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.

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.

Renewable energy policies, such as the Renewable Portfolio Standard, arising from increasing environmental concerns have set very ambitious targets for wind power penetration in electric power systems throughout the world. In many cases, the geographical locations with good wind resources are not close to the main load centers. It becomes extremely important to assess adequate transmission facility to deliver wind power to the power grid. <p>Wind is a highly variable energy source, and therefore, transmission system planning for wind delivery is very different from conventional transmission planning. Most electric power utilities use a deterministic n-1 criterion in transmission system planning. Deterministic methods cannot recognize the random nature of wind variation that dictates the power generated from wind power sources. This thesis presents probabilistic method to evaluate the contribution of a wind power delivery system to the overall system reliability. The effects of site-specific wind regime, system load, transmission line unavailability, and redundancy on system reliability were studied using a basic system model. The developed method responds to the various system parameters and is capable of assessing the actual system risks. <p>Modern power system aims to provide reliable as well as cost effective power supply to its consumers. Reliability benefits, environmental benefits and operating cost savings from wind power integration should be compared with the associated investment costs in order to determine optimum transmission facility for wind power delivery. This thesis presents the reliability/cost techniques for determining appropriate transmission line capacity to connect a wind farm to a power grid. The effect of transmission system cost, line length, wind regime, wind penetration and customer interruption cost on the optimum transmission line sizing were studied using a basic system model. The methodology and results presented in this thesis should be useful in transmission system planning for delivering wind power to a power system.

The evaluation of composite system reliability is extremely complex as it is necessary to include detailed modeling of both generation and transmission facilities and their auxiliary elements. The most significant quantitative indices in composite power system adequacy evaluation are those which relate to load curtailment. Many utilities have difficulty in interpreting the expected load curtailment indices as the existing models are based on adequacy analysis and in many cases do not consider realistic operating conditions in the system under study. This thesis presents a security based approach which alleviates this difficulty and provides the ability to evaluate the well-being of customer load points and the overall composite generation and transmission power system. Acceptable deterministic criteria are included in the probabilistic evaluation of the composite system reliability indices to monitor load point well-being. The degree of load point well-being is quantified in terms of the healthy and marginal state indices in addition to the traditional risk indices. The individual well-being indices of the different system load points are aggregated to produce system indices. This thesis presents new models and techniques to quantify the well-being of composite generation and, direct and alternating current transmission systems. Security constraints are basically the operating limits which must be satisfied for normal system operation. These constraints depend mainly on the purpose behind the study. The constraints which govern the practical operation of a power system are divided, in this thesis, into three sets namely, steady-state, voltage stability and transient stability constraints. The inclusion of an appropriate transient stability constraint will lead to a more accurate appraisal of the overall power system well-being. This thesis illustrates the utilization of a bisection method in the analytical evaluation of the critical clearing time which forms the basis of most existing stability assessments. The effect of employing high-speed-simultaneous or adaptive reclosing schemes is presented in this thesis. An effective and fast technique to incorporate voltage stability considerations in composite generation and transmission system reliability evaluation is also presented. The proposed technique can be easily incorporated in an existing composite power system reliability program using voltage stability constraints that are constructed for individual load points based on a relatively simple risk index. It is believed that the concepts, procedures and indices presented in this thesis will provide useful tools for power system designers, planners and operators and assist them to perform composite system well-being analysis in addition to traditional risk assessment.

Renewable energy policies, such as the Renewable Portfolio Standard, arising from increasing environmental concerns have set very ambitious targets for wind power penetration in electric power systems throughout the world. In many cases, the geographical locations with good wind resources are not close to the main load centers. It becomes extremely important to assess adequate transmission facility to deliver wind power to the power grid. <p>Wind is a highly variable energy source, and therefore, transmission system planning for wind delivery is very different from conventional transmission planning. Most electric power utilities use a deterministic n-1 criterion in transmission system planning. Deterministic methods cannot recognize the random nature of wind variation that dictates the power generated from wind power sources. This thesis presents probabilistic method to evaluate the contribution of a wind power delivery system to the overall system reliability. The effects of site-specific wind regime, system load, transmission line unavailability, and redundancy on system reliability were studied using a basic system model. The developed method responds to the various system parameters and is capable of assessing the actual system risks. <p>Modern power system aims to provide reliable as well as cost effective power supply to its consumers. Reliability benefits, environmental benefits and operating cost savings from wind power integration should be compared with the associated investment costs in order to determine optimum transmission facility for wind power delivery. This thesis presents the reliability/cost techniques for determining appropriate transmission line capacity to connect a wind farm to a power grid. The effect of transmission system cost, line length, wind regime, wind penetration and customer interruption cost on the optimum transmission line sizing were studied using a basic system model. The methodology and results presented in this thesis should be useful in transmission system planning for delivering wind power to a power system.

Renewal process has been often employed as a mathematical model of the failure and repair cycle of components in power system reliability assessment. This implies that after repair, the component is assumed to be restored to be in as good as new condition in terms of reliability perspective. However, some of the components may enter an aging stage as the system grows older. This thesis describes how aging characteristics of a system may impact the calculation of commonly used quantitative reliability indices such as Loss of Load Expectation (LOLE), Loss of Load Duration (LOLD), and Expected Energy Not Supplied (EENS). To build the history of working and failure states of a system, Stochastic Point Process modeling based on Sequential Monte Carlo simulation is introduced. Power Law Process is modeled as the failure rate function of aging components. Power system reliability analysis can be made at the generation capacity level where transmission constraints may be included. The simulation technique is applied to the Single Area IEEE Reliability Test System (RTS) and the results are evaluated and compared. The results show that reliability indices become increased as the age of the system grows.

In recent decades, there has been a dramatic increase in utilizing renewable energy resources by many power utilities around the world. The tendency toward using renewable energy resources is mainly due to the environmental concerns and fuel cost escalation associated with conventional fossil generation. Among renewable resources, wind energy is a proven source for power generation that positively contributes to global, social, and economic environments. Nowadays, wind energy is a mature, abundant, and emission-free power generation technology, and a significant percentage of electrical power demand is supplied by wind. However, the intermittent nature of wind generation introduces various challenges for both the operation and planning of power systems. One of the problems of increasing the use of wind generation can be seen from the reliability assessment point of view. Indeed, there is a recognized need to study the contribution of wind generation to overall system reliability and to ensure the adequacy of generation capacity. Wind power generation is different than conventional generation (i.e., fossil-based) in that wind power is variable and non-controllable, which can affect power system reliability. Therefore, modeling wind generation in a reliability assessment calls for reliable stochastic simulation techniques that can properly handle the uncertainty and precisely reflect the variable characteristics of the wind at a particular site. The research presented in this thesis focuses on developing a reliable and appropriate model for the reliability assessment of power system generation, including wind energy sources. This thesis uses the Monte Carlo Markov Chain (MCMC) technique due to its ability to produce synthetic wind power time series data that sufficiently consider the randomness of the wind along with keeping the statistical and temporal characteristics of the measured data. Thereafter, the synthetic wind power time series based on MCMC is coupled with a probabilistic sequential methodology for conventional generation in order to assess the overall adequacy of generating systems. The study presented in this thesis is applied to two test systems, designated the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (IEEE-RTS). A wide range of reliability indices are then calculated, including loss of load expectation (LOLE), loss of energy expectation (LOEE), loss of load frequency (LOLF), energy not supplied per interruption (ENSPI), demand not supplied per interruption (DNSPI), and expected duration per interruption (EDPI). To show the effectiveness of the proposed methodology, a further study is conducted to compare the obtained reliability indices using the MCMC model and the ARMA model, which is often used in reliability studies. The methodologies and the results illustrated in this thesis aim to provide useful information to planners or developers who endeavor to assess the reliability of power generation systems that contain wind generation.

The last two decades have brought about significant changes in the resource planning environment of electric power utilities throughout the world. The conventional generation technologies that have been the backbone of every electric utility i.e., coal, hydro, nuclear, oil and natural gas, are being re-examined to address environmental concerns and resource utilization. The research described in this thesis focuses on the adequacy and economic assessment of non-utility generation (NUG) and demand-side management (DSM) initiatives within a typical power system. The main objective was to examine and extend the ability of the contingency enumeration approach to evaluate the economic reliability benefits of incorporating NUG and DSM options separately or jointly in composite system adequacy assessment. Two test systems were employed in the evaluations. The studies undertaken in this thesis demonstrate the need for accurate load model representations which clearly reflect the mix of customer sectors at each bus.Chronological hourly load curves were developed for each load bus in the test systems recognizing the individual load profiles of the customers. The adequacy and economic implications of demand-side management initiatives in the test systems were examined at each load point in the composite generation and transmission configuration. This thesis illustrates the development of techniques by which system planners and operators can incorporate reliability cost/worth assessment power system applications. Focus is placed in the thesis on the utilization of reliability cost/worth concepts in integrated resource planning in the form of NUG additions and DSM initiatives. Methods for the joint implementation of NUG and DSM options in a composite power system are presented and examples from the studies conducted are used to illustrate the procedures. Studies are presented which illustrate the impacts of NUG additions and DSM initiatives on the test system planning reserve margins (PRM) and on the total societal cost of electrical energy. The total evaluated cost incorporates the explicit cost associated with customer failures but does not include the cost associated with DSM program implementation. The results of the studies conducted show that NUG facilities and DSM programs can have considerable reliability and economic impacts on electric power systems.