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.

For operational and planning purposes it is important to observe, predict and monitor the traffic performance of congested urban road links and networks. This monitoring effort describes the traffic conditions in road networks using congestion performance measures. The objective of this research is to analyse and evaluate methods for measuring congestion and congestion performance measures for monitoring purposes. For this objective, a selection of the required aspects of the performance measures in the literature is considered. The aspects to be considered can be classified into two categories: A first group relates to the statistical aspects of these indicators, i.e. reliability. The second relates to their ability to capture the impacts of congestion, i.e .relevance. The reliability and relevance of the congestion performance measures are evaluated. A recommendation of the most suitable indicator is provided at the end of the study. / QC 20110912

Bakgrund: Det finns i nuläget inget svenskt self-efficacy instrument för barn och ungdomar med smärta. Den här undersökningen syftade till att översätta samt reliabilitets- och validitetstesta en engelskspråkig self-efficacy skala för barn och ungdomar med smärta. Metod: Urvalet bestod av 62 elever från tre olika klasser i Uppsala. Skalan översattes till svenska och ett frågeformulär utformades för att möjliggöra en utvärdering av test-retest reliabilitet samt kriterie- och ögonblicksvaliditet. Resultat: Värdena på viktad kappa för överensstämmelsen av två skattningar (S1 och S2) med self-efficacy instrumentet (SEIS) varierade mellan Kw= 0,37 -  Kw=0,75. Sambandet mellan Functional disability inventory (FDI) och SEIS beräknades med Spearmans rangkorrelation där rs = 0,364 (p<0,05). Ögonblicksvaliditeten för SEIS beskrevs som att den var lättförståelig, innehöll vardagliga aktiviteter men att vissa aktiviteter saknades. Konklusion: Slutsatsen av denna undersökning var att frågorna i SEIS bör omarbetas för att bli mer specifika och kunna användas. Det kan även utarbetas nya aktiviteter till instrumentet eftersom resultaten av undersökningen visade att vissa aktiviteter saknades. På grund av urvalets karaktär var resultaten troligtvis inte generaliserbara.

In many parts of the tropics irregular and erratic rainfall has great national economic as well as socio-economic effects. In Kenya, where a large part of the population live in rural areas and rainfed agriculture is the main livelihood, droughts and floods have farreaching impacts on communities. One form of mitigating the negative effects of drought is the implementation of simple, small-scale, low cost schemes called rainwater harvesting. This involves the capture, storing and redirection of rainfall, runoff, and groundwater. In Kenya, such schemes are being implemented in rural areas through different actors. Two Non-Governmental Organizations involved are the Kenya Rainwater Association and the German Agro Action that work in Tseikuru, a semi-arid area with water availability and sanitation issues. The main livelihood is agropastorialism and there is little experience with rainwater harvesting. Commonly, water is collected by digging shallow holes into dry river beds where groundwater tables are high. These areas are prone to contamination and could be situated many kilometres away, making water collection laborious. By implementing rainwater harvesting schemes water availability as well as water quality is expected to be improved. However, due to great rainfall variability and effects of climate change these schemes may fall short of their expectations. Also the potential change on water demand may affect communities’ response to prolonged dry spells. This study aims to examine whether the implemented rainwater harvesting schemes in rural Tseikuru are reliable in times of adverse rainfall and if increased water availability (and potentially also increased water demand) affects the communities’ vulnerability towards droughts. The study is based on interviews with local stakeholders and technicians during a Minor Field Study in Tseikuru, as well as statistical analysis on rainfall data over the area and literature studies. Results showed that rainwater harvesting schemes are generally successful in supplying readily available and safe water. However the rural population of Tseikuru have not completely abandoned their old habits of collecting water from dry riverbeds, choosing instead to treat the schemes as an alternative source to water, thereby avoiding dependency towards the schemes.

Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA’s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet the critical requirements associated with shipping, commercial and sport fishing vessel safety, and oil spill response. This dissertation also performs a detailed qualitative and quantitative assessment of the impact of various forcing functions on wave pre- dictions, and develops maps showing extreme variations in significant wave heights (SWHs). For instance, it is found that the SWH could vary by as much as 1 m in the northern CI region in the presence of currents (hence justifying the need for integration of the wave model with a circulation model). Such maps can be useful for several engineering operations, and could also serve as guidance tool as to what can be expected in certain regions. Aside from the system development, the issue of forecast reliability is also addressed for PWS region in the context of the associated uncertainty which confronts the manager of engineering operations or other planners. For this purpose, high-resolution 36-h daily forecasts of SWHs are compared with measurements from buoys and satellites for about a year. The results show that 70% of the peak SWHs in the range 5-8 m were predicted with an accuracy of 15% or less for a forecast lead time of 9 h. On average, results indicate 70% or greater likelihood of the prediction falling within a tolerance of ±(1*RMSE) for all lead times. This analysis could not be performed for CI due to lack of data sources.

Deregulated and competitive power market places utilities under high pressure to assure providing power with a satisfactory level of power continuity. This objective entails a high level of reliability which in turn demands a high financial budget for design, operation, and maintenance. Therefore, the need for utilities to balance these factors has been increasing to become the core of a utility's asset management activities. Maintenance is a key aspect of asset management. The main objective of maintenance is to extend the lifetime of equipment and/or reduce the probability of failure. Maintenance activities play an important role in improving system reliability by keeping the condition of a system's equipment within an acceptable level. Generally speaking, technical requirements and budget constraints are the most influential factors in assigning maintenance activities. The most cost-effective maintenance approach is the approach that can sustain a high level of reliability while maintenance cost is minimized. The transformer has a significant role in the power system due to its remarkable effect on the overall level of reliability in addition to its extensive investments in the power grid. Transformer management is comprised of identifying the appropriate type and frequency to maintain the transformer, and the appropriate time to replace the transformer in a cost-effective manner. The essential objective of this thesis is to introduce a novel framework for transformer management. An approach which links maintenance and replacement decisions is presented in this thesis. This approach proposes a methodical decision-making system to determine the optimal time to replace the transformer. Indeed, the proposed approach essentially investigates the cost-effectiveness of replacing the transformer both before and after the lifetime is extended by maintenance. To properly investigate the effect of maintenance, maintenance activities should first be scheduled effectively. Therefore, this approach introduces a maintenance strategy based on reliability-centered maintenance (RCM) concept and genetic algorithm (GA) to optimally schedule maintenance activities. Two replacement studies are conducted: with and without the effect of maintenance. A comparison between replacement studies is discussed in the proposed approach.

The primary function of a power system is to supply its customers with electrical energy as economically as possible and with acceptable reliability and quality. Generating capacity adequacy evaluation is the oldest and most extensively studied aspect of power system reliability assessment. A wide range of methods have been developed to perform this evaluation. Two computer programs were developed based on the analytical and simulation techniques and used as tools in this research work. A number of basic considerations in generating capacity adequacy evaluation are investigated. Generating unit residence time distributions and peaking load units are incorporated in the analysis.<p> Two commonly encountered misconceptions regarding the basic system reliability indices are examined by applying the two programs to two reliability test systems. Reliability index probability distributions can be used to supplement the information provided by the expected index values. The concept of creating distributions and the additional information that can be obtained is illustrated in this thesis. <p> Generating unit residence time distributions are generally categorized as being either exponential or non-exponential in form. The exponential distribution is utilized, however, in virtually all practical system studies. The impacts on the system reliability of non-exponential unit state residence time distributions are examined in this research. <p> Peaking load units and base load units have different operating characteristics. The functions of peaking load units vary with changes in the system operating conditions. This is examined in this research. <p>The conclusions and techniques presented in this thesis should prove valuable in power system planning and operation.

A power system is normally composed of a large number of generators and transmission lines that are connected through switching stations and substations. The quality and availability of power supply to the customer is highly dependent on the performance of the station equipment. Research shows that station related outages can have considerable impact on the composite system reliability. The individual station components, the station configurations and the terminal connection topologies are important factors in bulk system reliability evaluation. The major components in a station are circuit breakers, bus bars and transformers and these elements are periodically removed from service in order to conduct preventive maintenance. The removal of equipment for maintenance creates a change in the station configuration and a more vulnerable system. The failure of a related major component during a station preventive maintenance outage can result in a system disturbance and customer load loss. The bulk of the existing infrastructure of most electric power systems has been installed over the last 30 to 50 years. Aging failures of system components are a growing issue in modern electric power systems. Station related preventive maintenance outages and aging failures are important factors that affect the system reliability. This thesis examines the reliability implications of station related outages, including maintenance outages and aging outages in basic station configurations using two practical test systems. Models and techniques are created to incorporate these outages in composite system reliability evaluation. The techniques presented and the quantitative analyses illustrated in this thesis provide valuable information for a wide range of system planning, design, reinforcement and maintenance applications, including design and modification of power stations and station maintenance planning.

This thesis presents the development of a new method for incorporating station related outages in composite or bulk system reliability analysis. Station related failures can cause multiple component outages that can propagate to other parts of the network resulting in severe damages. In order to minimize the effects of station related outages on the composite system performance it is necessary for the designer to assess their effects. This task can be achieved by including station related outages in the composite system evaluation. Monte Carlo simulation is used in this research to assess composite system reliability. The new method described in this thesis is used to include station related outages in the reliability evaluation of two composite test systems. This new method is relatively simple and can be used to consider multiple component outages due to station related failures in composite system reliability evaluation. In this approach, the effects of station related outages are combined with the connected terminal failure parameters. Reliability studies conducted on the two composite test systems demonstrates that station failures significantly affect the system performance. The system reliability can be improved by selecting appropriate station configurations. This is illustrated by application to the two composite test systems.

The reliability of protection systems has emerged as an important topic because protection failures have critical influence on the reliability of power systems. The goal of this research is to develop novel approaches for modeling and analysis of the impact of protection system failures on power system reliability. It is shown that repairable and non-repairable assumptions make a remarkable difference in reliability modeling. A typical all-digital protection system architecture is modeled and numerically analyzed. If an all-digital protection system is indeed repairable but is modeled in a non-repairable manner for analysis, the calculated values of reliability indices could be grossly pessimistic. The smart grid is emerging with the penetration of information-age technologies and the development of the Special Protection System (SPS) will be greatly influenced. A conceptual all-digital SPS architecture is proposed for the future smart grid. Calculation of important reliability indices by the network reduction method and the Markov modeling method is illustrated in detail. Two different Markov models are proposed for reliability evaluation of the 2-out-of-3 voting gates structure in a generation rejection scheme. If the model with consideration of both detectable and undetectable logic gate failures is used as a benchmark, the simple model which only considers detectable failures will significantly overestimate the reliability of the 2-out-of-3 voting gates structure. The two types of protection failures, undesired-tripping mode and fail-to-operate mode are discussed. A complete Markov model for current-carrying components is established and its simplified form is then derived. The simplified model can appropriately describe the overall reliability situation of individual components under the circumstances of complex interactions between components due to protection failures. New concepts of the self-down state and the induced-down state are introduced and utilized to build up the composite unit model. Finally, a two-layer Markov model for power systems with protection failures is proposed. It can quantify the impact of protection failures on power system reliability. Using the developed methodology, we can see that the assumption of perfectly reliable protection can introduce errors in reliability evaluation of power systems.