Thesis (M.S.)--Mississippi State University. Department of Computational Engineering. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.

Thesis (M.S.M.E.)--University of South Florida, 2003. / Title from PDF of title page. Document formatted into pages; contains 87 pages. Includes bibliographical references.

The Spin-Transfer Torque Magnetoresistive Random Access Memory (STT-MRAM) has opened new doors as an emerging technology with high potential to replace traditional CMOS-based memory technology. This has come true due to the density, speed and non- volatility that have been demonstrated. The STT-MRAM uses Magnetic Tunnel Junction (MTJ) elements as non-volatile memory storage devices because of the recent discovery of spin-torque phenomenon for switching the magnetization states. The magnetization of the free layer in STT-MRAM can be switched from logic "1" to logic "0" by the use of a spin-transfer torque. However, the STT-MRAMs have till now only been used as universal memory. As a result, STT-MRAMs are not yet commercially used as computing elements, though they have the potential to be used as Logic-In-Memory computation applications. In order to advance this STT-MRAM technology for computation, we have used different MRAM devices that are available as memory elements with different geometries, to use it as computing elements. This dissertation presents design and implementation of such devices using different multilayer magnetic material stacks for computation. Currently, the design of STT-MRAMs is limited to only memory architectures, and there have been no proposals on the viability of STT-MRAMs as computational devices. In the present work, we have developed a design, which could be implemented for universal logic computation. We have utilized the majority gate architecture, which uses the magneto-static interaction between the freelayers of the multilayer nanomagnets, to perform computation. Furthermore, the present work demonstrates the study of dipolar interaction between nanomagnetic disks, where we observed multiple magnetization states for a nanomagnetic disk with respect to its interaction energy with its neighboring nanomagnets. This was achieved by implementing a single layer nanomagnetic disk with critical dimension selected from the phase plot of single domain state (SDS) and vortex state (VS). In addition, we found that when the interaction energy between the nanomagnetic disks with critical dimension decreases (increase in center-to-center distance) the magnetization state of the nanomagnetic disks changes from single domain state to vortex state within the same dimension. We were able to observe this effect due to interaction between the neighboring nanomagnets. Finally, we have presented the design and implementation of a Spin-Torque driven Re- configurable Array of Nanomagnets (STRAN) that could perform Boolean and non-Boolean computation. The nanomagnets are located at every intersection of a very large crossbar array structure. We have placed these nanomagnets in such a way that the ferromagnetic free layers couple with each other. The reconfigurable array design consists of an in-plane (IP) free layer and a fixed polarizer [magnetized out-of-plane (OP)]. The cells that need to be deselected from the array are taken to a non-computing oscillating state.

A “smarter grid” is expected to be more flexible and more reliable than traditional electric power grids. Among technologies required for the “smarter grid” deployment, this dissertation presents a sustainable microgrid and a spatial and temporal model of plug-in electric vehicle charging demand for the “smarter grid”. First, this dissertation proposes the dynamic modeling technique and operational strategies for a sustainable microgrid primarily powered by wind and solar energy resources. Multiple-input dc-dc converters are used to interface the renewable energy sources to the main dc bus. The intended application for such a microgrid is an area in which there is interest in achieving a sustainable energy solution, such as a telecommunication site or a residential area. Wind energy variations and rapidly changing solar irradiance are considered in order to explore the effect of such environmental variations to the intended microgrid. The proposed microgrid can be operated in an islanded mode in which it can continue to generate power during natural disasters or grid outages, thus improving disaster resiliency of the “smarter grid”. In addition, this dissertation presents the spatial and temporal model of electric vehicle charging demand for a rapid charging station located near a highway exit. Most previous studies have assumed a fixed charging location and fixed charging time during the off-peak hours for anticipating electric vehicle charging demand. Some other studies have based on limited charging scenarios at typical locations instead of a mathematical model. Therefore, from a distribution system perspective, electric vehicle charging demand is still unidentified quantity which may vary by space and time. In this context, this study proposes a mathematical model of electric vehicle charging demand for a rapid charging station. The mathematical model is based on the fluid dynamic traffic model and the M/M/s queueing theory. Firstly, the arrival rate of discharged vehicles at a charging station is predicted by the fluid dynamic model. Then, charging demand is forecasted by the M/M/s queueing theory with the arrival rate of discharged vehicles. The first letter M of M/M/s indicates that discharged vehicles arrive at a charging station with the Poisson distribution. The second letter M denotes that the time to charge each EV is exponentially distributed, and the third letter s means that there are s identical charging pumps at a charging station. This mathematical model of charging demand may allow grid’s distribution planners to anticipate charging demand at a specific charging station. / text

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Large-scale electrochemical energy storage is a technology that is uniquely suited to integrate intermittent renewable energy sources with the electric grid on a large scale. Grid-based energy storage also has the potential to reduce costs associated with periods of peak electric demand. For these reasons, this work describes the potential applications for grid-based energy storage, and then reviews large-scale energy storage technology innovations since the development of the lead-acid battery. The potential value of grid-based battery energy storage is discussed in the context of restructured electricity markets; then, a dynamic model-based economic optimization routine is developed to gauge the potential value of a vanadium redox flow battery (VRFB) operating for wholesale energy arbitrage and frequency regulation in Texas. Based on this analysis, the relative value of a VRFB in various regions of Texas for energy arbitrage and frequency regulation is examined. It is shown that frequency regulation is an appealing application for a grid-based VRFB, with a VRFB utilized for frequency regulation service in Texas potentially worth approximately $1500/kW. Finally, the effect of a VRFB’s characteristics on its value for frequency regulation and energy arbitrage are compared, and the operational insight developed in this work is used to glean how policies to integrate a large-scale energy storage with the electricity market might be crafted. / text

Since the inception of the Masdar Initiative in 2006, the Emirate of Abu Dhabi has invested a considerable amount of resources to promote renewable sources of energy like solar and wind. With an aim of achieving 7% of its electricity from renewable sources by the year 2020, there is much that the emirate needs to do in order to reduce its reliance on hydrocarbons while still planning capacity for future electricity demand. This report explores the effectiveness of a smart grid infrastructure as a mechanism to afford the flexibility and functionality required to incorporate renewable energy sources into the electric grid, as well as leveraging a real-time data network to attain reductions in peak demand consumption. Specific regulatory structures that exist in Abu Dhabi's electric and telecommunications markets are evaluated to understand the role they will play in dealing with interoperability standards, privacy concerns, and consumer participation issues that influence the effective integration of smart grid into Abu Dhabi's energy future. / text

In the Electric Reliability Council of Texas (ERCOT) compressed air energy storage (CAES) is currently viewed as the most promising energy storage technology due to Texas having suitable geology for CAES and few locations suitable for pumped-hydro storage. CAES is a proven technology but the economics for new facilities are uncertain. This work quantified the economic prospects for CAES in ERCOT as a function of installed wind capacity, natural gas price, and CAES capital cost. Two types of models were developed and used in this work. The first type of model was a CAES dispatch optimization model, which determined the maximum operating profits a CAES facility could earn given a set of electricity and ancillary services market prices. These models were used to examine several separate research questions relating to the maximum potential for CAES and the impact of uncertainty and other real-world complications. The models determined that the maximum operating profit from 2002-2010 varied widely from year to year and averaged $120-140/kW-year, which is likely below the operating profits required to justify investing in CAES. The models also determined that current price forecasting methods are sufficient to earn approximately 95% of the operating profits achievable with perfect knowledge of all prices in the year. The second type of model was a unit commitment model of ERCOT, which determined the least-cost operation of all the generators in the generation fleet to meet given load. The unit commitment model was used to determine electricity and ancillary service market prices under different assumptions about natural gas price, installed wind capacity, and installed CAES capacity. The CAES dispatch optimization model was then used to determine the operating profits of a CAES facility under these scenarios. CAES operating profits were found to increase with increasing natural gas price and installed wind capacity and to decrease with increasing installed CAES capacity. CAES operating profits were estimated to support installed CAES capacities from zero to more than 6 GW, depending on the natural gas price, installed wind capacity, installed CAES capacity, and the CAES capital costs. The strongest determinant of the maximum CAES capacity that would be profitable is the natural gas price, followed by the CAES capital costs. / text

Future smart grid systems will intelligently monitor and control energy flows in order to improve the efficiency and reliability of power delivery. This monitoring and control requires low-power, low-cost and highly reliable two-way communications between customers and utilities. To enable these two-way communication links, powerline communication (PLC) systems are attractive because they can be deployed over existing outdoor and indoor power lines. Power lines, however, have traditionally been designed for one-directional power delivery and remain hostile environments for communication signal propagation. In particular, non-Gaussian noise that is dominated by asynchronous impulsive noise and periodic impulsive noise, is one of the primary factors that limit the communication performance of PLC systems. For my PhD dissertation, I propose transmitter and receiver methods to mitigate the impact of asynchronous impulsive noise and periodic impulsive noise, respectively, on PLC systems. The methods exploit sparsity and/or cyclostationarity of the noise in both time and frequency domains, and require no or minor training overhead prior to data transmission. Compared to conventional PLC systems, the proposed transceivers achieve dramatic improvement (up to 1000x) in coded bit error rates in simulations, while maintaining similar throughput. / text