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.

Currently, major power systems almost invariably operate under interconnected conditions to transfer power in a stable and reliable manner. Multi-area reliability evaluation has thus become an invaluable tool in the planning and operation of such systems. Multi - area reliability evaluation is typically done by considering equivalent tie lines between different areas in an integrated power system. It gives approximate results for the reliability indices of a power system as it models each of the areas as a single node to which are connected the entire area generation and loads. The intratransmission lines are only indirectly modeled during the calculation of equivalent tie lines' capacities. This method is very widely used in the power industry, but the influence of the various approximations and assumptions, which are incorporated in this method, on reliability calculations has not been explored. The objective of the research work presented in this thesis is the development of a new method called Composite system based multi - area reliability model, which does multi - area reliability evaluation considering the whole composite system. It models the transmission system in detail and also takes into account the loss sharing policy within an area and no - load loss sharing policy among the areas. The proposed method is applied to standard IEEE 24 bus Reliability Test System (RTS) and the traditional equivalent tie-line method is applied to the multi-area configuration of the same test system. The results obtained by both the methods are analyzed and compared. It is found that the traditional model, although having some advantages, may not give accurate results.

Fossil fuel is presently a major source for electricity production, but it contributes significantly to Green House Gas emissions. Wind is a promising alternative, and can potentially become a major power resource in future power systems. Wind power installations are growing significantly for producing clean energy in electric power systems. As the wind penetration continues to increase to relatively high levels, it can significantly affect the overall performance and reliability of the power system. Hence, it becomes very important to accurately model the behaviour of wind, its interaction with conventional sources and also with other wind resources connected to the power system in order to conduct a realistic assessment of system reliability and benefits from wind energy utilization. When the wind penetration levels are low, all the wind energy generated is utilized to serve the load. However, at higher wind penetration levels, wind energy is spilled due to limitations in the operating reserve or ramping capability of the scheduled generating units. The system reliability and the wind energy benefits are reduced as the wind energy spillage increases due to wind curtailment. Hence, accurate wind models should be researched and developed to include wind energy curtailment in the reliability modelling, considering factors such as the system load level, priority loading order of the generating unit and response rates of the generating units. Researchers have not incorporated these factors in wind power modelling and in the adequacy evaluation of wind integrated power systems. A new analytical technique is developed in the subsequent chapters to carry out a comprehensive wind absorption capability evaluation of the power system, and also to incorporate this characteristic in reliability modelling of the system. Wind curtailments can take place not only due to generation constraints, but also due to transmission line constraints depending on the capacity and location of the wind energy resource in the power system, and the power transfer capacity of the transmission lines connected to the wind farm bus. Therefore, reliability modelling of the power system considering wind curtailments due to both generation and transmission constraints should be carried out to assess the impact of wind farms on bulk system reliability and the wind energy benefits. Wind curtailment is incorporated in the composite power system reliability evaluation by modelling the wind resource both as generation and as negative load. The techniques can be utilized to conduct system adequacy and wind energy benefit assessment both at the capacity planning stages and composite generation/transmission planning stages, incorporating wind power curtailment due to generating unit response limitations. As the wind penetration in a power system increases, the wind farms connected to the system are distributed at different geographical locations. Both analytical and Monte Carlo Simulation based techniques have previously been used by the research group at the University of Saskatchewan to include the cross correlation between the wind characteristics of different wind farms in the wind modelling for reliability evaluation of power systems. However, the combined effect of wind diversity and wind curtailments due to both transmission and generation constraints on the system reliability and wind energy benefit assessment has not been considered. The techniques developed for system adequacy and wind energy benefit assessment considering wind curtailment due to generation and transmission constraints are further modified and presented in this thesis to include wind diversity in the analysis. The developed techniques for adequacy evaluation of wind integrated power systems considering wind power curtailment and diversity should be extremely useful for system planning engineers and policy makers as wind power penetration in power systems continues to increase throughout the world.

There are presently worldwide targets for decreasing anthropogenic greenhouse gases (GHGs) emissions owing to global climate change concerns. Here in the United Kingdom, the government has committed to reduce its GHGs emissions by at least 80% by 2050 relative to 1990 levels. In order to achieve the ambitious 2050 targets and minimise cumulative emissions along the way, modern power systems are facing a series of great challenges. These challenges include extensive utilisation of renewable generation, diverse demand--side participation in power system operation and planning, as well as considerable application of emerging smart devices and appliances. All of these challenges will significantly increase the complexity of future power systems in terms of both operation and design. Regardless, the primary objective of power systems remains the same. That is the system must supply all the customers (responsive ones and non-responsive ones) with electricity as economically as possible and with an adequate level of continuity and quality. With the widespread utilisation of smart meters and appliances as well as the large-scale installation of different storage technologies, the services that demand response (DR) and electrical energy storage (EES) resources can provide will cover a wide range of ancillary services. More importantly, the grid-scale penetration of DR and EES resources is able to provide energy management and capacity support services, which can be considered as the alternative to generation resources. In this light, considerable amount of research has been done focusing on engaging particular types of electricity users with different kinds of incentives and/or tariff schemes, so that the economic benefits to both utilities and customers are optimised. However, no general framework for systematic assessment of the contribution to power system adequacy of supply from potential grid-scale penetration of DR and EES resources is available up till now, particularly taking specific consideration of DR's flexibility and payback characteristics as well as EES's operational parameters. The research work in this thesis therefore emphasises exclusively on the potential of grid-scale DR and EES resources to serve as alternative resources to electricity generation within the context of power system adequacy of supply. More specifically, based on literature survey of existing studies in similar topics, this thesis has made some substantial contributions and innovations, such as developing novel models of these emerging demand-side resources, implementing a systematic adequacy of supply assessment with new aspect to measure the level of adequacy of supply (new indices), proposing a novel and comprehensive framework for evaluation of the capacity credit of DR and EES, and analysing the economic value based on power system fundamental long--term costs of interruption and supply. Ultimately, this thesis has established a comprehensive framework for assessment of the contribution of DR and EES to power system adequacy of supply. Additionally, the numerical studies carried out in this thesis have enabled the inference of general adequacy of supply implications in terms of deploying DR and EES resources to provide capacity support to power systems.

<p>In reregulated and restructured electricity markets the production and retail of electricity is conducted on competitive markets, the transmission and distribution on the other hand can be considered as natural monopolies. The financial regulation of Distribution System Operators (DSOs) has in many countries, partly as a consequence of the restructuring in ownership, gone through a major switch in regulatory policy. From applying regulatory regimes were the DSOs were allowed to charge their customers according to their actual cost plus some profit, i.e. cost-based regulation, to regulatory models in which the DSOs performance are valued in order to set the allowable revenue, i.e. Performance-Based Regulation (PBR). In regulatory regimes that value performance, the direct link between cost and income is weakened or sometimes removed. This give the regulated DSOs strong cost cutting incentives and there is consequently a risk of system reliability deterioration due to postponed maintenance and investments in order to save costs. To balance this risk the PBR-framework is normally complemented with some kind of quality regulation (QR). How both the PBR and QR frameworks are constructed determines the incentive that the DSO will act on and will therefore influence the system reliability development.</p><p>This thesis links the areas of distribution system reliability and performancebased regulation. First, the key incentive features within PBR, that includes the quality of supply, are identified using qualitative measures that involve analyses of applied regulatory regimes, and general regulatory policies. This results in a qualitative comparison of applied PBR models. Further, the qualitative results are quantified and analysed further using time sequential Monte Carlo simulations (MCS). The MCS enables detailed analysis of regulatory features, parameter settings and financial risk assessments. In addition, the applied PBRframeworks can be quantitatively compared. Finally, some focus have been put on the Swedish regulation and the tool developed for DSO regulation, the Network Performance Assessment Model (NPAM), what obstacles there might be and what consequences it might bring when in affect.</p>

The objective of the proposed research is to quantify the limits of overstressed and aging circuit breakers in terms of probability of failure and to provide guidelines to determine network reconfigurations, generator commitment, and economic dispatch strategies that account for these limits. The proposed temporary power system operating strategies address circuit breaker adequacy issues and allow overstressed breakers to be operated longer and more reliably until they are replaced with adequate equipment. The expansion of electric networks with new power sources (nuclear plants, distributed generation) results in increased short-circuit or fault currents levels. As fault currents increase, they will eventually exceed circuit breaker ratings. Circuit breakers exposed to fault currents in excess of their ratings are said to be overstressed, underrated, or inadequate. Insufficient ratings expose overstressed breakers to increased failure probabilities. Extensive common-mode outages caused by circuit breaker failures reduce the reliability of power systems. To durably avoid outages and system unreliability, overstressed breakers must eventually be replaced. Large-scale replacements of overstressed breakers cannot be completed in a short time because of budgetary limits, capital improvement schedules, and manufacturer-imposed constraints. Meanwhile, to preserve the ability of old and overstressed breakers to safely interrupt faults, short-circuit currents must be kept within the limits imposed by the ratings and the age of these breakers by using the substation reconfiguration and generator commitment strategies described in this study. The immediate benefit of the above-mentioned operating strategies is a reduction of the failure probability of overstressed breakers obtained by avoiding the interruption of currents in excess of breaker ratings. Other benefits include (i) increased network reliability, (ii) restored operating margins with respect to existing equipment, and (iii) prioritized equipment upgrades that enhance the long-term planning of power systems.

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