The consumption of electricity is seen by society as a certainty and not an uncertainty; however, there are several uncertainties about how the topology of the electrical grid will look in the future. For instance, it is expected that the demand for electricity is set to considerably increase, there will be a greater incorporation of renewable generation sources, and society will call for a decrease in the spatial footprint of the electrical power grid. To address these uncertainties, new technology has been proposed to replace the conventional copper devices currently utilized. One of the new technologies that has shown great promise over the last decade are superconducting power devices. The appeal of superconducting technology lies in its ability to operate at significantly higher current densities than equivalently sized copper or aluminum technologies. This increase in current density will potentially allow for the electrical power grid to operate at higher capacity and greater efficiency. In order to develop superconducting devices for high power applications, knowledge of the critical boundaries with regards to temperature, current and magnetic field need to be studied. High-voltage engineering principles also need to be studied in order to ensure that an optimal design is produced for the superconducting power device. These theoretical and practical challenges of designing superconducting power devices are discussed in Chapter 1. Chapter 2 focuses on the high-voltage engineering and dielectric design aspects of a specific superconducting power device: HTS power cables. In particular, this chapter discusses the different dielectric design topologies, cable layouts, and reviews successfully demonstrated HTS power cables. One of the current limitations of designing superconducting power devices is the lack of dielectric materials compatible with cryogenic temperatures, and this area has been the focus of my research. The main focus of my Ph.D. is the investigation of new cryogenic dielectric materials and designs, which can be separated into two main areas. The cryogenic studies on increasing the dielectric strength of gaseous helium (GHe) focused on the addition of a small mol% of various gases such as nitrogen (N2), hydrogen (H2) and neon (Ne) to GHe (Chapter 4). The studies to increase partial discharge inception voltage of GHe cooled high temperature superconducting (HTS) power cables focused on using a Polyethylene Terephthalate heat shrink to individually insulate HTS tapes (Chapter 6), as well as the development of a novel HTS cable design referred to as the Superconducting Gas-Insulated Transmission Line (S-GIL) (Chapter 7). While the research conducted can be split into different categories, the experimental techniques in preparing samples and performing measurements are consistent and are discussed in Chapter 3. From completing this research, several key findings were discovered that will help advance the development of GHe cooled superconducting devices. Here is a summary of these discoveries: • The addition of 4 mol% of hydrogen gas to GHe increases the dielectric strength by 80% of pure GHe for all pressures. This trend was seen with both AC and DC voltages and DC breakdown strengths were approximately 1.4 times higher than the AC, as expected. • By measuring the breakdown strength of 1, 2, and 4 mol% hydrogen gas mixed with GHe, a linear relationship exists between hydrogen mol% and breakdown strength. The saturation limit does not appear to have been reached, so there is potential for higher breakdown strengths with higher hydrogen mol%. However, there are potential safety concerns with regards to flammability that need to be considered for higher mol% hydrogen mixtures. • Tertiary mixtures containing 8 mol% nitrogen gas, and 4 mol% hydrogen gas mixed with GHe yielded approximately a 400% increase in the dielectric strength when compared to GHe. With the introduction of the nitrogen gas to the mixture the maximum operating pressure was limited to approximately 0.85 MPa before condensation occurred. • The partial discharge inception voltage (PDIV) measurements for a cable measured in the 4 mol% hydrogen mixture and then in GHe showed a 25% higher value when the cable was measured in the 4 mol% hydrogen mixture than in GHe. This improvement in PDIV is not as great as the 80% improvement seen in the breakdown measurements. • The Polyethylene Terephthalate heat shrink selected to provide individual insulation to HTS tapes did not allow for a high operational voltage when used as the insulation method for a HTS cable as breakdown occurred between 1-2 kV. • The development of the S-GIL allows for the full benefits of increasing the dielectric strength of GHe to be exploited. • The S-GIL will allow for higher operating voltages and better thermal characteristics than currently available for GHe superconducting power cables. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the Doctor of Philosophy. / Summer Semester 2017. / June 8, 2017. / Dielectric, Gaseous Helium, High Temperature Superconductor, High Voltage / Includes bibliographical references. / Sastry Pamidi, Professor Directing Dissertation; Juan Ordonez, University Representative; Chris Edringtion, Committee Member; Lukas Graber, Committee Member; Simon Foo, Committee Member.

In Power Hardware-In-The-Loop (PHIL) simulations, it is important to understand the impedance characteristics of the system being tested. These impedances are used in the assessment of both the stability and the accuracy of the PHIL simulation experiment, as well as for stability analyses for the integration of the device under test (DUT) into the eventual system of deployment. When testing medium voltage systems in the megawatt power range, sensor noise stemming from the switching amplifiers can become quite an issue. This thesis evaluates four different impedance measurement techniques to find a reliable, accurate, and quick assessment over a wide frequency range in the noisy environments of medium voltage systems. (1) a single tone consisting of one sine wave at a single frequency, (2) a multitoned signal which is the sum of multiple sine waves, each at a unique frequency, (3) a frequency-swept sine wave, also known as a “chirp”, and (4) a pseudorandom binary sequence. Each of these signals are injected into the system while energized in order to measure the response, which is then processed for the impedance characteristics. Various tests are conducted to simulated systems with simulated sensor noise to determine the viability of each of the techniques. Once the techniques are determined to be appropriate signals for system characterization in noisy medium voltage systems, they will be applied to a simulated Multilevel Modular Converter (MMC) model. The data from the simulated model will then be verified with a hardware experimental verification test with the viable signals chosen. / A Thesis submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2018. / July 12, 2018. / Includes bibliographical references. / Hui Li, Professor Directing Thesis; Michael Steurer, Committee Member; Ming Yu, Committee Member.

Recently, the smart grid technologies have been developed rapidly recently, which an important component is the so called demand response management (DRM). With the help of a DRM program, a utility company can adjust the power demand and electricity price to reduce the cost of power generation and consumption. However, there are many problems in DRM need to be solved. For example, to solve the problem of optimizing a generator's power (GP), the conventional methods such as economic dispatch (EDP) may reduce the profit of the utility company. To solve the problem of optimizing a consumer's power (CP), the existing smart pricing strategies may reduce the long-term benefits of the customers. This dissertation aims to develop a two-stage game model to increase the profit of the utility company and while increase the long-term benefit of the customers. For solving the GP. It is critical for the power generator and utility company to allocate the power demand properly, but the profit for the utility company may be reduced. To solve the CP, it is difficult for the customers to achieve a long-term beneficial power-usage-pattern with myopic pricing strategies. The stability of the smart grid and the benefit of the customers may also be reduced due to the myopic pricing strategies. It is difficult for the utility company to use the existing methods (e.g., EDP) to order an optimal power demand from the power generators to earn the maximum profit. There are two issues that are needed to be solved in the GP. First, the weight function for the utility company and power generators in the GP is not established properly in the existing methods. For example, the value of the weight function for the utility company and power generators are usually the same in an EDP method. However, in a smart grid, the utility company has the privilege to demand the power while the power generators must follow the demand. Hence the value of weight function for the utility company should be greater than the one for the power generators in a GP. Second, the optimal demand for the utility company is most likely not the optimal generation for the generators. The imbalanced power will increase the generation cost significantly. It is also difficult for a utility company to maintain an efficient DRM for a long-time period by using the existing smart pricing strategies. Applying incentive is the major solution for the utility company to influence the power demand of a customer. However, the traditional pricing strategies are shortsightedly designed, by which the long-time efficiency for the DRM is reduced. For example, the trigger punishment strategy applies a punishing price to a customer for a long period when a non-cooperation behavior is detected. During the punishment period, the customer chooses its power consumption freely since the punishment will be applied anyway. Such selfish behaviors reduce the long-term efficiency for the DRM and the stability of the smart grid. In this dissertation, we propose a two-stage game model to solve the GP and CP to increase the long-term efficiency for the DRM, maintain the stability of the smart grid, and also increase the profit of the utility company. In the first stage, a Stackelberg game model is applied to solve the GP, in which the utility company is the leading player while the generators are the following players. We prove that the GP for the following players is a convex problem mathematically. The following players achieve the Nash equilibrium (NE) state by choosing the unique optimal generation. The leading player reacts with this unique generation to achieve the optimal profit. Both the leading and following players reach an agreement in the NE state, in which they have no motivation to deviate the optimal actions. A genetic algorithm is developed to obtain the optimal demand for the leading and following players. In addition, we introduce a power balance constraint to the leading and following players to avoid the cost caused by the imbalanced power. By applying the constraint, the generated power is equal to the demand all the time. The smart grid will not need to store the excessive power in the energy storage unit or send the power back to the power generators to keep them idling. The cost is avoided and the efficiency of the DRM is increased. In the second stage, a repeated game model is applied to solve the CP, in which the customers are the players. The strategy for the players is to minimize the individual power consumption of each customer. The utility function for the players is the cost of the customers. The objective for the players is to minimize the cost. In this work, we prove that the NE state exists for the repeated game. However, it has been shown that in the NE state, the players' myopic behaviors may reduce the benefits for the entire group of players. To avoid the loss, we use a genetic algorithm to find the Pareto-efficient solution for the players, in which no player can increase its benefit by reducing other players' benefit. We apply a Tit-for-Tat (TFT) smart pricing strategy to increase the punishment strength from the utility company. Once an irrational behavior from a player is detected, a punishment will be applied to the player for a short period of time. The player can choose to cooperate or not during the punishment period. Compared to the existing smart pricing strategies, the long-term benefit for the smart grid is increased by applying the TFT strategy to the customers. The numerical simulations in different scenarios are conducted to evaluate the performance of the proposed two-stage game framework by using MATLAB. All the parameters and constraints of the related components are from the Department of Energy's report and the Oasisui online database. Five power generators, one utility company, and one hundred customers have been used in the simulations. Compared with the existing solutions (e.g., EDP and gaming optimization), the cost in power consumption is reduced by 6% percent while the profit for power generation is increased by 8% percent in our test scenarios. With the help of the proposed model, we enhance the efficiency for the DRM. The peak-to-average ratio (PAR) of the power demand of our work is compared with the EDP method. The effect of the PAR is studied. The numerical results show that the proposed model has a similar PAR to that of the EDP method, which implies that the proposed model has no negative influence on the stability of the smart grid. The punishing effort of the TFT strategy is compared with the trigger strategy (TP) to study the punishment influence on the customers. The numerical results show that the customers who are applied with the TFT strategy are more willing to cooperate with the utility company. The impact of the power loss ratio and different types of customers is also simulated and analyzed. The simulation results show that the players with a greater transmission loss ratio are more willing to cooperate. The customers that are associated with a greater linear dissatisfaction coefficient are more concerned about the dissatisfaction cost. The customers with greater price-sensitive coefficients are more concerned about the consumption cost. In summary, compared to the existing solutions, the proposed two-stage game model improves the performance of the DRM while maintain the stability of the smart grid. We also discuss the future research issues in the related areas. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / May 8, 2018. / Includes bibliographical references. / Ming Yu, Professor Directing Dissertation; Xiuwen Liu, University Representative; Leonard Tung, Committee Member; Petru Andrei, Committee Member.

Weather and Air quality monitoring are very important aspects of smart city management. As population increase in the cities, the emission of pollutants includes Carbone Monoxide, Nitrogen Dioxide, Ozone and the Particulate matter will increase which will cause health and environmental issue. This paper is about developing a low-cost Urban sensors box based on Internet of Things. The Urban box is equipped with 4G/3G wireless communication which allows the wide range of mobility around the city. The Urban Sensor box is a collaborative work to monitor real-time data of the city’s environment, infrastructure, and activities. All these data will be provided to understand the interconnected behavior of different tangible networks of the urban environment. / A Thesis submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2018. / July 19, 2018. / Internet of things, sensors, smart city, wireless network / Includes bibliographical references. / Reza Arghandeh, Professor Directing Thesis; Sastry Pamidi, Committee Member; Simon Y. Foo, Committee Member.

Future Naval vessels are looking to incorporate a new variety of electrical loads. These loads include rail guns, high power radars, electric propulsion drives, and lasers. These loads, especially the rail gun, can be classified as high-power ramp rate loads. Before now, these types of loads were not prevalent on naval vessels; therefore, generators were used throughout the ship to power a multitude of devices that did not require high-power ramp rates. Many of the generators had a specific purpose; there were no interconnections between generators. With these new types of loads, a power system that can accommodate these devices is needed. Integrated Power Systems (IPS) look to solve the high-power ramp rate issue as well as provide a multitude of benefits such as efficiency, resiliency, and reconfigurability. The generators, loads, energy storages, protections, etc. will all be located and connected within the IPS. The IPS can provide the foundation to achieve a multitude of benefits; however, the control system must be intelligent in order to realize the IPS’ full potential. Part of the control problem is how to manage sources and loads to ensure load demand is met. In terrestrial systems, the near infinite bus takes care of changes in load demand. In a microgrid, such as those found on ships, a large change in load demand, such as those seen by high-power ramp rate loads, can have adverse effects on the power system and devices connected to the power system. The control must coordinate the sources and/or loads to ensure load demand is met with minimal impact to the system. In this dissertation, the beginnings of a distributed Energy Management control layer are shown. The control layer looks to assist in realizing the IPS’ full potential. This is done by providing a distributed type of control to fortify the resiliency and reliability, ensuring load demand is met, and certifying the energy storages state of charge is maintained to ensure an ever-ready presence. This control layer aims to meet load demand, ensure device constraints (power ratings, ramp rate limitations, etc.) are not exceeded, and maintain the energy storages desired state of charge. The control objective is met through a combined approach of a distributed spinning reserve algorithm and distributed MPC. The distributed MPC utilizes the distributed optimization technique called the Alternating Direction Method of Multipliers (ADMM). / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 20, 2018. / Distributed Control, Energy Management, Energy Storage, Model Predictive Control, Naval / Includes bibliographical references. / Jonathan Clark, University Representative; Omar Faruque, Committee Member; Sastry Pamidi, Committee Member.

The current trend for naval destroyer-class ships is the move toward DC distribution systems as the next generation of ships is developed. The main motivation for using DC is to increase the power density of the ships to accommodate advanced weaponry such as the electromagnetic railgun. The distribution systems are also expected to be modular and plug-n-play in nature, leading toward a distributed control scheme to integrate the distributed sources and loads that could be online at any given time. One of the main performance requirements for the future power distribution systems is the ability to accurately share power among the distributed resources on the ship, while also maintaining the voltage stability of the distribution system, often referred to as power management. The primary candidate to accomplish the power management of the ship systems is droop control. Droop control has been extensively studied for terrestrial applications for sharing power between paralleled sources. Specifically, its application to DC microgrids is of interest since islanded microgrids have similar properties to ship systems. In these studies, it has been shown that conventional droop control is limited in its power sharing capabilities due to a tradeoff between the accuracy of the power sharing between devices and the regulation of the bus voltage. Secondary controllers have been proposed to modify the droop control scheme to alleviate these issues based on linear controllers or heuristic methods. However, accurate models for DC microgrids are difficult to derive for linear control design, and heuristic methods do not present an autonomous way to adjust the parameters of the controller. Therefore, adaptive control is proposed to adjust the droop controller’s parameters in an online fashion to find the optimal values based on the system conditions. Model reference adaptive control is chosen in this research for its ability to deal with system uncertainties and ensure stability. Specifically, combined model reference adaptive control is chosen for its improvements in transient response and robustness over the direct and indirect versions. The method is developed and simulated using MATLAB/Simulink to determine the performance of the algorithm. Additionally, a notional MVDC ship power system is developed in the same environment to provide a test system with various distributed sources and loads. A load profile is developed for the main system components such as propulsion, service loads, and the advanced weaponry to reflect a notional battle scenario. The algorithm is first tested in simulation, and then deployed to external distributed controllers to validate the performance of the power management scheme under hardware constraints and communication latency. The algorithm is also demonstrated in conjunction with a management layer for distributed energy storage modules throughout the ship system to further illustrate the real-world viability of the method. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 19, 2018. / Includes bibliographical references. / Chris S. Edrington, Professor Directing Dissertation; Juan Ordonez, University Representative; Simon Foo, Committee Member; Pedro Moss, Committee Member.

In large-scale power systems, the integration of intelligent monitoring system increases the system resiliency and the control robustness. For example, sensor monitoring allows to automatically supervise the health of sensors and detect sensor failures without relying on hardware redundancy, and hence, it will further reduce the cost of monitoring systems in power systems. Sensor failure is critical in smart grids, where controllers rely on healthy measurements from different sensors to determine all kinds of operations. Current literature review shows that most of the researchers focus on control and management side of smart grids, assuming the information control centers or agencies get from sensors is accurate. However, when sensor failure happens, missing data and/or bad data can flow into control and management systems, which may lead to potential malfunction or even power system failures. This brings the need for Sensor Fault Detection and Isolation (SFDI), to eliminate this potential threat. The integration of the SFDI into monitoring systems will allow avoiding the contingencies due to fault data, and therefore increases the system resiliency and the control robustness. Hardware redundancy is the common solution for SFDI. By placing multiple sensors in the same position, the control center can then rely on redundant sensors when one is broken or inaccurate. Apparently, this method will increase the cost significantly when applying to large power systems. Analytical redundancy, on the contrary, a quantitative method built from power system models, is a more promising solution. It does not necessarily require hardware redundancy and hence can lower the cost. With an appropriate number of sensors placed in strategic locations, the algorithm can then automatically detect sensor failures without the need of extra redundant sensors. Furthermore, SFDI together with intelligent sensor optimization and placement will also facilitate the transfer of conventional central grid control to distributed decision making agencies with minimum computation and communication burden for each branch, and thus, it will enhance the system performance and resiliency. In this dissertation, a comprehensive review over the state-of-the-art FDI methodologies is given at first, then a proposed algorithm to determine the optimal location of computation agents is introduced, which serves as a guide for the SFDI algorithm implementation explained right after. The results of the algorithms indicated promising application in power system monitoring. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 19, 2018. / communication cost, computation agent, computation cost, distributed computation, optimal location, sensor fault / Includes bibliographical references. / Chris S. Edrington, Professor Directing Dissertation; Juan C. Ordóñez, University Representative; Pedro Moss, Committee Member; Simon Foo, Committee Member.

Nowadays the medium-voltage dc system (MVDC) has been proposed in the renewable energy collector fields, long distance power transmission, small-scale industrial networks and all-electric shipboards due to its relatively higher efficiency, higher flexibility and lower cost in certain applications compared to the ac grid. Batteries offer scalable energy storage solutions in these applications for high-power and long-term energy demands with high energy density. Batterers play an essential role to smooth the power fluctuations and stabilize the grid as well. As the interface between battery energy storage and MVDC bus, the battery energy storage system (BESS) converter is a key enabling technology with specific requirements. Due to the lack of mature dc circuit breakers, the BESS converter is desired to achieve superior dc fault response which benefits the MVDC system reliability and resiliency. In addition, considering the high expenses and limited lifetime of nowadays battery products, multiple services and functions are preferred for BESS. In this research, the isolated modular multilevel dc/dc converter (iM2DC) based BESS is proposed. It can achieve both fault current limiting and fault ride through functions with direct dc current control capability, so it is possible to maintain the system operation during fault to ensure fault localization and fast recovery. Besides, via the virtual impedance method, the proposed topology employs the converter cell capacitors rather than batteries to provide the ripple energy to achieve the active power filter (APF) function, which allows the energy storage system to improve MVDC system power quality without consuming battery lifetime or extra circuits. In addition, since the medium-frequency transformer operation frequency can be as high as the converter switching frequency, the whole system power density will be improved. A controller hardware-in-the-loop testbed, which consists of the iM2DC based BESS model simulated in the real-time digital simulator (RTDS) and the multifunctional control programmed in the ABB controller products, is utilized to validate the functionality of proposed technology. Furthermore, the system efficiency of proposed BESS is not most optimized with the sinusoidal modulation. Therefore, in this research, a novel phase-shifted square wave modulation strategy is proposed for iM2DC. Compared to the conventional modulation methods, the proposed technique achieves reduced dc inductance due to higher equivalent switching frequency. In addition, the required capacitor energy can be minimized, which decreases the capacitor size without sacrificing the total device rating. Detailed principles of the proposed modulation and passive components design are presented. A downscaled 2kW prototype is built in the lab and the experimental results are provided to demonstrate the proposed modulation strategy. Finally the dissertation work is summarized and the scope of future work is discussed. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2017. / November 17, 2017. / battery energy storage system, high/medium voltage dc grid, isolated modular multilevel dc/dc converter / Includes bibliographical references. / Hui Li, Professor Directing Dissertation; Juan C. Ordonez, University Representative; Thomas A. Lipo, Committee Member; Chris S. Edrington, Committee Member; Michael Steurer, Committee Member.

In undersea remote sensing change detection is the process of detecting changes from pairs of multi-temporal sonar images of the seafloor that are surveyed approximately from the same location. The problem of change detection, subsequent anomaly feature extraction, and false alarms reduction is complicated due to several factors such as the presence of random speckle pattern in the images, variability in the seafloor environmental conditions, and platform instabilities. These complications make the detection and classification of targets difficult. This thesis presents the first successful development of an end-to-end automated seabed change detection using multi-temporal synthetic aperture sonar (SAS) imagery that include a false detection/false alarms reduction based on principal and independent component analysis (PCA/ICA). ICA is a well-established statistical signal processing technique that aims to decompose a set of multivariate signals, i.e., SAS images, into a basis of statistically independent data-vectors with minimal loss of information content. The goal of ICA is to linearly transform the data such that the transformed variables are as statistically independent from each other as possible. The changes in the scene are detected in reduced second or higher order dependencies by ICA. Thus removing dependencies will leave the change features that will be further analyzed for detection and classification. Test results of the proposed method on a data set of SAS images (snippets) of declared changes from an automated change detection (ACD) process will be presented. These results illustrate the effectiveness of component analysis for reduction of false alarms in ACD process. In the context of sea surface object detection, this thesis investigates bistatic radar engagement using synthetic aperture radar (SAR) and examines five models of the bistatic electromagnetic scattering that will support future research on SAR sea-surface change detection. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2017. / November 21, 2017. / ACD, CCD, Change detection, Electromagnetic scattering, ICA, synthetic aperture sonar / Includes bibliographical references. / Rodney G. Roberts, Professor Directing Dissertation; Anke Meyer-Baese, University Representative; Uwe H. Meyer-Baese, Committee Member; Simon Y. Foo, Committee Member.

Power hardware-in-the-loop (PHIL) simulation is a technique whereby actual power hardware is interfaced to a virtual surrounding system through PHIL interfaces making use of power amplifiers and/or actuators. PHIL simulation is often an attractive approach for early integration testing of devices, allowing testing with unrealized systems with substantial flexibility. However, while PHIL simulation offers a number of potential benefits, there are also a number of associated challenges and limitations stemming from the non-ideal aspects of the PHIL interface. These can affect the accuracy of the experiments and, in some cases, lead to instabilities. Consequently, accuracy, stability, and sensitivity to disturbances are some of the most important considerations in the analysis and design of PHIL simulation experiments, and the development of PHIL interface algorithms (IA) and augmentations for improvements in these areas is the subject of active research. Another area of research sharing some common attributes with PHIL simulation is the field of robotic bilateral teleoperation systems. While there are some distinctions and differences in characteristics between the two fields, much of the literature is also focused on the development of algorithms and techniques for coupling objects. A number of disparate algorithms and augmentations have also been proposed in the teleoperation literature, some of which are fundamentally very similar to those applied in PHIL simulation. While some of the teleoperation methods may have limited applicability in PHIL experiments, others have substantial relevance and may lend themselves to improvements in the PHIL application area. This work focuses on the application and analysis of a teleoperation framework in the context of PHIL simulation. The extended Lawrence Architecture (ELA) is a framework unifying and describing a large set of teleoperation interfacing algorithms. This work focuses on the application and analysis of the ELA to PHIL simulation. This includes the expression of existing PHIL IAs in the context of the ELA, derivation of relevant transfer functions and metrics for assessment of performance, the exploration of the implications of the transparency requirements, and the exploration of new IAs supported by the ELA which may be well suited to the particular characteristics of PHIL simulation. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2018. / March 9, 2018. / Power Systems, Simulation / Includes bibliographical references. / Chris S. Edrington, Professor Directing Dissertation; Omer Arda Vanli, University Representative; Michael Steurer, Committee Member; Rodney G. Roberts, Committee Member; Md Omar Faruque, Committee Member.