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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.

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.

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.

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.

Renewable sources of energy such as wind turbine generators and solar panels have attracted much attention because they are environmentally friendly, do not consume fossil fuels, and can enhance a nation’s energy security. As a result, recently more significant amounts of renewable energy are being integrated into conventional power grids. The research reported in this dissertation primarily investigates the reliability-constrained planning and operations of electric power systems including renewable sources of energy by accounting for uncertainty. The major sources of uncertainty in these systems include equipment failures and stochastic variations in time-dependent power sources. Different energy sources have different characteristics in terms of cost, power dispatchability, and environmental impact. For instance, the intermittency of some renewable energy sources may compromise the system reliability when they are integrated into the traditional power grids. Thus, multiple issues should be considered in grid interconnection, including system cost, reliability, and pollutant emissions. Furthermore, due to the high complexity and high nonlinearity of such non-traditional power systems with multiple energy sources, computational intelligence based optimization methods are used to resolve several important and challenging problems in their operations and planning. Meanwhile, probabilistic methods are used for reliability evaluation in these reliability-constrained planning and design. The major problems studied in the dissertation include reliability evaluation of power systems with time-dependent energy sources, multi-objective design of hybrid generation systems, risk and cost tradeoff in economic dispatch with wind power penetration, optimal placement of distributed generators and protective devices in power distribution systems, and reliability-based estimation of wind power capacity credit. These case studies have demonstrated the viability and effectiveness of computational intelligence based methods in dealing with a set of important problems in this research arena.

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.

According to the European Network of Transmission System Operators for Electricity (ENTSO-E) there is a need to invest 104 billion Euros to either refurbish or construct overhead lines (OHLs). This massive enterprise is mainly driven by the need to accommodate the proliferation of renewable energy generation projects across Europe in response to the European Commission’s directive to supply 20% of its energy from renewables by the year 2020. However, 30% of transmission projects experience delays; and moreover, it has been found that if the existing grid capacity is to be increased by about 1.3% it would facilitate about 3% of renewables. Therefore, attention towards the thermal uprating of existing networks has attracted research interest. In this thesis, the main contribution to this research is a probabilistic and holistically integrated system and OHL plant reliability centred thermal uprating evaluation methodology. This methodology is designed to aid the facilitation of the thermal uprating’s of existing lines, through a variety of multistage and multifaceted risk based decisions. These multifaceted aspects are subject to the conflicting views to thermal uprating which stem from various utility personnel; which further stem from their constricted views on system reliability. For example, plant maintainers may resist thermal uprating because it may require the need to increase maintenance works on right-of-ways, or because they may need to prevent conductors from ageing sooner than initially projected. However, restricting thermal uprating for these reasons will limit the capability of the system to facilitate renewables, and this will negatively affect overall system reliability. Therefore, the presented methodology aids to facilitate highly efficient interdependent decision making amongst plant designers and maintainers, and system planners and operators, to effectively manage thermal uprating risks in consideration to the overall utility’s goals. This thesis implements a variety of studies to enlighten utility personnel of the possible economic benefits and risk mitigation practices that could be realised through thermal uprating. To present robustly conclusive and compelling results, these studies research the value of thermal uprating from three possible time scales: long-, medium- and short-term time domains. Consequently, planners (through this methodology) will for the first time ascertain the true value of (1) uprating existing conductors by accepting the subsequent acceleration of their ageing, (2) selecting the optimal reconductoring technology from a suite of candidate (conventional and novel) conductor technologies, (3) the retensioning policy to implement (at a particular stage of a project) in order to maintain reliability, and (4) novel real-time OHL ageing management tools for power system operators to use reliably.

<p>Ova studija ima za cilj da prikaže mogućnost generisanja modela obezbeđenja pouzdanosti složenih postrojenja u termoelektranama.</p> / <p>The goal of this study is to show the possibility of generating reliability ensuring models of complex facilities in thermal power plants.</p> / <p>The goal of this study is to show the possibility of generating reliability<br />ensuring models of complex facilities in thermal power plants.</p>