Society relies more and more on a continuous supply of electricity. However, while underinvestments in reliability lead to an unacceptable number of power interruptions, overinvestments result in too high costs for society. To give incentives for a socioeconomically optimal level of reliability, quality regulations have been adopted in many European countries. These quality regulations imply new financial risks for the distribution system operator (DSO) since poor reliability can reduce the allowed revenue for the DSO and compensation may have to be paid to affected customers.This thesis develops a method for evaluating the incentives for reliability investments implied by different quality regulation designs. The method can be used to investigate whether socioeconomically beneficial projects are also beneficial for a profit-maximizing DSO subject to a particular quality regulation design. To investigate which reinvestment projects are preferable for society and a DSO, risk-based methods are developed. With these methods, the probability of power interruptions and the consequences of these can be simulated. The consequences of interruptions for the DSO will to a large extent depend on the quality regulation. The consequences for the customers, and hence also society, will depend on factors such as the interruption duration and time of occurrence. The proposed risk-based methods consider extreme outage events in the risk assessments by incorporating the impact of severe weather, estimating the full probability distribution of the total reliability cost, and formulating a risk-averse strategy. Results from case studies performed show that quality regulation design has a significant impact on reinvestment project profitability for a DSO. In order to adequately capture the financial risk that the DSO is exposed to, detailed risk-based methods, such as the ones developed in this thesis, are needed. Furthermore, when making investment decisions, a risk-averse strategy may clarify the benefits or drawbacks of a project that are hard to discover by looking only at the expected net present value. / QC 20110530

Over the past decades, the concepts and methods for reliability assessment have evolved from analysing the ability of individual components to operate without faults and as intended during their lifetime, into the comprehensive approaches for evaluating various engineering strategies for system planning, operation and maintenance studies. The conventional reliability assessment procedures now receive different perspectives in different engineering applications and this thesis aims to improve existing approaches by incorporating in the analysis: a) a more detailed and accurate models of LV and MV networks and their reliability equivalents, which are important for the analysis of transmission and sub-transmission networks, b) the variations in characteristics and parameters of LV and MV networks in different areas, specified as “generic” UK/Scottish highly-urban, urban, sub-urban and rural network models, c) the relevant requirements for network reliability performance imposed by Regulators on network operators, d) the actual aggregate load profiles of supplied customers and their correlation with typical daily variations of fault probabilities and repair times of considered network components, and e) some of the expected “smart grid” functionalities, e.g., increased use of network automation and reconfiguration schemes, as well as the higher penetration levels of distributed generation/storage resources. The conventional reliability assessment procedures typically do not include, or only partially include the abovementioned important factors and aspects in the analysis. In order to demonstrate their importance, the analysis presented in the thesis implements both analytical and probabilistic reliability assessment methods in a number of scenarios and study cases with improved and more detailed “generic” LV and MV network models and their reliability equivalents. Their impact on network reliability performance is analysed and quantified in terms of the frequency and duration of long and short supply interruptions (SAIFI and SAIDI), as well as energy not supplied (ENS). This thesis addresses another important aspect of conventional approaches, which often, if not always, provide separate indicators for the assessment of system-based reliability performance and for the assessment of customer-based reliability performance. The presented analysis attempts to more closely relate system reliability performance indicators, which generally correspond to a fictitious “average customer”, to the actual “best-served” and “worst-served” customers in the considered networks. Here, it is shown that a more complex metric than individual reliability indicators should be used for the analysis, as there are different best-served and worst-served customers in terms of the frequency and duration of supply interruptions, as well as amounts of not supplied energy. Finally, the analysis in the thesis considers some aspects of the anticipated transformation of existing networks into the future smart grids, which effectively require to re-evaluate the ways in which network reliability is approached at both planning and operational stages. Smart grids will feature significantly higher penetration levels of variable renewable-based distributed generation technologies (with or without energy storage), as well as the increased operational flexibility, automation and remote control facilities. In this context, the thesis evaluates some of the considered smart grid capabilities and functionalities, showing that improved system reliability performance might result in a deterioration of power quality performance. This is illustrated through the analysis of applied automation, reconfiguration and automatic reclosing/remote switching schemes, which are shown to reduce frequency and duration of long supply interruptions, but will ultimately result in more frequent and/or longer voltage sags and short interruptions. Similarly, distributed generation/storage resources might have strong positive impact on system reliability performance through the reduced power flows in local networks and provision of alternative supply points, even allowing for a fully independent off-grid operation in microgrids, but this may also result in the reduced power quality levels within the microgrids, or elsewhere in the network, e.g. due to a higher number of switching transfers and transients.

abstract: Corrective transmission topology control schemes are an essential part of grid operations and are used to improve the reliability of the grid as well as the operational efficiency. However, topology control schemes are frequently established based on the operator's past knowledge of the system as well as other ad-hoc methods. This research presents robust corrective topology control, which is a transmission switching methodology used for system reliability as well as to facilitate renewable integration. This research presents three topology control (corrective transmission switching) methodologies along with the detailed formulation of robust corrective switching. The robust model can be solved off-line to suggest switching actions that can be used in a dynamic security assessment tool in real-time. The proposed robust topology control algorithm can also generate multiple corrective switching actions for a particular contingency. The solution obtained from the robust topology control algorithm is guaranteed to be feasible for the entire uncertainty set, i.e., a range of system operating states. Furthermore, this research extends the benefits of robust corrective topology control to renewable resource integration. In recent years, the penetration of renewable resources in electrical power systems has increased. These renewable resources add more complexities to power system operations, due to their intermittent nature. This research presents robust corrective topology control as a congestion management tool to manage power flows and the associated renewable uncertainty. The proposed day-ahead method determines the maximum uncertainty in renewable resources in terms of do-not-exceed limits combined with corrective topology control. The results obtained from the topology control algorithm are tested for system stability and AC feasibility. The scalability of do-not-exceed limits problem, from a smaller test case to a realistic test case, is also addressed in this research. The do-not-exceed limit problem is simplified by proposing a zonal do-not-exceed limit formulation over a detailed nodal do-not-exceed limit formulation. The simulation results show that the zonal approach is capable of addressing scalability of the do-not-exceed limit problem for a realistic test case. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

abstract: The uncertainty and variability associated with stochastic resources, such as wind and solar, coupled with the stringent reliability requirements and constantly changing system operating conditions (e.g., generator and transmission outages) introduce new challenges to power systems. Contemporary approaches to model reserve requirements within the conventional security-constrained unit commitment (SCUC) models may not be satisfactory with increasing penetration levels of stochastic resources; such conventional models pro-cure reserves in accordance with deterministic criteria whose deliverability, in the event of an uncertain realization, is not guaranteed. Smart, well-designed reserve policies are needed to assist system operators in maintaining reliability at least cost. Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements. This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

abstract: Photovoltaic (PV) power generation has the potential to cause a significant impact on power system reliability since its total installed capacity is projected to increase at a significant rate. PV generation can be described as an intermittent and variable resource because its production is influenced by ever-changing environmental conditions. The study in this dissertation focuses on the influence of PV generation on trans-mission system reliability. This is a concern because PV generation output is integrated into present power systems at various voltage levels and may significantly affect the power flow patterns. This dissertation applies a probabilistic power flow (PPF) algorithm to evaluate the influence of PV generation uncertainty on transmission system perfor-mance. A cumulant-based PPF algorithm suitable for large systems is used. Correlation among adjacent PV resources is considered. Three types of approximation expansions based on cumulants namely Gram-Charlier expansion, Edgeworth expansion and Cor-nish-Fisher expansion are compared, and their properties, advantages and deficiencies are discussed. Additionally, a novel probabilistic model of PV generation is developed to obtain the probability density function (PDF) of the PV generation production based on environmental conditions. Besides, this dissertation proposes a novel PPF algorithm considering the conven-tional generation dispatching operation to balance PV generation uncertainties. It is pru-dent to include generation dispatch in the PPF algorithm since the dispatching strategy compensates for PV generation injections and influences the uncertainty results. Fur-thermore, this dissertation also proposes a probabilistic optimal power dispatching strat-egy which considers uncertainty problems in the economic dispatch and optimizes the expected value of the total cost with the overload probability as a constraint. The proposed PPF algorithm with the three expansions is compared with Monte Carlo simulations (MCS) with results for a 2497-bus representation of the Arizona area of the Western Electricity Coordinating Council (WECC) system. The PDFs of the bus voltages, line flows and slack bus production are computed, and are used to identify the confidence interval, the over limit probability and the expected over limit time of the ob-jective variables. The proposed algorithm is of significant relevance to the operating and planning studies of the transmission systems with PV generation installed. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

The global mean surface temperature rise was observed in the past century and proved the warming of the earth climate system. Global warming is believed to continue into the next decades due to unprecedented increases in greenhouse gas emissions. As a consequence of global warming, extreme weather scenarios are also expected to occur more frequently. In such a context, it is of vital importance to assess the impacts of climate change on the operational performance of power systems. This thesis investigates the impacts of climate change on the operational performance of power systems. The future climate is simulated based on emission scenarios and is then used as an input to the thermal models of power system components to assess their ratings and ageing, and further the reliability of the system. This research contributes to a number of areas in power system research. In the literature review, the risks that climate change may cause to power systems are identified. The models used for the simulation of future climate are firstly introduced. The weather variables that can be simulated from the models include air temperature, solar radiation, wind speed and direction, soil moisture and soil temperature. Among the models, the one for soil temperature is originally developed in this thesis. Following this, the component thermal models of overhead line, cable and transformer, from different standards are compared and selected. After that, the sensitivity of component ratings to individual weather variables is investigated, as a preliminary study for the later research in this thesis. Then, the impacts of climate change on component ratings (including both static and dynamic rating) are comprehensively and probabilistically assessed. The assessment results indicate the reduction of component ratings due to climate change. The impacts of climate change on system reliability is further examined on the IEEE Reliability Test System. Results demonstrate and quantify the reduction of both component ratings and system reliability, and prove that the dynamic rating can be used to mitigate the reduction. Finally, the preliminary exploration of transformer ageing is carried out and shows an increased ageing rate due to air temperature rises.

System testing is very time-consuming and costly, especially for complex high-cost and high-reliability systems. For this reason, the number of failures needed for the developmental phase of system testing should be relatively small in general. To assess the reliability growth of a repairable system, the generalized confidence interval and the modified signed log-likelihood ratio test for the scale parameter of the power-law process are studied concerning incomplete failure data. Specifically, some recorded failure times in the early developmental phase of system testing cannot be observed; this circumstance is essential to establish a warranty period or determine a maintenance phase for repairable systems. For the proposed generalized confidence interval, we have found that this method is not biased estimates which can be seen from the coverage probabilities obtained from this method being close to the nominal level 0.95 for all levels of γ and β. When the performance of the proposed method and the existing method are compared and validated regarding average widths, the simulation results show that the proposed method is superior to another method due to shorter average widths when the predetermined number of failures is small. For the proposed modified signed log-likelihood ratio test, we have found that this test performs well in controlling type I errors for complete failure data, and it has desirable powers for all parameters configurations even for the small number of failures. For incomplete failure data, the proposed modified signed log-likelihood ratio test is preferable to the signed log-likelihood ratio test in most situations in terms of controlling type I errors. Moreover, the proposed test also performs well when the missing ratio is up to 30% and n > 10. In terms of empirical powers, the proposed modified signed log-likelihood ratio test is superior to another test for most situations. In conclusion, it is quite clear that the proposed methods, the generalized confidence interval, and the modified signed log-likelihood ratio test, are practically useful to save business costs and time during the developmental phase of system testing since the only small number of failures is required to test systems, and it yields precise results.

As human society develops, there is an increasing demand for electricity. However, the reserves of fossil fuels on earth are limited and may run out in the foreseeable future. Therefore, the possibility of replacing traditional fossil fuels with renewable energy sources is widely being investigated to resolve the world-faced energy shortage and environmental problems. The first method is to utilize more renewable energy such as wind and solar power and increase the percentage of distributed generation. Another method is to popularize electric vehicles due to their environmental-friendly and energy-saving characteristics. However, the integration of distributed generation and electric vehicles may greatly influence the operation and planning of power systems in several ways. This might result in deterioration of power system reliability. Since the society development highly depends on a safe and reliable power grid, it is essential to ensure high reliability of power systems when integrated with renewable energy resources. This master thesis aims to investigate the reliability performance of power distribution systems after integrating distributed generation and electric vehicles. First, the probabilistic model of distributed generation and electric vehicles for various scenarios are simulated. After that, a set of reliability analyses based on a standard reliability test system are carried out, in which a sequential Monte-Carlo simulation method is adopted to estimate average reliability indices. The overall conclusion is that the integration of distributed generation enhances power system reliability performance through supplying power to nearby customers in island mode. For electric vehicles, the proper regulation of charging behavior can help reduce the deterioration of power system reliability to the most extent, and the Vehicle-to-Grid mode can also improve system reliability. Furthermore, the electric bus dynamic charging mode has no additional harm to power system reliability performance than non-dynamic charging and has a promising prospect. / När det mänskliga samhället utvecklas finns det en ökande efterfrågan på el. Reserverna av fossila bränslen på jorden är dock begränsade och kan ta slut inom en överskådlig framtid. Därför undersöks möjligheten att ersätta traditionella fossila bränslen med förnybara energikällor för att lösa den världsomspända energibristen och miljöproblemen. Den första metoden är att använda mer förnybar energi såsom vind- och solenergi och öka andelen distribuerad produktion. En annan metod är att popularisera elfordon på grund av deras miljövänliga och energibesparande egenskaper. Integrationen av distribuerad produktion och elfordon kan dock påverka sätt och planering av kraftsystem i hög grad på flera sätt. Detta kan leda till försämring av elsystemets tillförlitlighet. Eftersom samhällsutvecklingen i hög grad beror på ett säkert och tillförlitligt kraftnät är det viktigt att säkerställa hög tillförlitlighet hos kraftsystem när de är integrerade med förnybara energikällor. Syftet med detta examensarbete är att undersöka tillförlitligheten hos kraftdistributionssystemet efter integrering av distribuerad generation och elfordon. För det första konstrueras den probabilistiska modellen för distribuerad generation och elfordon inklusive olika scenarier. Därefter genomförs en uppsättning tillförlitlighetsanalys baserad på RBTS buss 6-system, där sekventiell Monte-Carlo-simuleringsmetod antas för att uppskatta genomsnittliga återansvarsindex. Den övergripande slutsatsen är att integreringen av distribuerad produktion förbättrar systemets tillförlitlighet genom att leverera kraft till närliggande kunder på öns plats. För elektriska fordon kan korrekt reglering av laddningsbeteendet bidra till att minska försämringen av elsystemets tillförlitlighet i största möjliga utsträckning, och läget Fordon till nät kan även förbättra systemets tillförlitlighet. Dessutom har det elektriska bussens dynamiska laddningsläge ingen ytterligare skada på kraftsystemets tillförlitlighet och har ett lovande perspektiv.

Early in the process of developing or upgrading new weapon systems, Department of Defense (DoD) system and technology developers are faced with decisions regarding which technologies are appropriate for inclusion into the conceptual design. To reduce risk and improve decision making, system and technology developers need a capability to assess the impact of technology reliability on the attributable Operating and Support (O&S) cost of the system. Early understanding of the reliability implications of potential technologies on system O&S cost will help make better informed decisions early in the system development timeline, prior to points of design lock-in. Using a Marine Corps case study and a system dynamics simulation model, this thesis examines the nature of the relationship between component reliability and attributable changes in O&S cost. This thesis also develops a potential analysis methodology repeatable for future use. The modeling results indicate that this relationship is best described as exponential decay, meaning that the savings in O&S cost per system mile is proportional for any fixed incremental change in component reliability. We find these results to be insensitive to changes in preventative maintenance policies, maintenance deferment ratios, and component replacement cost. We completed verification and validation using the case study and existing Marine Corps systems, finding good association between the modeling results and the actual system. This analysis is valuable to the system and technology developer by helping to answer the question: "how reliable is reliable enough in terms of O&S cost" when considering technologies with uncertainties in long-term performance. / Master of Science

A general framework to design structural systems for a system-reliability goal is proposed. Component-based structural design proceeds on a member to member basis, insuring acceptable failure probabilities for every single structural member without explicitly assessing the overall system safety, whereas structural failure consequences are related to the whole system performance (the cost of a building or a bridge destroyed by an earthquake) rather than a single beam or column failure. Engineering intuition tells us that the system is safer than each individual component due to the likelihood of load redistribution and al- ternate load paths, however such conservatism cannot be guaranteed without an explicit system-level safety check. As a result, component-based structural designs can lead to both over-conservative components and a less-than-anticipated system reliability. System performance depends on component properties as well as the load-sharing network, which can possess a wide range of behaviors varying from a dense redundant system with scope for load redistribution after failure initiates, to a weakest-link type network that fails as soon as the first member exceeds its capacity. The load-sharing network is characterized by its overall system reliability and the system-reliability sensitivity, which quantifies the change in system safety due to component reliability modifications. A general algorithm is proposed to calculate modified component reliabilities using the sensitivity vector for the load-sharing network. The modifications represent an improvement on the structural properties of more critical components (more capacity, better ductility), and provide savings on less important members which do not play a significant role. The general methodology is applied to light steel-framed buildings under seismic loads. The building is modeled with non-linear spring elements representing its subsystems. The stochastic response of this model under seismic ground motions provides load-sharing, system reliability and sensitivity information, which are used to propose target diaphragm and shear wall reliability to meet a building reliability goal. Finally, diaphragm target reliability is used to propose modified component designs using stochastic simulations on geometric and materially non-linear finite-element models including every individual component. This material is based upon work supported by the National Science Foundation under Grant Nos. 1301001 (Virginia Tech), 1301033 (University of Massachusetts, Amherst) and 1300484 (Johns Hopkins University). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily re ect the views of the National Science Foundation. The author is grateful to the industry partner, the American Iron and Steel Institute, for their cooperation. / Ph. D. / This research proposes methods to design engineering networks for acceptable overall safety. Some examples of engineering networks include electrical systems, transportation systems and infrastructural systems. When any such system is designed, the properties of every individual component (size, capacity etc.) are assigned according to cost and safety requirements. However, it is typically very difficult to reliably quantify the overall safety of the entire system, which is technically known as ‘system reliability’. As a result, there are limited options for engineers to adjust the individual component designs within a system to achieve a pre-specified ‘targeted’ system reliability . This dissertation proposes computational and statistical methods to achieve this. The proposed methods are applied to a specific engineering system, namely a two story building subjected to ground shaking resulting from an earthquake. Computer models are developed for different scales of the building, beginning from the full building structure, then its individual floors and walls, and finally the individual components that make up each floor and wall. These models are verified with experimental results spanning all three scales. The verified models are then used to both compute the overall system reliability of the building subjected to earthquake ground shaking, as well as to modify its design component-by-component to achieve a targeted system reliability which is different from the system reliability of the original design. The results indicate that the as-designed reliability of the building system is adequate, but this reliability results from features of the building that are not expected to provide additional safety. The research demonstrates means to obtain this additional safety by redesigning the core functional building components, without relying on the unexpected added safety from ‘non-structural’ components (such as partition walls inside a building). The methods developed herein can be applied to redesign the components of various engineering system networks such that a targeted overall system reliability can be satisfied, resulting in improved performance and life-safety, potentially even at reduced costs.