The verification of power grids in modern integrated circuits must start early in the design process when adjustments can be most easily incorporated. We adopt an existing early verification framework. The framework is vectorless, i.e., it does not require input test patterns and does not rely on simulating the power grid subject to these patterns. In this framework, circuit uncertainty is captured via a set of current constraints that capture what may be known or specified from circuit behavior. Grid verification becomes a question of finding the worst-case grid behavior which, in turn, entails the solution of linear programs (LPs) whose size and number is proportional to the size of the grids. The thesis builds on this systematic framework for dealing with circuit uncertainty with the aim of improving efficiency and expanding the capabilities handled within. One contribution introduces an efficient method based on a sparse approximate inverse technique to greatly reduce the size of the required linear programs while ensuring a user-specified over-estimation margin on the exact solution. The application of the method is exhibited under both R and RC grid models. Another contribution first extends grid verification under RC grid models to also check for the worst-case branch currents. This would require as many LPs as there are branches. Then, it shows how to adapt the approximate inverse technique to speed up the branch current verification process. A third contribution proposes a novel approach to reduce the number of LPs in the voltage drop and branch current verification problems. This is achieved by examining dominance relations among node voltage drops and among branch currents. This allows us to replace a group of LPs by one conservative and tight LP. A fourth contribution proposes an efficient verification technique under RLC models. The proposed approach provides tight conservative bounds on the maximum and minimum worst-case voltage drops at every node on the grid.

Thesis (Ph.D.)--University of Melbourne, Dept. of Computer Science and Software Engineering, 2006. / Typescript. Includes bibliographical references (leaves 189-207).

Thesis (Ph.D.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 89-91)

Thesis (M. Eng.)--University of Louisville, 2004. / Department of Computer Engineering and Computer Science. Vita. "December 2004." Includes bibliographical references (leaves 50-58).

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts.

No description available.

A set of algorithms building a program package for the generation of twoandthree-dimensional unstructured/hybrid grids around complex geometrieshas been developed. The unstructured part of the grid generator is based on the advancing frontalgorithm. Tetrahedra of variable size, as well as directionally stretched tetrahedracan be generated by specification of a proper background grid, initiallygenerated by a Delaunay algorithm. A marching layer prismatic grid generation algorithm has been developedfor the generation of grids for viscous flows. The algorithm is able to handleregions of narrow gaps, as well as concave regions. The body surface is describedby a triangular unstructured surface grid. The subsequent grid layers in theprismatic grid are marched away from the body by an algebraic procedurecombined with an optimization procedure, resulting in a semi-structured gridof prismatic cells. Adaptive computations using remeshing have been done with use of a gradientsensor. Several key-variables can be monitored simultaneously. The sensorindicates that only the key-variables with the largest gradients give a substantialcontribution to the sensor. The sensor gives directionally stretched grids. An algorithm for the surface definition of curved surfaces using a biharmonicequation has been developed. This representation of the surface canbe used both for projection of the new surface nodes in h-refinement, and theinitial generation of the surface grid. For unsteady flows an algorithm has been developed for the deformationof hybrid grids, based on the solution of the biharmonic equation for the deformationfield. The main advantage of the grid deformation algorithm is that itcan handle large deformations. It also produces a smooth deformation distributionfor cells which are very skewed or stretched. This is necessary in orderto handle the very thin cells in the prismatic layers. The algorithms have been applied to complex three-dimensional geometries,and the influence of the grid quality on the accuracy for a finite volumeflow solver has been studied for some simpler generic geometries. / QC 20100812

No description available.

There are unique challenges and opportunities related to the integration of electric vehicles into the future power grid, especially the modern distribution grid since electric vehicle (EV) charging facilities and fast-charging stations are usually tied to low-voltage and medium-voltage power networks. The grid-connected EVs, if properly controlled, can operate as distributed energy storage and provide various ancillary services, such as peak shaving, fast-response reserve capacity, frequency regulation, voltage control and reactive supports. The purpose of this thesis is to integrate EVs to the power grid and provides suitable ancillary services to improve the grid reliability and stability. The larger future penetration of EVs and renewable energies is also taken into account to develop the vehicle-to-grid (V2G) control scheme with the constraints of EV charging and communication infrastructures. The main contents include: V2G mathematical model and system configuration; impact evaluation of EV integration and the V2G control framework; energy scheduling of EVs integration; V2G dynamic regulation services; control method of EV aggregator for dispatching a fleet of EVs; and the evaluation of V2G control scheme and hardware-in-the-loop experimental system design. 　　In the thesis, the impact of EV charging demand on the conventional distribution grid is firstly estimated to reveal the negative effects of the arbitrary EV charging and the necessity to control the EV charging process. The potential benefits EVs can bring into the power grid support are discussed and a V2G control framework is proposed to perform the V2G optimization and various regulation services. The current power electronics applied EV charging facilities and communication network are integrated into the V2G operation in the future distribution grid with microgrid and smaller installation of renewable generation units. 　　Next, mathematical model of V2G power control is formulated. Two optimization methods are proposed to schedule the EV charging and discharging energy to minimize the power losses and the operating cost while satisfying the mobility needs and the power system limitations. Subsequently, the dynamic regulation of V2G power is investigated to unleash the potential of EVs to provide multiple ancillary services simultaneously. In addition to V2G optimal energy scheduling, EVs can also be employed for dynamic power regulation which requires the fast response to the instantaneous imbalance between the power supply and demand. V2G power is controlled to mitigate the power fluctuation caused by the intermittent wind energy resources, and thus stabilize the system frequency and voltage. Finally, an EV-centric hybrid energy storage system is proposed, which combines the merits of V2G operation and superconducting magnetic energy storage (SMES) to enhance the power quality and system frequency stability. The critical issues in V2G applications are summarized in the end. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

In recent years, since the concept of smart grid rises and the existing power grids are continuously modernized, more and more electric vehicles (EVs) are integrated into the power grid. In the power grid, EVs are expected to provide various energy services, such as spinning reserves, regulation services, optimization services, stability improvement, reactive compensation and grid security. This thesis is to model, analyze and implement these energy services of EVs. 　　Firstly, a multilayer framework of a power system with vehicle-to-grid (V2G) and vehicle-to-vehicle (V2V) operation is proposed. Its fundamental components including batteries, renewable energy sources are modeled for system analysis. Moreover, a general model for multiply purposes is presented. 　　Secondly, based on the modeling of EVs and the power systems, the analysis on frequency regulation and transient stability of the V2G system can be carried out effectively. The objectives of the frequency regulation are to keep the system frequency constant, and eliminate the deviations fast and effectively. While, the transient stability is to observe the performances of the power systems integrated with EVs and superconducting magnetic energy storage (SMES) during emergency cases. The results illustrate that EVs are valuable for improve the frequency and transient stability of the power systems. 　　Finally, the coordination and optimization of the power systems with EVs are studied. Unit commitment involving EVs is analyzed, which uses EVs to replace some expensive generating units to achieve minimum operating cost and emissions. In addition, the optimal sizing of EV aggregations in the distribution power system is conducted to minimize the total power loss. And the individual EV in the aggregations is dispatched to achieve minimum charging cost by satisfying the optimal sized demand and the real-time pricing. The results verified that EVs can be used to achieve optimized goals, such as minimum costs, emissions and losses. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy