2,644 research outputs found

    A fault-tolerant multiprocessor architecture for aircraft, volume 1

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    A fault-tolerant multiprocessor architecture is reported. This architecture, together with a comprehensive information system architecture, has important potential for future aircraft applications. A preliminary definition and assessment of a suitable multiprocessor architecture for such applications is developed

    Optimal Co-Design of Microgrids and Electric Vehicles: Synergies, Simplifications and the Effects of Uncertainty.

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    The burgeoning electrification of automobiles is causing convergence of the transportation and electrical power systems. This is visible in localized micropower systems, or microgrids, that supply plug-in vehicles. Though each system is designed by a separate industry, the need to reduce petroleum use and greenhouse gas emissions directs us to study the interface between these systems and develop methods to design both systems simultaneously. A method is presented for optimal co-design of a microgrid and electric vehicles using a nested optimal dispatch problem to solve for the operation of the microgrid and vehicles. This nested structure is implemented within a sequential optimization and reliability analysis loop to solve for the desired system reliability given uncertainties in the power load and solar power supply. The method is demonstrated for the case of co-designing a military microgrid and its all-electric tactical vehicles. The co-design approach results in a combined system design that minimizes capital investment and operating costs while meeting the reliability and performance requirements of both systems. The electric vehicles are shown to increase system reliability by providing energy storage without compromising their driving performance, and this support is shown to be robust to changes in the vehicle plug-in scheduling. The resulting optimal designs are highly-dependent on the input parameters, such as fuel cost and cost of capital equipment. For scenarios with high fuel costs and low battery prices, the co-design systems diverges significantly from separately-designed systems, resulting in improved performance and lower total costs.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91403/1/johnjohn_1.pd

    Airborne Advanced Reconfigurable Computer System (ARCS)

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    A digital computer subsystem fault-tolerant concept was defined, and the potential benefits and costs of such a subsystem were assessed when used as the central element of a new transport's flight control system. The derived advanced reconfigurable computer system (ARCS) is a triple-redundant computer subsystem that automatically reconfigures, under multiple fault conditions, from triplex to duplex to simplex operation, with redundancy recovery if the fault condition is transient. The study included criteria development covering factors at the aircraft's operation level that would influence the design of a fault-tolerant system for commercial airline use. A new reliability analysis tool was developed for evaluating redundant, fault-tolerant system availability and survivability; and a stringent digital system software design methodology was used to achieve design/implementation visibility

    Resilience Enhancement Strategies for Modern Power Systems

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    The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and man-made attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. Also, the massive integration of information and communication technology to power systems has evolved the power systems into what is known as cyber-physical power systems (CPPSs). Although advanced technologies in the cyber layer improve the operation and control of power systems, they introduce additional vulnerabilities to power system performance. This has motivated studying power system resilience evaluation and enhancements methods. Power system resilience can be defined as ``The ability of a system to prepare for, absorb, adapt to, and recover from disruptive events''. Assessing resilience enhancement strategies requires further and deeper investigation because of several reasons. First, enhancing the operational and planning resilience is a mathematically involved problem accompanied with many challenges related to modeling and computation methods. The complexities of the problem increases in CPPSs due to the large number and diverse behavior of system components. Second, a few studies have given attention to the stochastic behavior of extreme events and their accompanied impacts on the system resilience level yielding less realistic modeling and higher resilience level. Also, the correlation between both cyber and physical layers within the context of resilience enhancement require leveraging sophisticated modeling approaches which is still under investigation. Besides, the role of distributed energy resources in planning-based and operational-based resilience enhancements require further investigation. This calls for developing enhancement strategies to improve resilience of power grids against extreme events. This dissertation is divided into four parts as follows. Part I: Proactive strategies: utilizing the available system assets to prepare the power system prior to the occurrence of an extreme event to maintain an acceptable resilience level during a severe event. Various system generation and transmission constraints as well as the spatiotemporal behavior of extreme events should be properly modeled for a feasible proactive enhancement plan. In this part, two proactive strategies are proposed against weather-related extreme events and cyber-induced failure events. First, a generation redispatch strategy is formulated to reduce the amount of load curtailments in transmission systems against hurricanes and wildfires. Also, a defensive islanding strategy is studied to isolate vulnerable system components to cyber failures in distribution systems. Part II: Corrective strategies: remedial actions during an extreme event for improved performance. The negative impacts of extreme weather events can be mitigated, reduced, or even eliminated through corrective strategies. However, the high stochastic nature of resilience-based problem induces further complexities in modeling and providing feasible solutions. In this part, reinforcement learning approaches are leveraged to develop a control-based environment for improved resilience. Three corrective strategies are studied including distribution network reconfiguration, allocating and sizing of distributed energy resources, and dispatching reactive shunt compensators. Part III: Restorative strategies: retain the power service to curtailed loads in a fast and efficient means after a diverse event. In this part, a resilience enhancement strategy is formulated based on dispatching distributed generators for minimal load curtailments and improved restorative behavior. Part IV: Uncertainty quantification: Impacts of uncertainties on modeling and solution accuracy. Though there exist several sources of stochasticity in power systems, this part focuses on random behavior of extreme weather events and the associated impacts on system component failures. First, an assessment framework is studied to evaluate the impacts of ice storms on transmission systems and an evaluation method is developed to quantify the hurricane uncertainties for improved resilience. Additionally, the role of unavailable renewable energy resources on improved system resilience during extreme hurricane events is studied. The methodologies and results provided in this dissertation can be useful for system operators, utilities, and regulators towards enhancing resilience of CPPSs against weather-related and cyber-related extreme events. The work presented in this dissertation also provides potential pathways to leverage existing system assets and resources integrated with recent advanced computational technologies to achieve resilient CPPSs

    Operating strategies to preserve the adequacy of power systems circuit breakers

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    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.Ph.D.Committee Chair: Meliopoulos, A. P. Sakis; Committee Member: Divan, Deepakraj M.; Committee Member: Harley, Ronald G.; Committee Member: Johnson, Ellis L.; Committee Member: Taylor, David G

    Reliability Evaluation and Defense Strategy Development for Cyber-physical Power Systems

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    With the smart grid initiatives in recent years, the electric power grid is rapidly evolving into a complicated and interconnected cyber-physical system. Unfortunately, the wide deployment of cutting-edge communication, control and computer technologies in the power system, as well as the increasing terrorism activities, make the power system at great risk of attacks from both cyber and physical domains. It is pressing and meaningful to investigate the plausible attack scenarios and develop efficient methods for defending the power system against them. To defend the power grid, it is critical to first study how the attacks could happen and affect the power system, which are the basis for the defense strategy development. Thus, this dissertation quantifies the influence of several typical attacks on power system reliability. Specifically, three representative attack are considered, i.e., intrusion against substations, regional LR attack, and coordinated attacks. For the intrusion against substations, the occurrence frequency of the attack events is modeled based on statistical data and human dynamics; game-theoretical approaches are adopted to model induvial and consecutive attack cases; Monte Carlo simulation is deployed to obtain the desired reliability indices, which incorporates both the attacks and the random failures. For the false data injection attack, a practical regional load redistribution (LR) attack strategy is proposed; the man-in-the-middle (MITM) intrusion process is modeled with a semi-Markov process method; the reliability indices are obtained based on the regional LR attack strategy and the MITM intrusion process using Monte Carlo simulation. For the coordinated attacks, a few typical coordination strategies are proposed considering attacking the current-carrying elements as well as attacking the measurements; a bilevel optimization method is applied to develop the optimal coordination strategy. Further, efficient and effective defense strategies are proposed from the perspectives of power system operation strategy and identification of critical elements. Specially, a robustness-oriented power grid operation strategy is proposed considering the element random failures and the risk of man-made attacks. Using this operation strategy, the power system operation is robust, and can minimize the load loss in case of malicious man-made attacks. Also, a multiple-attack-scenario (MAS) defender-attack-defender model is proposed to identify the critical branches that should be defended when an attack is anticipated but the defender has uncertainty about the capability of the attacker. If those identified critical branches are protected, the expected load loss will be minimal

    Condition-based hazard rate estimation and optimal maintenance scheduling for electrical transmission system

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    The effectiveness of expending maintenance resources can vary dramatically depending on the target and timing of the maintenance activities. The objective of the work to develop a method of allocating economic resources and scheduling maintenance tasks among bulk transmission system equipment, so as to optimize the effect of maintenance with respect to the mitigation of component failure consequences. Techniques including condition-based failure rate estimation of electric transmission system components, analysis of failure consequences in power system, probabilistic modeling and risk assessment, and optimization are integrated in the work. Hidden Markov model is a good tool to estimate instantaneous status for deteriorating components. The maintenance selection and scheduling approach for bulk transmission equipment is based on the cumulative long-term risk caused by failure of each piece of equipment;This approach not only accounts for equipment failure probability and equipment damage, but it also accounts for the outage consequence in term of system related security problems. Various types of maintenance activities are studied and their relationship to the failure modes and system security improvement are investigated. An optimizer is developed to select and schedule the maintenance for large networks with various types of resource constraints, together with methods of resource reallocation;Finally, a strategy of incorporating maintenance activities among different transmission owners is developed. The objective of our work is to allocate resources economically and strategically so as to provide best performance of maintenance for electrical transmission system. These strategies can also be applied to problems inherent to resource intensive asset management in many similar types of infrastructures such as gas pipelines, airlines, and telecommunications

    The impact of maintenance contract arrangements on the yield of offshore wind power plants

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    In the optimisation of maintenance and vessel strategies for the operation of offshore wind plant, it is normally assumed that the off-taker of the power produced may directly control the dispatch of maintenance resources. However, in practice, services such as maintenance technicians and vessels are usually contracted from companies with larger arenas of operation, and so the organisational interfaces between these parties, and the different objective functions involved, need to be considered. This article looks at different current and future models for contracted maintenance, identifies interfaces and conflicts of interest, and constructs a quantified model demonstrating the potential impact on headline energy yields for a set of wind farms with a common contracted maintenance resource. The modelling illustrates that the performance of a site with contracted maintenance operations is not only dependent on the contracts held by that site but also on the effective competition in place with other sites for a centralised resource, and the performance of a site may be highly sensitive to the alignment of contractual incentives, relative travel distances, and the relative size of the site in terms of energy yield

    Impact Assessment, Detection, And Mitigation Of False Data Attacks In Electrical Power Systems

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    The global energy market has seen a massive increase in investment and capital flow in the last few decades. This has completely transformed the way power grids operate - legacy systems are now being replaced by advanced smart grid infrastructures that attest to better connectivity and increased reliability. One popular example is the extensive deployment of phasor measurement units, which is referred to PMUs, that constantly provide time-synchronized phasor measurements at a high resolution compared to conventional meters. This enables system operators to monitor in real-time the vast electrical network spanning thousands of miles. However, a targeted cyber attack on PMUs can prompt operators to take wrong actions that can eventually jeopardize the power system reliability. Such threats originating from the cyber-space continue to increase as power grids become more dependent on PMU communication networks. Additionally, these threats are becoming increasingly efficient in remaining undetected for longer periods while gaining deep access into the power networks. An attack on the energy sector immediately impacts national defense, emergency services, and all aspects of human life. Cyber attacks against the electric grid may soon become a tactic of high-intensity warfare between nations in near future and lead to social disorder. Within this context, this dissertation investigates the cyber security of PMUs that affects critical decision-making for a reliable operation of the power grid. In particular, this dissertation focuses on false data attacks, a key vulnerability in the PMU architecture, that inject, alter, block, or delete data in devices or in communication network channels. This dissertation addresses three important cyber security aspects - (1) impact assessment, (2) detection, and (3) mitigation of false data attacks. A comprehensive background of false data attack models targeting various steady-state control blocks is first presented. By investigating inter-dependencies between the cyber and the physical layers, this dissertation then identifies possible points of ingress and categorizes risk at different levels of threats. In particular, the likelihood of cyber attacks against the steady-state power system control block causing the worst-case impacts such as cascading failures is investigated. The case study results indicate that false data attacks do not often lead to widespread blackouts, but do result in subsequent line overloads and load shedding. The impacts are magnified when attacks are coordinated with physical failures of generators, transformers, or heavily loaded lines. Further, this dissertation develops a data-driven false data attack detection method that is independent of existing in-built security mechanisms in the state estimator. It is observed that a convolutional neural network classifier can quickly detect and isolate false measurements compared to other deep learning and traditional classifiers. Finally, this dissertation develops a recovery plan that minimizes the consequence of threats when sophisticated attacks remain undetected and have already caused multiple failures. Two new controlled islanding methods are developed that minimize the impact of attacks under the lack of, or partial information on the threats. The results indicate that the system operators can successfully contain the negative impacts of cyber attacks while creating stable and observable islands. Overall, this dissertation presents a comprehensive plan for fast and effective detection and mitigation of false data attacks, improving cyber security preparedness, and enabling continuity of operations
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