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.

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The focus of this thesis is to develop a generic approach for solving reliability design optimisation problems which could be applicable to a diverse range of real engineering systems. The basic problem in optimal reliability design of a system is to explore the means of improving the system reliability within the bounds of available resources. Improving the reliability reduces the likelihood of system failure. The consequences of system failure can vary from minor inconvenience and cost to significant economic loss and personal injury. However any improvements made to the system are subject to the availability of resources, which are very often limited. The objective of the design optimisation problem analysed in this thesis is to minimise system unavailability (or unreliability if an unrepairable system is analysed) through the manipulation and assessment of all possible design alterations available, which are subject to constraints on resources and/or system performance requirements. This thesis describes a genetic algorithm-based technique developed to solve the optimisation problem. Since an explicit mathematical form can not be formulated to evaluate the objective function, the system unavailability (unreliability) is assessed using the fault tree method. Central to the optimisation algorithm are newly developed fault tree modification patterns (FTMPs). They are employed here to construct one fault tree representing all possible designs investigated, from the initial system design specified along with the design choices. This is then altered to represent the individual designs in question during the optimisation process. Failure probabilities for specified design cases are quantified by employing Binary Decision Diagrams (BDDs). A computer programme has been developed to automate the application of the optimisation approach to standard engineering safety systems. Its practicality is demonstrated through the consideration of two systems of increasing complexity; first a High Integrity Protection System (HIPS) followed by a Fire Water Deluge System (FWDS). The technique is then further-developed and applied to solve problems of multi-phased mission systems. Two systems are considered; first an unmanned aerial vehicle (UAV) and secondly a military vessel. The final part of this thesis focuses on continuing the development process by adapting the method to solve design optimisation problems for multiple multi-phased mission systems. Its application is demonstrated by considering an advanced UAV system involving multiple multi-phased flight missions. The applications discussed prove that the technique progressively developed in this thesis enables design optimisation problems to be solved for systems with different levels of complexity. A key contribution of this thesis is the development of a novel generic optimisation technique, embedding newly developed FTMPs, which is capable of optimising the reliability design for potentially any engineering system. Another key and novel contribution of this work is the capability to analyse and provide optimal design solutions for multiple multi-phase mission systems. Keywords: optimisation, system design, multi-phased mission system, reliability, genetic algorithm, fault tree, binary decision diagram

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.

With increased load demands from the customers, substation congestion problems have become inevitable to the utility companies. Instead of expanding related system installations to alleviate the short-term overloads on the facilities, feasibilities of integrating distributed generator (DG) units to defer the possible congestions are of much concern. This thesis presents an optimal location and reliability analyzing scheme for distribution system integrated with DG units, and provides the systematic guidance to utility companies for related operations. The methodology focuses on the substation capacity constraints and provides the optimal DG locations that can alleviate the congestion problem with highest reliability indices. The proposed analyzing scheme can supply valuable assistance to the utility companies and small independent power producers (IPP) for determining the installations and integrations of DG units to defer possible emerging substation expansions.

As wind exploitation gains prominence in the power industry, the extensive use of this intermittent source of power may heavily rely on our ability to select the best combination of wind farming sites that yields maximal reliability of power systems at minimal cost. This research proposes a general method to minimize the wind park global power output variance by optimally distributing a predetermined number of wind turbines over a preselected number of potential wind farming sites for which the wind patterns are statistically known. The objective is to demonstrate the benefits of diversification for the reliability of wind-sustained systems through the search for steadier overall power outputs. Three years of wind data from the recent NREL/3TIER study in the western US provides the statistics for evaluating each site for their mean power output, variance and correlation with each other so that the best allocations can be determined. Some traditional reliability indices such as the LOLP are computed by using sequential Monte Carlo simulations to emulate the behavior of a power system uniquely composed of wind turbines and a load modeled from the 1996 IEEE RTS. It is shown that configurations featuring minimal global power output variances generally prove the most reliable for moderate load cases, provided the sites are not significantly correlated with the modeled load. Under these conditions, the choice of uncorrelated/negatively correlated sites is favored. The correlations between the optimized global wind power outputs and the modeled load are studied as well.