The reliability of supply in a bulk electricity system is directly related to the availability of the generation and transmission facilities. In a conventional vertically integrated system these facilities are usually owned and operated by a single company. In the new deregulated utility environment, these facilities could be owned and operated by a number of independent organizations. In this case, the overall system reliability is the responsibility of an independent system operator (ISO). The load point and system reliabilities are a function of the capacities and availabilities of the generation and transmission facilities and the system topology. This research examines the effect of equipment unavailability on the load point and system reliability of two test systems. The unavailabilities of specific generation and transmission facilities have major impacts on the load point and system reliabilities. These impacts are not uniform throughout the system and are highly dependent on the overall system topology and the operational philosophy of the system. Contingency evaluation is a basic planning and operating procedure and different contingencies can have quite different system and load point impacts. The risk levels associated with a given contingency cannot be estimated using deterministic criteria. The studies presented in this thesis estimate the risk associated with each case using probability techniques and rank the cases based on the predicted risk levels. This information should assist power system managers and planners to make objective decisions regarding reliability and cost. Composite system preventive maintenance scheduling is a challenging task. The functional separation of generation and transmission in the new market environment creates operational and scheduling problems related to maintenance. Maintenance schedules must be coordinated through an independent entity (ISO) to assure reliable and economical service. The methods adopted by an ISO to coordinate planned outages are normally based on traditional load flow and stability analysis and deterministic operating criteria. A new method designated as the maintenance coordination technique (MCT) is proposed in this thesis to coordinate maintenance scheduling. The research work illustrated in this thesis indicates that probabilistic criteria and techniques for composite power system analysis can be effectively utilized in both vertically integrated and deregulated utility systems. The conclusions and the techniques presented in this thesis should prove valuable to those responsible for system planning and maintenance coordination.

This paper investigates the purchasing power parity (PPP) hypothesis using panel data. Under PPP the real exchange rate is stationary around a constant mean. Recent panel data unit root tests are employed to test the PPP proposition where, under the conventional null hypothesis of a unit root, the real exchange rate is not stationary and PPP does not hold. In this case, as the time period t + n approaches infinity, its variance relative to period t will also approach infinity. The usual alternative in unit root tests is stationarity around a constant mean or a linear trend. The paper brings innovation into the PPP and panel unit root testing literature by allowing for possible nonlinear deterministic trends in the alternative hypothesis (as advanced by Cushman (2004)). If the null hypothesis is rejected in favour of the alternative of a non-linear trend, PPP still does not hold, but does at least revert back to a meaningful, stable long-run equilibrium. Given this non-linear trend, the variance of the real exchange rate as t + n approaches infinity, conditional on that trend, remains finite. Overall, evidence for stationarity in exchange rates is found in four out of six panels under consideration, including both support for stationary processes with no trend or a linear trend as well as for processes following a non-linear deterministic trend, in particular at time orders 5 and 6. The rejections are, in fact, most consistent at the nonlinear orders. Given nonlinear trends, PPP as usually defined does not hold, despite the rejection of unit roots. It is also found that stronger evidence for stable long-run equilibria in real exchange rates appears when the German Deutschmark is chosen as a base currency instead of the US Dollar. Finally, it appears that a very recent panel unit root test that takes account of cross-sectional dependencies delivers more consistent and sensible results.

The reliability of supply in a bulk electricity system is directly related to the availability of the generation and transmission facilities. In a conventional vertically integrated system these facilities are usually owned and operated by a single company. In the new deregulated utility environment, these facilities could be owned and operated by a number of independent organizations. In this case, the overall system reliability is the responsibility of an independent system operator (ISO). The load point and system reliabilities are a function of the capacities and availabilities of the generation and transmission facilities and the system topology. This research examines the effect of equipment unavailability on the load point and system reliability of two test systems. The unavailabilities of specific generation and transmission facilities have major impacts on the load point and system reliabilities. These impacts are not uniform throughout the system and are highly dependent on the overall system topology and the operational philosophy of the system. Contingency evaluation is a basic planning and operating procedure and different contingencies can have quite different system and load point impacts. The risk levels associated with a given contingency cannot be estimated using deterministic criteria. The studies presented in this thesis estimate the risk associated with each case using probability techniques and rank the cases based on the predicted risk levels. This information should assist power system managers and planners to make objective decisions regarding reliability and cost. Composite system preventive maintenance scheduling is a challenging task. The functional separation of generation and transmission in the new market environment creates operational and scheduling problems related to maintenance. Maintenance schedules must be coordinated through an independent entity (ISO) to assure reliable and economical service. The methods adopted by an ISO to coordinate planned outages are normally based on traditional load flow and stability analysis and deterministic operating criteria. A new method designated as the maintenance coordination technique (MCT) is proposed in this thesis to coordinate maintenance scheduling. The research work illustrated in this thesis indicates that probabilistic criteria and techniques for composite power system analysis can be effectively utilized in both vertically integrated and deregulated utility systems. The conclusions and the techniques presented in this thesis should prove valuable to those responsible for system planning and maintenance coordination.

Planning for Ontario’s future energy supply mix is a very challenging undertaking which requires consideration of various drivers and decision criteria. From the literature review conducted, no published work has been found addressing the multi-period energy planning problem with CO2 emission constraints and the option of carbon capture and storage (CCS). The objective of this project was to develop a novel multi-period mixed-integer non-linear programming (MINLP) model that is able to realize the optimal mix of energy supply sources which will meet current and future electricity demand, CO2 emission targets, and lower the overall cost of electricity. This model was implemented in GAMS (General Algebraic Modeling System). The model was formulated using an objective function that minimizes the net present value of the cost of electricity (COE) over a time horizon of 14 years. The formulation incorporates several time dependent parameters such as forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The model was applied to two case studies in order to examine the economical, structural, and environmental effects that would result if Ontario’s electricity sector was required to reduce its CO2 emissions to a specific limit. The first case study examined a base case scenario in which no CO2 limits were imposed. The second case study examined a scenario in which Ontario’s electricity sector must comply with CO2 emission limits similar to the Kyoto target of 6% below 1990 levels. The results indicate that in order to meet the CO2 targets of 6% below 1990 levels, Nanticoke, Atikokan, and Thunder Bay coal-fired power plants must be fuel-switched, and Lambton coal-fired power plant must be retrofitted with a CCS system. Furthermore, a total CO2 reduction of approximately 32% was achieved when compared to the base case. The total cost associated with reducing the CO2 emissions to 6% below 1990 levels, per ton of CO2, was $48.79 / ton CO2 reduced. The total expenditure for Case Study II (CO2 limit of 6% below 1990 levels) was approximately 10.1% higher than for the base case. This model offers many potential benefits to Ontario’s energy sector. In addition to providing an optimal solution for meeting future electricity demand, it can help Ontario meet its emissions targets while minimizing the overall cost of electricity. Furthermore, although this project was aimed at Ontario’s future energy supply mix, it could also be readily applied to other regions or even countries as a whole.

Planning for Ontario’s future energy supply mix is a very challenging undertaking which requires consideration of various drivers and decision criteria. From the literature review conducted, no published work has been found addressing the multi-period energy planning problem with CO2 emission constraints and the option of carbon capture and storage (CCS). The objective of this project was to develop a novel multi-period mixed-integer non-linear programming (MINLP) model that is able to realize the optimal mix of energy supply sources which will meet current and future electricity demand, CO2 emission targets, and lower the overall cost of electricity. This model was implemented in GAMS (General Algebraic Modeling System). The model was formulated using an objective function that minimizes the net present value of the cost of electricity (COE) over a time horizon of 14 years. The formulation incorporates several time dependent parameters such as forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The model was applied to two case studies in order to examine the economical, structural, and environmental effects that would result if Ontario’s electricity sector was required to reduce its CO2 emissions to a specific limit. The first case study examined a base case scenario in which no CO2 limits were imposed. The second case study examined a scenario in which Ontario’s electricity sector must comply with CO2 emission limits similar to the Kyoto target of 6% below 1990 levels. The results indicate that in order to meet the CO2 targets of 6% below 1990 levels, Nanticoke, Atikokan, and Thunder Bay coal-fired power plants must be fuel-switched, and Lambton coal-fired power plant must be retrofitted with a CCS system. Furthermore, a total CO2 reduction of approximately 32% was achieved when compared to the base case. The total cost associated with reducing the CO2 emissions to 6% below 1990 levels, per ton of CO2, was $48.79 / ton CO2 reduced. The total expenditure for Case Study II (CO2 limit of 6% below 1990 levels) was approximately 10.1% higher than for the base case. This model offers many potential benefits to Ontario’s energy sector. In addition to providing an optimal solution for meeting future electricity demand, it can help Ontario meet its emissions targets while minimizing the overall cost of electricity. Furthermore, although this project was aimed at Ontario’s future energy supply mix, it could also be readily applied to other regions or even countries as a whole.

This paper investigates the purchasing power parity (PPP) hypothesis using panel data. Under PPP the real exchange rate is stationary around a constant mean. Recent panel data unit root tests are employed to test the PPP proposition where, under the conventional null hypothesis of a unit root, the real exchange rate is not stationary and PPP does not hold. In this case, as the time period t + n approaches infinity, its variance relative to period t will also approach infinity. The usual alternative in unit root tests is stationarity around a constant mean or a linear trend. The paper brings innovation into the PPP and panel unit root testing literature by allowing for possible nonlinear deterministic trends in the alternative hypothesis (as advanced by Cushman (2004)). If the null hypothesis is rejected in favour of the alternative of a non-linear trend, PPP still does not hold, but does at least revert back to a meaningful, stable long-run equilibrium. Given this non-linear trend, the variance of the real exchange rate as t + n approaches infinity, conditional on that trend, remains finite. Overall, evidence for stationarity in exchange rates is found in four out of six panels under consideration, including both support for stationary processes with no trend or a linear trend as well as for processes following a non-linear deterministic trend, in particular at time orders 5 and 6. The rejections are, in fact, most consistent at the nonlinear orders. Given nonlinear trends, PPP as usually defined does not hold, despite the rejection of unit roots. It is also found that stronger evidence for stable long-run equilibria in real exchange rates appears when the German Deutschmark is chosen as a base currency instead of the US Dollar. Finally, it appears that a very recent panel unit root test that takes account of cross-sectional dependencies delivers more consistent and sensible results.

The use of statistics has been common practice within the petroleum industry for over a decade. With such a mature subject that includes specialized software and numerous articles, the challenge of this project was to introduce a duplicable method to perform deterministic regression while confirming the mathematical and actual validation of the resulting model. A five-step procedure was introduced using Statistical Analysis Software (SAS) for necessary computations to obtain a model that describes an event by analyzing the environmental variables. Since SAS may not be readily available, the code to perform the five-step methodology in R has been provided. The deterministic five-step procedure methodology may be applied to new fields with a limited amount of data. As an example case, 17 wells drilled in north central Texas were used to illustrate how to apply the methodology to obtain a deterministic model. The objective was to predict the number of days required to drill a well using environmental conditions and technical variables. Ideally, the predicted number of days would be within +/- 10% of the observed time of the drilled wells. The database created contained 58 observations from 17 wells with the descriptive variables, technical limit (referred to as estimated days), depth, bottomhole temperature (BHT), inclination (inc), mud weight (MW), fracture pressure (FP), pore pressure (PP), and the average, maximum, and minimum difference between fracture pressure minus mud weight and mud weight minus pore pressure. Step 1 created a database. Step 2 performed initial statistical regression on the original dataset. Step 3 ensured that the models were valid by performing univariate analysis. Step 4 history matched the models-response to actual observed data. Step 5 repeated the procedure until the best model had been found. Four main regression techniques were used: stepwise regression, forward selection, backward elimination, and least squares regression. Using these four regression techniques and best engineering judgment, a model was found that improved time prediction accuracy, but did not constantly result in values that were +/- 10% of the observed times. The five-step methodology to determine a model using deterministic statistics has applications in many different areas within the petroleum field. Unlike examples found in literature, emphasis has been given to the validation of the model by analysis of the model error. By focusing on the five-step procedure, the methodology may be applied within different software programs, allowing for greater usage. These two key parameters allow companies to obtain their time prediction models without the need to outsource the work and test the certainty of any chosen model.

In the automotive industry uniaxial vibration testing is a common method used to predict the lifetime of components. In reality truck components work under multiaxial loads meaning that the excitation is multiaxial. A common method to account for the multiaxial effect is to apply a safety margin to the uniaxial test results. The aim of this work is to find a safety margin between the uniaxial and multiaxial testing by means of virtual vibration testing and statistical methods. Additionally to the safety margin the effect of the fixture’s stiffness on the resulting stress in components has been also investigated.

The deterministic microasperities play a vital role in reducing the coefficient of friction and wear of thrust surfaces and improve the tribological properties of the surfaces. Deterministic microasperities have a specific pattern in terms of size, shape and spacing. These specified geometries are controllable and repeatable. The microasperities are micron scaled asperities and cavities on a surface that form the surface roughness. The present thesis shows the detailed process to fabricate the deterministic microasperities on thrust surfaces, i.e. stainless substrate, using micro-fabrication processes such as lapping and ultra-violet photolithography in combination with an electroplating (nickel) process. A Novel alignment technique is used to align the photomask with the substrate to get repeatable and aligned patterns on the thrust surface. Deterministic microasperities are characterized by using precision instruments such as an Optical profilometer, Scanning Electron Microscope (SEM) and Optical microscope to study the various surface parameters such as Average roughness (Ra), Root mean square value (rms) and Peak value (PV) of the thrust surface.

In order to achieve enhanced and cost-effective performance of engineering components, Surface Engineering embraces traditional and innovative surface technologies which modify the surface properties of metallic and non-metallic engineering components for specific and sometime unique engineering purposes. The surface roughness of an engineered surface may be classified as: the random surface roughness which is a product of surface finishing and the deterministic surface roughness which is engineered to increase the lubrication characteristics of the hydro dynamically lubricated thrust ring. The effect of stochastic/random roughness can not be ignored when the roughness is of the same amplitude as that of fluid film thickness. Average flow model derived in terms of flow factors which are functions of the roughness characteristics is used to study the random surface roughness effects on hydrodynamic lubrication of deterministic asperity. In addition, the effect of boundary conditions on flow factors is studied by calculating the pressure and shear flow factor using two different new boundary conditions. The results are obtained for random surface roughness having a Gaussian distribution of roughness heights.