Reconfigurable computing is an old concept that during the past couple of decades has become increasingly popular. The concept combines the flexibility of software with the performance of hardware. One important contributing factor to the uprising in popularity is the presence of FPGAs (field-programmable gate arrays), which realize the concept by allowing the hardware to be reconfigured dynamically. The current state of reconfigurable computing is discussed further in the thesis. Debugging is a vital part in the development of a hardware design. It can be done in several ways depending on the situation. The most common way is to perform simulations but in some cases the fault-finding has to be done when the design is implemented in hardware. In this thesis a framework concept is designed that utilizes and evaluates some of the reconfigurable computing ideas. The framework provides debugging possibilities for FPGA designs in a novel way, with a modular system where each module provide means to aid finding a specific fault. The framework is added to an existing design, and offers the user a glimpse into the design behavior and the hardware it runs on. One of the debug modules will be released separately under a free license. It allows the developer to see the contents of the memories in a design without requiring special debugging equipment.

Partial Reconfigurable FPGA provides ability of reconfigure the FPGA duringrun-time. But the reconfigurable part is disabled while performing reconfiguration. In order to maintain the functionality of system, data stream should be hold for RP during that time. Due to this feature, the reconfiguration time becomes critical to designed system. Therefore this thesis aims to build a functional partial reconfigurable system and figure out how much time the reconfiguration takes. A XILINX ML605 evaluation board is used for implementing the system, which has one static part and two partial reconfigurable modules, ICMP and HTTP. A Web Client sends different packets to the system requesting different services. These packets’ type information are analyzed and the requests are held by a MicroBlaze core, which also triggers the system’s self-reconfiguration. The reconfiguration swaps the system between ICMP and HTTP modules to handle the requests. Therefore, the reconfiguration time is defined between detection of packet type and completion of reconfiguration. A counter is built in SP for measuring the reconfiguration time. Verification shows that this system works correctly. Analyze of test results indicates that reconfiguration takes 231ms and consumes 9274KB of storage, which saves 93% of time and 50% of storage compared with static FPGA configuration.

The survivability concerns the service continuity when the components of a system are damaged. This concept is especially useful in the emergency management of the system, as often emergencies involve accidents or incident disasters which more or less damage the system. The overall objective of this thesis study is to develop a quantitative management approach to the emergency management of a wireless cellular telecommunication system in light of its service continuity in emergency situations namely the survivability of the system. A particular wireless cellular telecommunication system, WCDMA, is taken as an example to ground this research.<p>The thesis proposes an ontology-based paradigm for service management such that the management system contains three models: (1) the work domain model, (2) the dynamic model, and (3) the reconfiguration model. A powerful work domain modeling tool called Function-Behavior-Structure (FBS) is employed for developing the work domain model of the WCDMA system. Petri-Net theory, as well as its formalization, is applied to develop the dynamic model of the WCDMA system. A concept in engineering design called the general and specific function concept is applied to develop a new approach to system reconfiguration for the high survivability of the system. These models are implemented along with a user-interface which can be used by emergency management personnel. A demonstration of the effectiveness of this study approach is included.<p>There are a couple of contributions with this thesis study. First, the proposed approach can be added to contemporary telecommunication management systems. Second, the Petri Net model of the WCDMA system is more comprehensive than any dynamic model of the telecommunication systems in literature. Furthermore, this model can be extended to any other telecommunication system. Third, the proposed system reconfiguration approach, based on the general and specific function concept, offers a unique way for the survivability of any service provider system.<p>In conclusion, the ontology-based paradigm for a service system management provides a total solution to service continuity as well as its emergency management. This paradigm makes the complex mathematical modeling of the system transparent to the manager or managerial personnel and provides a feasible scenario of the human-in-the-loop management.

In the next decade, electric vehicles (EV) will be heading to the road in a fast speed. Utility company would have no control over the future EV charging points or stations, and no direct control over periods and frequency of EV charging that could cause great effects to the existing distribution network operations if not well planned. Distribution system operation and expansion planning would become more complicated due to the high degree of uncertainty of the EV charging demand. Markov model is used in this study to calculate the probabilities and locations of EV charging. To mitigate the loading and voltage quality problem, feeder reconfiguration is proposed. The problem is formulated as an stochastic programming program with an objective function of minimizing total switching and system loss costs, and subject to radial structure of the distribution network and security constraints. The problem is solved by a binary particle swarm optimization technique. Test results indicate that feeder reconfiguration can be exercised to match loading patterns of different types of feeders (residential, commercial and industrial) with various stochastic charging scenarios, and consequently, reduce the impacts of EV charging and optimize the use of the existing network.

Constellation reconfi guration consists of transforming an initial constellation of satellites into some final constellation of satellites to maintain system optimality. Constellations with phased deployment, changing mission requirements, or satellite failures would all benefi t from reconfi guration capability. The constellation reconfiguration problem can be broken into two broad sub-problems: constellation design and constellation transfer. Both are complicated and combinatorial in nature and require new, more efficient methods. Having reviewed existing constellation design frameworks, a new framework, the Elliptical Flower Constellations (EFCs), has been developed that offers improved performance over traditional methods. To assist in rapidly analyzing constellation designs, a new method for orbit propagation based on a sequential solution of Kepler's equation is presented. The constellation transfer problem requires an optimal assignment of satellites in the initial orbit to slots in the final orbit based on optimal orbit transfers between them. A new method for approximately solving the optimal two-impulse orbit transfer with fixed end-points, the so-called minimum Delta v Lambert's problem, is developed that requires the solution of a 4th order polynomial, as opposed to the 6th or higher order polynomials or iterative techniques of existing methods. The recently developed Learning Approach to sampling optimization is applied to the particular problem of general orbit transfer between two generic orbits, with several enhancements specifi c to this problem that improve its performance. The constellation transfer problem is then posed as a Linear Assignment Problem and solved using the auction algorithm once the orbit transfers have been computed. Constellations designed for global navigation satellite systems and for global communications demonstrate signifi cant improvements through the use of the EFC framework over existing methods. An end-to-end example of constellation recon figuration for a constellation with changing regional coverage requirements shows the effectiveness of the constellation transfer methods.

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In this dissertation, the artificial intelligent Petri nets is applied to find the optimal switching operation for service restoration and feeder loading balance for 18-feeders distribution systems that containing the whole 24-hours load profiles of service zones. After the fault location has been identified and isolated for a system fault contingency, the Petri nets model with inference mechanism is derived and applied to solve the optimal load transfer among distribution feeders. For system normal operation condition, the load balancing among distribution feeders is obtained by the Petri nets model to enhance the operation efficiency of distribution systems. The switching operation, which will result in the loading balance among distribution feeders, is derived by the Petri nets model according to the loading cost of distribution systems. To determine the effectiveness of the proposed methodology, a Taipower (Taiwan Power Company) distribution system which serves a mixed types of customers is selected to perform the computer simulation. It is found that the Petri nets approach can enhance the solution process of fault restoration with proper load transfer and improve feeder load balance for distribution systems by considering the load characteristics of the service customers.

The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of the Shipboard Power System (SPS) are critical to the mission of a surface combatant ship, especially under battle conditions. In the event of battle, various weapons might attack a ship. When a weapon hits the ship it can cause severe damage to the electrical system on the ship. This damage can lead to de-energization of critical loads on a ship that can eventually decrease a ship’s ability to survive the attack. It is very important, therefore, to maintain availability of energy to the connected loads that keep the power systems operational. Technology exists that enables the detection of an incoming weapon and prediction of the geographic area where the incoming weapon will hit the ship. This information can then be used to take reconfiguration actions before the actual hit so that the actual damage caused by the weapon hit is reduced. The Power System Automation Lab (PSAL) has proposed a unique concept called "Predictive Reconfiguration" which refers to performing reconfiguration of a ship’s power system before a weapon hit to reduce the potential damage to the electrical system caused by the impending weapon hit. The concept also includes reconfiguring the electrical system to restore power to as much of the healthy system as possible after the weapon hit. This dissertation presents a new methodology for Predictive Reconfiguration of a Shipboard Power System (SPS). This probabilistic approach includes a method to assess the damage that will be caused by a weapon hit. This method calculates the expected probability of damage for each electrical component on the ship. Also a heuristic method is included, which uses the expected probability of damage to determine reconfiguration steps to reconfigure the ship’s electrical network to reduce the damage caused by a weapon hit. This dissertation also presents a modified approach for performing a reconfiguration for restoration after the weapon hits the system. In this modified approach, an expert system based restoration method restores power to loads de-energized due to the weapon hit. These de-energized loads are restored in a priority order. The methods were implemented using multi-agent technology. A test SPS model based on the electrical layout of a non-nuclear surface combatant ship was presented. Complex scenarios representing electrical casualties caused due to a weapon hit, on the test SPS model, were presented. The results of the Predictive Reconfiguration methodology for complex scenarios were presented to illustrate the effectiveness of the developed methodology.

In a deregulated power market, customers would have more choices for their power service and the improvement of service quality has become a challenge to power transmission and distribution companies. Distribution system reliability that was traditionally considered within the planning activities, is now incorporated in the operational environment. This dissertation presents study results of a multi-objective feeder operation optimization problem that considers how to balance network efficiency, switching and reliability costs in a distribution network. The proposed method divides annual feeder load curve into multi periods of load levels and optimizes the feeder configurations for different load levels in annual operation planning. Customer load profiles and seasonal varying data of feeder section failure rates and customer interruption costs are considered. Simulations results demonstrate the time varying effects on the optimal distribution feeder reconfiguration and operation costs. A binary particle swarm optimization (BPSO) search is adopted to determine the feeder configuration in each time period. Test results indicate that not considering time varying effects and using only simplified fixed load and reliability parameters could underestimate the total loss to the utility and its customers.

Thèse de doctorat : Informatique : Nice : 2006. / Bibliogr. p. 95-100. Résumés en français, en anglais et en portugais.