Optimization Techniques for Modern Power Systems Planning, Operation and Control

Recent developments in computing, communication and improvements in optimization techniques have piqued interest in improving the current operational practices and in addressing the challenges of future power grids. This dissertation leverages these new developments for improved quasi-static analysis of power systems for applications in power system planning, operation and control. The premise of much of the work presented in this dissertation centers around development of better mathematical modeling for optimization problems which are then used to solve current and future challenges of power grid. To this end, the models developed in this research work contributes to the area of renewable integration, demand response, power grid resilience and constrained contiguous and non-contiguous partitioning of power networks. The emphasis of this dissertation is on finding solutions to system operator level problems in real-time. For instance, multi-period mixed integer linear programming problem for applications in demand response schemes involving more than million variables are solved to optimality in less than 20 seconds of computation time through tighter formulation. A balanced, constrained, contiguous partitioning scheme capable of partitioning 20,000 bus power system in under one minute is developed for use in time sensitive application area such as controlled islanding

Towards Unifying Inheritance and Automatic Program Specialization

Inheritance allows a class to be specialized and its attributes refined, but implementation specialization can only take place by overriding with manually implemented methods. Automatic program specialization can generate a specialized, efficient implementation. However, specialization of programs and specialization of classes (inheritance) are considered different abstractions. We present a new programming language, Lapis, that unifies inheritance and program specialization at the conceptual, syntactic, and semantic levels. This paper presents the initial development of Lapis, which uses inheritance with covariant specialization to control the automatic application of program specialization to class members. Lapis integrates object-oriented concepts, block structure, and techniques from automatic program specialization to provide both a language where object-oriented designs can be efficiently implemented and a simple yet powerful partial evaluator for an object-oriented language

DEEP LEARNING BASED POWER SYSTEM STABILITY ASSESSMENT FOR REDUCED WECC SYSTEM

Power system stability is the ability of power system, for a giving initial operating condition, to reach a new operation condition with most of the system variables bounded in normal range after subjecting to a short or long disturbance. Traditional power system stability mainly uses time-domain simulation which is very time consuming and only appropriate for offline assessment. Nowadays, with increasing penetration of inverter based renewable, large-scale distributed energy storage integration and operation uncertainty brought by weather and electricity market, system dynamic and operating condition is more dramatic, and traditional power system stability assessment based on scheduling may not be able to cover all the real-time dispatch scenarios, also online assessment and self-awareness for modern power system becomes more and more important and urgent for power system dynamic security. With the development of fast computation resources and more available online dataset, machine learning techniques have been developed and applied to many areas recently and could potentially applied to power system application. In this dissertation, a deep learning-based power system stability assessment is proposed. Its accurate and fast assessment for power system dynamic security is useful in many places, including day-ahead scheduling, real-time operation, and long-term planning. The simplified Western Electricity Coordinating Council (WECC) 240-bus system with renewable penetration up to 49.2% is used as the study system. The dataset generation, model training and error analysis are demonstrated, and the results show that the proposed deep learning-based method can accurately and fast predict the power system stability. Compared with traditional time simulation method, its near millisecond prediction makes the online assessment and self-awareness possible in future power system application

Many-Task Computing and Blue Waters

This report discusses many-task computing (MTC) generically and in the context of the proposed Blue Waters systems, which is planned to be the largest NSF-funded supercomputer when it begins production use in 2012. The aim of this report is to inform the BW project about MTC, including understanding aspects of MTC applications that can be used to characterize the domain and understanding the implications of these aspects to middleware and policies. Many MTC applications do not neatly fit the stereotypes of high-performance computing (HPC) or high-throughput computing (HTC) applications. Like HTC applications, by definition MTC applications are structured as graphs of discrete tasks, with explicit input and output dependencies forming the graph edges. However, MTC applications have significant features that distinguish them from typical HTC applications. In particular, different engineering constraints for hardware and software must be met in order to support these applications. HTC applications have traditionally run on platforms such as grids and clusters, through either workflow systems or parallel programming systems. MTC applications, in contrast, will often demand a short time to solution, may be communication intensive or data intensive, and may comprise very short tasks. Therefore, hardware and software for MTC must be engineered to support the additional communication and I/O and must minimize task dispatch overheads. The hardware of large-scale HPC systems, with its high degree of parallelism and support for intensive communication, is well suited for MTC applications. However, HPC systems often lack a dynamic resource-provisioning feature, are not ideal for task communication via the file system, and have an I/O system that is not optimized for MTC-style applications. Hence, additional software support is likely to be required to gain full benefit from the HPC hardware

Optimal planning of fixed route bus transit systems : a systems approach

A new bus transit planning tool is developed for application in determining operating policies of a fixed-route bus transit system. The objective of the study is to model a bus transit system which functions under time-varying passenger demands and service characteristics. The two phase transit model developed in this research is intended for use as a mass transit planning tool, to solve transit problems confronting the mass transit planner. The model is used to compute cost differentials in transit system options. These alternatives of expanding, abandoning or modifying service depend upon the service frequency, fleet size and other system attributes such as operating speed, delay, passenger demand and relevant cost factors. The model is formulated in two phases, jointly utilizing linear and dynamic programming techniques. It is directed toward optimizing transit operation during one period and then aggregating each operation over the range of transit service periods. The basic components of system function to be optimized (minimal total cost) include such variables as bus operating and ownership costs, passenger costs in terms of walking, riding, and transfer times as well as bus fares. The transit model has been programmed for a digital computer. This model requires inputs of existing street configuration and bus routes, bus schedules, speed and delay data for street networks, fare structure, load factor and passenger Origin-Destination information for different periods. A practical application of the transit model is presented in the format of a case study. This application illustrates the utilization of the methodology for deriving bus transit operating policies and the consideration of planning alternatives. The result of a comparison of these policies and alternatives is a significant reduction in the total system cost. Special emphasis has been given to the analysis of the structural elements involved in a transit system as well as new transit planning techniques. There follows a summation of the findings and the implications of the results. This summary includes an appraisal of the model as to its limitations as well as recommendations for future research. The appendix, finally, lists a summary of notations review of previous research, flow charts and listings of computer programs, supplemental data, computer input and output files, and an annotated bibliography containing current literature concerning the operation and planning of public transportation

Centralized wind power plant voltage control with optimal power flow algorithm

This thesis presents a method of controlling the reactive power injected into a medium-voltage collection system by multiple wind turbine generators such that the voltage at one bus is maintained at a specified level. The proposed control accounts for the system impedance between the wind turbine generator terminals and the point of interconnect, and utilizes an optimal power flow algorithm to dispatch reactive power amongst the wind turbine generators. This optimal power flow algorithm minimizes real power losses within the wind power plant and avoids operating conditions that violate various operating constraints. This thesis presents a 100 wind turbine generator wind plant test system and uses this test system to demonstrate the potential increased revenues occasioned by the proposed control system as compared to a system that dispatches the wind turbine generator reactive power injections uniformly. Analysis shows that it can be cost effective to install the proposed control system

Exploring the Augmentation of Fuzzing Techniques with Interface Awareness

Device drivers are an essential part in modern Unix-like systems to handle operations on physical devices, from hard disks and printers to digital cameras and Bluetooth speakers. The surge of new hardware, particularly on mobile devices, introduces an explosive growth of device drivers in system kernels. Many such drivers are provided by third-party developers, which are susceptible to security vulnerabilities and lack proper vetting. Unfortunately, the complex input data structures for device drivers render traditional analysis tools, such as fuzz testing, less effective, and so far, research on kernel driver security is comparatively sparse.In my thesis, I present DIFUZE, an interface-aware fuzzing tool to automatically generate valid inputs and trigger the execution of the kernel drivers. We leverage static analysis to compose correctly-structured input in the userspace to explore kernel drivers. DIFUZE is fully automatic, ranging from identifying driver handlers, to mapping of device file names, to constructing complex argument instances. We evaluate our approach on seven modern Android smartphones. The results show that DIFUZE can effectively identify kernel driver bugs, and reports 32 previously unknown vulnerabilities, including flaws that lead to arbitrary code execution

Dynamic Assignment of Scoped Memory Regions in the Translation of Java to Real-Time Java

Advances in middleware, operating systems, and popular, general-purpose languages have brought the ideal of reasonably-bound execution time closer to developers who need such assurances for real-time and embedded systems applications. Extensions to the Java libraries and virtual machine have been proposed in a real-time Java standard, which provides for specification of release times, execution costs, and deadlines for a restricted class of threads. To use such features, the programmer is required to use unwieldy code constructs to create region-like areas of storage, associate them with execution scopes, and allocate objects from them. Further, the developer must ensure that they do not violate strict inter-region reference rules. Unfortunately, it is difficult to determine manually how to map object instantiations to execution scopes. Moreover, if ordinary Java code is modified to effect instantiations in scopes, the resulting code is difficult to read, maintain, and reuse. We present a dynamic approach to determining proper placement of objects within scope-bounded regions, and we employ a procedure that utilizes aspect-oriented programming to instrument the original program, realizing the program’s scoped memory concerns in a modular fashion. Using this approach, Java programs can be converted into region-aware Java programs automatically