for assessing the voltage stability in static and dynamic analysis. SVSILji assesses system stability by all lines in SPS. DVSI detects local bifurcations in SPS. SVSILji was found to be a better index in comparison with some indices in the literature for a study on a two-bus power system. Also, results of DVSI were similar to the results of conventional bifurcation analysis software when applied to a small power system. Using SVSILji and DVSI on the test SPS computer model, three of four factors affection voltage stability during SPS reconfiguration were verified. During reconfiguration, SVSILji and DVSI are used together to assess SPS stability.

Power System Deregulation is a trend, and it takes place when the government, reduces unnecessary intervention and relaxes the control of capacity and price for the electricity market. It can establish the market mechanism and create rules that facilitate competition. The intention is to raise the market efficiency, introducing various types of production technologies and marketing management. As a result, it should create higher added value and ensure customer rights and interests to reach a win-win situation from both parties. In this thesis, a maximum profit will be pursued in the security market by the use of the Enhanced Immune Algorithm and Signal-to-Noise Ratio search under deregulated environment. Participation of generator companies and distribution companies are determined by ISO depending on their individual contributions to join the security market. The monetary influence is also discussed by using the social welfare. In this thesis, optimization will be considered when a line trip could lead to system congestion under security analysis. Tracing was used to find GenCos and DisCos¡¦s contributions to the transmission lines. ISO determines the participants to join the security market according to the tracing results. For the same fault type, various dispatch fees of the bids from participants will have various impacts on ISO¡¦s dispatch in terms of social welfare in the security market. Various fault types will also be discussed for the impacts of dispatch fees over ISO. This research could also provide a solid foundation for power system deregulation in the future. ISO can forecast the cost for a fault, and maximizes social welfare.

Thesis (Ph.D.)--Tennessee Technological University, 2009. / Title from title page screen (viewed on Feb. 9, 2010). Includes bibliographical references.

Thesis (Ph.D.) -- McGill University. / Written for the Dept. of Electrical Engineering. Typewritten MS. Bibliography: leaves 283-299.