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Title: A Novel In-Situ Method for Inhibiting Surface Roughening during the Thermal Oxide Desorption Etching of Silicon and Gallium Arsenide.
Creator: Pun, Arthur Fong-Yuen, Zheng, Jim. P., Gielisse, Peter J., Perry, Reginald J., Foo, Simon Y., Xin, Yan, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: A method inhibiting surface roughening of silicon and gallium arsenide wafers during the thermal desorption of their native oxide layers is proposed and tested experimentally, with silicon results indicating a 75% reduction in surface roughness from an averaged value of 2.20 nm to 0.56 nm, and gallium arsenide results indicating a 76% reduction from an averaged surface roughness of 1.6 nm to 0.4 nm. This method does not significantly alter the semiconductor crystalline surface, thus retaining...
Show moreA method inhibiting surface roughening of silicon and gallium arsenide wafers during the thermal desorption of their native oxide layers is proposed and tested experimentally, with silicon results indicating a 75% reduction in surface roughness from an averaged value of 2.20 nm to 0.56 nm, and gallium arsenide results indicating a 76% reduction from an averaged surface roughness of 1.6 nm to 0.4 nm. This method does not significantly alter the semiconductor crystalline surface, thus retaining suitability for subsequent epitaxial growth, as demonstrated experimentally. The method is readily implementable in currently utilized deposition systems, subject to the requirements of material growth, substrate heating, and producing a non-oxidizing environment, either inert atmosphere or reduced pressures. The technique involves depositing a thin sacrificial film directly onto the native oxide surface at lower temperatures, of which the thickness is dependent on both the native oxide thickness and the oxide stochiometry initially present within the oxide layer, but has been found experimentally to be on the order of 0.5 nm – 4 nm for a 2 nm to 4 nm air-formed native oxide layer. Upon heating this structure to high temperatures, the native oxide preferentially reacts with the sacrificial deposited film instead of the bulk wafer, resulting in the chemical reduction to volatile components, which are evaporated at these temperatures. This method is developed for silicon and gallium arsenide and examined experimentally utilizing atomic force microscopy and reflection high-energy electron diffraction. Different native oxide preparation techniques are theorized to yield varying chemical stochiometries, with experimental results elucidating information regarding these differences. Further, a modified tri-layer implementation, in which the deposited film is re-oxidized, is tested for applicability as a novel wafer pacification technique.
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Date Issued: 2005
Identifier: FSU_migr_etd-0474
Format: Thesis

Title: Study of Correlations Between Microwave Transmissions and Atmospheric Effects.
Creator: Stringer, Andrew James, Foo, Simon Y., Yu, Ming, Harvey, Bruce A., Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Understanding the effects of atmospheric conditions with respect to microwave propagation and performance is critical to the design and placement of microwave antennas for modern communication systems. Weather data acquisition in the state of Florida is underdeveloped and the published effects of weather on microwave communications are limited to general models based on large regional climate models. The goal of this research is to correlate atmospheric conditions and microwave transmission...
Show moreUnderstanding the effects of atmospheric conditions with respect to microwave propagation and performance is critical to the design and placement of microwave antennas for modern communication systems. Weather data acquisition in the state of Florida is underdeveloped and the published effects of weather on microwave communications are limited to general models based on large regional climate models. The goal of this research is to correlate atmospheric conditions and microwave transmission via the existing Florida Department of Transportation (FDOT) Road Weather Information System (RWIS) network, new Environmental Sensor Station (ESS) sites, and Harris Corporation network management software – Netboss. The microwave radios in the FDOT microwave infrastructure through powerful Netboss scripting tools and options are utilized to record the received signal level (RSL) output of the microwave radios for signal analysis. This RSL data is analyzed and correlated with the acquired ESS weather data to determine basic atmospheric effects on microwave propagation. Methods for analysis of correlated data include existing atmospheric attenuation models, such as the Global (Crane) and International Telecommunications Union (ITU) models, and empirical methods such as the Fast Fourier Transform (FFT), Short Time Fourier Transform (STFT), Discrete Wavelet Transform (DWT) and wavelet decomposition, and correlation analysis of each method used. The data is treated as a discrete non-stationary signal. Results do not show a clear correlation between receiver signal level (RSL) and weather parameters for several of the test methods. Testing the correlation and cross correlation of the raw data yielded weak correlation. The simulation of rain attenuation via the ITU model displayed weak insignificant results for the sets of RSL data. The FFT and STFT both incorporate too much noise and distortion to accurately compute a correlation. Wavelet decomposition shows a strong correlation between several weather parameters and a weak correlation for others. This result confirms the wavelet decomposition analysis and agrees with trends found in the RSL and weather parameters. Further analysis points to multipath fading and atmospheric ducting. During early hours of the morning, reflections from moist surfaces, such as tree foliage and other terrestrial objects, water vapor and dew will cause transmitted signals to reach the receive antenna out of phase, which will cause attenuation or gain while atmospheric ducting will cause gain in the RSL and is visible in the acquired data. It is concluded that weather conditions such as water vapor, mist, and rising fog have an effect on microwave propagation.
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Date Issued: 2010
Identifier: FSU_migr_etd-0396
Format: Thesis

Title: Evaluation and DSP Based Implementation of PWM Approaches for Single-Phase DC-AC Converters.
Creator: Zhou, Lining, Chang, Jie J., Zheng, Jim P., Roberts, Rodney G., Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Switching-mode single-phase DC-AC converters have been widely used in critical applications such as uninterrupted power supply systems and AC motor drivers. Among various control techniques, Pulse Width Modulation (PWM) technique is the most effective one that is commonly used to regulate the magnitude and frequency of the converter's output voltage. With recent revolution in the Digital Signal Processing (DSP) technology, the trend of converter control is moving to DSP based real-time...
Show moreSwitching-mode single-phase DC-AC converters have been widely used in critical applications such as uninterrupted power supply systems and AC motor drivers. Among various control techniques, Pulse Width Modulation (PWM) technique is the most effective one that is commonly used to regulate the magnitude and frequency of the converter's output voltage. With recent revolution in the Digital Signal Processing (DSP) technology, the trend of converter control is moving to DSP based real-time digital control system. Digital control has the advantage of low cost with increased flexibility and accuracy. In this thesis, three open-loop PWM control schemes are evaluated and compared in both time domain and frequency domain. Theoretical analysis and spectrum evaluation have been completed. Digital simulation is conducted for each of the control schemes to verify the theoretical analysis. Experimental implementation based on a TMS320F2812 DSP is presented and finally system experimental results are demonstrated.
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Date Issued: 2005
Identifier: FSU_migr_etd-0519
Format: Thesis

Title: A Framework for Implementing Independent Component Analysis Algorithms.
Creator: Ejaz, Masood, Foo, Simon Y., Meyer-Baese, Anke, Liu, Xiuwen, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Independent Component Analysis (ICA) is a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. ICA defines a generative model for the observed multivariate data, which is generally given as a large database of samples. In the model the data samples are assumed to be linear or non-linear mixture of some unknown latent variables (time dependent or independent), and the mixing system is also unknown. The latent...
Show moreIndependent Component Analysis (ICA) is a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. ICA defines a generative model for the observed multivariate data, which is generally given as a large database of samples. In the model the data samples are assumed to be linear or non-linear mixture of some unknown latent variables (time dependent or independent), and the mixing system is also unknown. The latent variables, if time-independent, are assumed to have a non-gaussian distribution. For variables that have a particular time structure, the non-gaussian distribution condition can be alleviated. Also, the latent variables are assumed to be mutually independent. These variables are called the independent components of the observed data and can be found, up to some degree of accuracy, using different algorithms based on ICA techniques. There are several algorithms based on different approaches for ICA widely in use for all sort of applications. These algorithms include, but not limited to, the popular FastICA, FOBI (Fourth-Order Blind Identification) & JADE (Joint Approximate Diagonalization of Eigen-Matrices), Maximum Likelihood & Infomax, Kernel based algorithms, SOBI (Second-Order Blind Identification) etc. All the algorithms except SOBI are used for time-independent data. The main purpose of this research is to create a framework for using different ICA algorithms. In other words to analyze the statistical properties of the data to estimate which ICA algorithm will be best suited for that type of data or which ICA algorithm will converge for the specific type of data. The data to be analyzed can come from any application or source, although for our research we have generated a large number of different datasets with random mixtures of different number of random variables that follow a number of different distributions. The idea is to make a system that takes the data and yields some characteristics or specifications of the data that correlates maximally to some specific type of ICA algorithm or algorithms. Four different ICA algorithms have been used for this research: FastICA based on the optimization of negentropy of the datasets, Infomax based on the maximum likelihood of the datasets, Joint Approximate Diagonalization of Eigenvalues (JADE) based on the fourth-order cumulant tensor of the input data, and finally Kernel ICA based on the optimization of canonical correlation of the mapped values of the input datasets in the kernel space. We used hundreds of datasets to study the errors generated by all the methods and the correlation between the datasets and the methods and found out some very interesting results to show that for some specific parameters of ICA algorithms, one can estimate, with high probability, the relationship between the statistics of the datasets and the approach to be used to find the independent components. The statistics, easy to employ, can predict with high accuracy the ICA method or methods to be used for some specific dataset without actually dealing with all the ICA methods and thus saving quite a bit of time and processing resources, hence increasing the efficiency of the researcher.
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Date Issued: 2008
Identifier: FSU_migr_etd-0584
Format: Thesis

Title: College of Engineering Microwave Noise Temperature Measurement Uncertainty Analysis Utilizing Monte Carlo Simulations.
Creator: Smith, Ronald Joseph, Weatherspoon, Mark H., Arora, Rajendra K., Roberts, Rodney G., Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: The ability to quantify device performance characteristics is a concern shared by developers, manufacturers, and consumers alike. From a subatomic perspective, the fluctuations found in repeated measurements can be attributed to the random nature of the charge carriers – the electrons. This limitation is also present in any receiver noise measurement set-up. The uncertainty of a noise measurement should be reported with the measurement, but assessing it can be problematic. The receiver system...
Show moreThe ability to quantify device performance characteristics is a concern shared by developers, manufacturers, and consumers alike. From a subatomic perspective, the fluctuations found in repeated measurements can be attributed to the random nature of the charge carriers – the electrons. This limitation is also present in any receiver noise measurement set-up. The uncertainty of a noise measurement should be reported with the measurement, but assessing it can be problematic. The receiver system noise equation, which describes a measurement system, possesses non-linear parameter dependencies. Because of this, an intuitive or quantitative assessment of the measurement uncertainties would be very difficult, if not impossible, to obtain. This research work analyzes the measurement uncertainty inherent to a receiver noise measurement set-up utilizing Monte Carlo simulations. The algorithm used to assess the uncertainty incorporates a random number generator, a non-linear least squares fitting routine, and an uncertainty extraction routine. The random number generation depends on the behavior of noise sources; consequently, it produces either a normal or uniform distribution of data. Normalizing the generator allows the spread to be centered about a desired mean with a desired variance. The variance is a function of the underlying uncertainties associated with the test equipment employed. These values are given in the equipment specification sheets. The spread of real measurement data taken in a testing environment arises from perfectly uncorrelated, partially correlated, and perfectly correlated noise sources. The extreme cases (perfectly uncorrelated and perfectly correlated) are utilized to determine the effect of the erratic behavior of the charge carriers at the extremes. To simulate correlated noise sources, the random numbers are generated with the same random number generator. For the uncorrelated noise sources, the random numbers are generated by separate random processes. Once the random numbers are created, they are used to generate a spread of noise parameter simulated data. Due to the non-linear dependencies of these noise parameters, the effects of the random deviants on measurement uncertainty can not be predicted. An over-determined system of equations allows the receiver parameters of interest to be solved for. The over-determined system of equations can be created because one of the underlying noise parameters has multiple states. Over-determining the system allows for statistical smoothing of the data points. As mentioned previously, the noise parameters have non-linear dependencies and the system noise equation can not easily be transformed into a linear form. Consequently, a non-linear fitting routine is employed. The number of solutions the routine could find for one over-determined set of equations is endless, therefore the acceptable solutions are confined to values close to the true values – "true values" being a set of values actually measured in the testing environment. This confinement simply entails setting the value used as the initial guess for the fitting routine to that of the true value. Once a set of values is found for the receiver parameters, the process is repeated N times (N being the number of simulated data points desired). For each receiver parameter, there are N values that deviate about some mean value. The spread in values is a function of the underlying random process, but the behavior can not be predicted due to the non-linear dependencies. The only assumption that can be made is that the spread should exhibit a Gaussian distribution since all of the random data (except ambient temperature) is created based on this normal distribution. The overall uncertainty in the noise temperature for several devices is determined and compared with the value estimated for a simulated system. Several frequencies are selected for the analysis. The results show good agreement for calculations performed within either 1 or 2 standard deviations of the mean value for the hot and ambient loads. The estimated uncertainty for the simulated receiver system offers explanation as to why the cold load noise temperature measurement uncertainty diverges from the values found for the other DUTs.
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Date Issued: 2007
Identifier: FSU_migr_etd-0348
Format: Thesis

Title: A Comparison of Wi-Fi and WiMAX with Case Studies.
Creator: Wu, Ming-Chieh, Harvey, Bruce A., Yu, Ming, Foo, Simon Y., Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Currently over 50% of the world's population check their e-mails everyday. Collecting information from the Internet is a routine. In the early 21st century, wireless communication has become a hot topic in IT (Information Technology) and CT (Communication Technology), as evidenced by the growth of wireless technologies such as 3G, Wi-Fi and WiMax. 3G is a cellular technology developed in conjunction with the cellular phone network. Wi-Fi is a wireless local area network technology. WiMax is...
Show moreCurrently over 50% of the world's population check their e-mails everyday. Collecting information from the Internet is a routine. In the early 21st century, wireless communication has become a hot topic in IT (Information Technology) and CT (Communication Technology), as evidenced by the growth of wireless technologies such as 3G, Wi-Fi and WiMax. 3G is a cellular technology developed in conjunction with the cellular phone network. Wi-Fi is a wireless local area network technology. WiMax is designed for the wireless metropolitan area network. Today, people not only want the fixed wireless access to the Internet, but also want the mobile wireless access as well. They want a ubiquitous connection, even when in a train, a cab, or the subway. This demand is resulting in increasing competition between the leading wireless technologies. 3G, Wi-Fi and WiMax all appear to have the potential to feed the demand, but still have issues that need to be addressed. The future direction of wireless Internet access is uncertain, including whether these three technologies will operate cooperatively or competitively. This thesis is going to predict the future direction by analysis of 3G, Wi-Fi and WiMax technologies and the evaluation of three wireless access case studies. This thesis will begin with an introduction to the history of Internet and will then continue with a discussion of the technical aspects of 3G, Wi-Fi and WiMax. After the technology introduction, this thesis will evaluate three current implementations of wireless Internet access as case studies to verify the capabilities of Wi-Fi and WiMax, and to discuss the feasibility of building a city-wide wireless network. Finally, a reasonable prediction of the future implementation of a city-wide wireless Internet structure will be presented.
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Date Issued: 2007
Identifier: FSU_migr_etd-0701
Format: Thesis

Title: A Stochastic Approach to Digital Control Design and Implementation in Power Electronics.
Creator: Zhang, Da, Li, Hui, Collins, Emmanuel G., Foo, Simon Y., Kwan, Bing W., Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: This dissertation uses the theory of stochastic arithmetic as a solution for the FPGA implementation of complex control algorithms for power electronics applications. Compared with the traditional digital implementation, the stochastic approach simplifies the computation involved and saves digital resources. The implementation of stochastic arithmetic is also compatible with modern VLSI design and manufacturing technology and enhances the ability of FPGA devices New anti-windup PI controllers...
Show moreThis dissertation uses the theory of stochastic arithmetic as a solution for the FPGA implementation of complex control algorithms for power electronics applications. Compared with the traditional digital implementation, the stochastic approach simplifies the computation involved and saves digital resources. The implementation of stochastic arithmetic is also compatible with modern VLSI design and manufacturing technology and enhances the ability of FPGA devices New anti-windup PI controllers are proposed and implemented in a FPGA device using stochastic arithmetic. The developed designs provide solutions to enhance the computational capability of FPGA and offer several advantages: large dynamic range, easy digital design, minimization of the scale of digital circuits, reconfigurability, and direct hardware implementation, while maintaining the high control performance of traditional anti-windup techniques. A stochastic neural network (NN) structure is also proposed for FPGA implementation. Typically NNs are characterized as highly parallel algorithms that usually occupy enormous digital resources and are restricted to low cost digital hardware devices which do not have enough digital resource. The stochastic arithmetic simplifies the computation of NNs and significantly reduces the number of logic gates required for the proposed the NN estimator. In this work, the proposed stochastic anti-windup PI controller and stochastic neural network theory are applied to design and implement the field-oriented control of an induction motor drive. The controller is implemented on a single field-programmable gate array (FPGA) device with integrated neural network algorithms. The new proposed stochastic PI controllers are also developed as motor speed controllers with anti-windup function. An alternative stochastic NN structure is proposed for an FPGA implementation of a feed-forward NN to estimate the feedback signals in an induction motor drive. Compared with the conventional digital control of motor drives, the proposed stochastic based algorithm has many advantages. It simplifies the arithmetic computations of FPGA and allows the neural network algorithms and classical control algorithms to be easily implemented into a single FPGA. The control and estimation performances have been verified successfully using hardware in the loop test setup. Besides the motor drive applications, the proposed stochastic neural network structure is also applied to a neural network based wind speed sensorless control for wind turbine driven systems. The proposed stochastic neural network wind speed estimator has considered the optimized usage of FPGA resource and the trade-off between the accuracy and the number of employed digital logic elements. Compared with the traditional approach, the proposed estimator uses minimum digital logic resources and enables large parallel neural network structures to be implemented in low-cost FPGA devices with high-fault tolerance capability. The neural network wind speed estimator has been verified successfully with a wind turbine test bed installed in CAPS (Center for Advanced Power Systems). Given that a low-cost and high-performance implementation can be achieved, it is believed that such stochastic control ICs will be extended to many other industry applications involving complex algorithms.
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Date Issued: 2006
Identifier: FSU_migr_etd-0543
Format: Thesis

Title: Numerical Algorithms for the Atomistic Dopant Profiling of Semiconductor Materials.
Creator: Aghaei Anvigh, Samira, Andrei, Petru, Zhang, Mei, Foo, Simon Y., Zheng, Jianping P., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and...
Show moreAghaei Anvigh, Samira, Andrei, Petru, Zhang, Mei, Foo, Simon Y., Zheng, Jianping P., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: In this dissertation, we investigate the possibility to use scanning microscopy such as scanning capacitance microscopy (SCM) and scanning spreading resistance microscopy (SSRM) for the "atomistic" dopant profiling of semiconductor materials. For this purpose, we first analyze the discrete effects of random dopant fluctuations (RDF) on SCM and SSRM measurements with nanoscale probes and show that RDF significantly affects the differential capacitance and spreading resistance of the SCM and...
Show moreIn this dissertation, we investigate the possibility to use scanning microscopy such as scanning capacitance microscopy (SCM) and scanning spreading resistance microscopy (SSRM) for the "atomistic" dopant profiling of semiconductor materials. For this purpose, we first analyze the discrete effects of random dopant fluctuations (RDF) on SCM and SSRM measurements with nanoscale probes and show that RDF significantly affects the differential capacitance and spreading resistance of the SCM and SSRM measurements if the dimension of the probe is below 50 nm. Then, we develop a mathematical algorithm to compute the spatial coordinates of the ionized impurities in the depletion region using a set of scanning microscopy measurements. The proposed numerical algorithm is then applied to extract the (x, y, z) coordinates of ionized impurities in the depletion region in the case of a few semiconductor materials with different doping configuration. The numerical algorithm developed to solve the above inverse problem is based on the evaluation of doping sensitivity functions of the differential capacitance, which show how sensitive the differential capacitance is to doping variations at different locations. To develop the numerical algorithm we first express the doping sensitivity functions in terms of the Gâteaux derivative of the differential capacitance, use Riesz representation theorem, and then apply a gradient optimization approach to compute the locations of the dopants. The algorithm is verified numerically using 2-D simulations, in which the C-V curves are measured at 3 different locations on the surface of the semiconductor. Although the cases studied in this dissertation are much idealized and, in reality, the C-V measurements are subject to noise and other experimental errors, it is shown that if the differential capacitance is measured precisely, SCM measurements can be potentially used for the "atomistic" profiling of ionized impurities in doped semiconductors.
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Date Issued: 2016
Identifier: FSU_2016SP_AghaeiAnvigh_fsu_0071E_13103
Format: Thesis

Title: A Design Methodology for the Implementation of Fuzzy Logic Traffic Controller Using Field Programmable Gate Array.
Creator: Ambre, Mandar Shriram, Kwan, Bing, Meyer-Baese, Uwe, Foo, Simon, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: In this thesis, an approach is proposed for the design and implementation of fuzzy traffic controllers using Field Programmable Gate Arrays (FPGAs).The focus of this study is to develop an effective traffic signaling strategy to be implemented at a typical intersection with four approaches. Adaptive traffic control using fuzzy principles has been demonstrated and reported by the authors in the literature. Here a high-level design approach is suggested, which involves VHDL-based logic...
Show moreIn this thesis, an approach is proposed for the design and implementation of fuzzy traffic controllers using Field Programmable Gate Arrays (FPGAs).The focus of this study is to develop an effective traffic signaling strategy to be implemented at a typical intersection with four approaches. Adaptive traffic control using fuzzy principles has been demonstrated and reported by the authors in the literature. Here a high-level design approach is suggested, which involves VHDL-based logic synthesis and the use of state diagrams with a VHDL backend for graphical design description. The operations of the fuzzifier and the defuzzifier of the fuzzy controller are described in VHDL. The fuzzy rule base for the controller is described using the state diagrams. Specifically, the fuzzy inference based on the fuzzy rules is implemented using MATLAB code. The output of the MATLAB program is stored in a ROM for use in the VHDL code. Once VHDL code is obtained then the hardware is implemented using the UP1 Education board. After the design was tested by using UP1 board the next step was to design a printed circuit board for this system. This was done by using Protel Design Explorer where the input to the circuit board comes from traffic sensors in the field and the output of the circuit board is given to the traffic controller.
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Date Issued: 2004
Identifier: FSU_migr_etd-0028
Format: Thesis

Title: Modeling Potentials in Dionflagellate Noctiluca Miliaris.
Creator: Aarons, Richard, Weatherspoon, Mark H., Andrei, Petru, Meyer-Baese, Anke, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Noctiluca Miliaris is a single cell, multi-membrane organism that has bioluminescent capabilities. This luminescent ability is closely associated with the flash triggering potential produced by an excitable membrane under active conditions such as the movement of ions through channels against the concentration gradient. External energy in the form of an electrical or mechanical stimulus is required for this type of ionic movement that can result in all-or-none spikes in the transmembrane...
Show moreNoctiluca Miliaris is a single cell, multi-membrane organism that has bioluminescent capabilities. This luminescent ability is closely associated with the flash triggering potential produced by an excitable membrane under active conditions such as the movement of ions through channels against the concentration gradient. External energy in the form of an electrical or mechanical stimulus is required for this type of ionic movement that can result in all-or-none spikes in the transmembrane potential if a certain threshold voltage is exceeded. Further examination of this strong nonlinear relationship between the transmembrane voltage and rate of ion flow due to an applied stimulating source provides valuable insight into the action potential that leads to the luminescence, and it also allows for the development of models of the vacuolar potential of Noctiluca Miliaris due to an applied current. An electric circuit model based upon a two-membrane, spherical cell consists of the series combination of a parallel R-C circuit representing the non-excitable, passive outer membrane and a parallel R-C-variable source resistor circuit representing the excitable, inner membrane. The variable source resistor represents a series combination of a dependent voltage source with a variable resistor. The dependent voltage source models the ionic gradient, and the variable resistor models the voltage-time dependent conductance of the ion channel of the active membrane. The variable resistor is also known as the active resistance, and a model of this resistance is primarily governed by the active membrane voltage. With knowledge of the values of each circuit element extracted from experimental measurements, the transmembrane potential is simulated using rectangular current pulses as the stimulating source for both sub-threshold and threshold conditions. A model of a spherical cell model with an external electric field incident on it is evaluated by solving Poisson's equation. This model requires knowledge of the cell radius, membrane thickness, and the conductivity and permittivity of the bath, membrane, and vacuole. With knowledge of these values from experimental measurements, the transmembrane potential is calculated for a stimulating source of known external electric field intensity under sub-threshold conditions.
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Date Issued: 2010
Identifier: FSU_migr_etd-0101
Format: Thesis

Title: Analysis and Implementation of Grid-Connected Solar PV with Harmonic Compensation.
Creator: Cao, Jianwu, Edrington, Chris S., Foo, Simon Y., DeBrunner, Linda, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: A grid-connected photovoltaic (PV) system with the functionality of harmonic compensation is introduced in this thesis. Based on this, a test bed is built up to validate the practicability of the proposed scheme. Increasing interest and investment in renewable energy give rise to rapid development of high penetration solar energy. There are multiple ways to interface PV arrays with the power grid. The topology of a multi-string two-stage PV module with a centralized inverter is developed in...
Show moreA grid-connected photovoltaic (PV) system with the functionality of harmonic compensation is introduced in this thesis. Based on this, a test bed is built up to validate the practicability of the proposed scheme. Increasing interest and investment in renewable energy give rise to rapid development of high penetration solar energy. There are multiple ways to interface PV arrays with the power grid. The topology of a multi-string two-stage PV module with a centralized inverter is developed in the thesis, which is more suitable for medium power applications. However, the output of solar arrays varies due to change of solar irradiation and weather conditions. Therefore, the maximum power point tracking algorithm is implemented in DC/DC converter to enable PV arrays to operate at maximum power point. The incremental conductance algorithm is employed to control the boost converter. Then the central inverter is controlled by decoupled current control algorithm and interfaced with the utility grid via the distribution network. Besides, the current control of the inverter is independent of maximum power point control of the DC/DC converter. Finally, system performance and transient responses are analyzed under the disturbance conditions. And system stability is evaluated when solar irradiation change or system fault happens. The system is simulated in MATLAB. More and more use of static power converter and switched mode power supplies injects harmonic current into the power system. It's advisable that PV can be controlled to compensate the harmonic current as well as supply the active power. The harmonic current is extracted by using time-domain current detection method, which is much easier to implement and doesn't need any transformation comparing with the instantaneous power theory method. The system simulation is accomplished and validated by using PSCAD/EMTDC. Meanwhile, experimental test bed is also established to verify the proposed algorithm. Eventually, the total harmonic distortion (THD) of the grid current after compensation is analyzed and compared with the standard of IEEE 519-1992.
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Date Issued: 2011
Identifier: FSU_migr_etd-0091
Format: Thesis

Title: Expansion and Implementation of the Wave Variable Method in Multiple Degree-of-Freedom Systems.
Creator: Alise, Marc T., Roberts, Rodney G., Moore, Carl, Foo, Simon, Repperger, Daniel, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Adding force feedback to a teleoperation system can greatly improve a user's ability to complete tasks. However, operating in the presence of time delay can cause serious problems for bilateral teleoperation systems. Even a small amount of time delay in a bilateral teleoperation system will generally degrade the system's performance and can cause instability. An important approach that guarantees stability for any fixed time delay is the wave variable method. In this thesis some recent...
Show moreAdding force feedback to a teleoperation system can greatly improve a user's ability to complete tasks. However, operating in the presence of time delay can cause serious problems for bilateral teleoperation systems. Even a small amount of time delay in a bilateral teleoperation system will generally degrade the system's performance and can cause instability. An important approach that guarantees stability for any fixed time delay is the wave variable method. In this thesis some recent material dealing with teleoperation systems using wave variables is presented. In particular, we describe a wave variable scheme based on a family of scaling matrices for a multiple degree-of-freedom bilateral teleoperation system. We include a derivation of a larger and more complete family of scaling matrices that will guarantee the system remains stable for a fixed time delay. The validity of the complete family of scaling matrices is verified through simulations and experiments. A multiple degree-of-freedom bilateral teleoperation system using the new wave variable method is simulated using a SIMULINK model. In addition, the new derivation was implemented in hardware using two different systems: an Immersion joystick with a C++ program and a PHANToM Omni haptic device with a virtual environment. Finally, an experiment was constructed using the PHANToM Omni haptic device as both the master and slave of the teleoperation system. Using Matlab and SIMULINK we added time delay to the communication channel and implemented the wave variable method with the complete family of scaling matrices. Human subjects were used to determine the best set of parameters for the system.
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Date Issued: 2007
Identifier: FSU_migr_etd-0167
Format: Thesis

Title: Hirschman Transform Applications in Compressive Sensing.
Creator: Xi, Peng, DeBrunner, Victor E., Gallivan, Kyle A., Harvey, Bruce A., DeBrunner, Linda S., Roberts, Rodney G., Florida State University, College of Engineering, Department of...
Show moreXi, Peng, DeBrunner, Victor E., Gallivan, Kyle A., Harvey, Bruce A., DeBrunner, Linda S., Roberts, Rodney G., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: The CS technology has attracted considerable attention because it can surpass the traditional limit of Nyquist sampling theory. Rather than sampling a signal at a high frequency and then compressing it, the CS senses the target signal in a compressed format directly. However, the great sampling improvement results in the increased complexity in decoding. The optimization of sensing structure never stops to simplify the decoding procedure as much as possible. Unlike the Heisenberg-Weyl measure...
Show moreThe CS technology has attracted considerable attention because it can surpass the traditional limit of Nyquist sampling theory. Rather than sampling a signal at a high frequency and then compressing it, the CS senses the target signal in a compressed format directly. However, the great sampling improvement results in the increased complexity in decoding. The optimization of sensing structure never stops to simplify the decoding procedure as much as possible. Unlike the Heisenberg-Weyl measure, the Hirschman notion of joint uncertainty is based on entropy rather than energy. The Discrete Hirschman Transform (DHT) has been proved to be superior in complexity reduction and high resolution to the traditional Discrete Fourier Transform in many aspects such as fast filtering, spectrum estimation, and image identification. In this dissertation, I implement a new deterministic compressive sensing system based on DHT with four contributions: (1) apply Weyl's sum character estimation to the DHT matrices to develop a new deterministic sensing structure (2) theoretically prove that the new sensing structure satisfy the Mutual Incoherence Property (3) discover a Non-tensor Wavelet Transform as the sparse basis for DHT sensing structures as well as for other DFT and DFT-like sensing matrices. (4) design a DHT computational core based on FPGA and related communication suite based on C#.
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Date Issued: 2017
Identifier: FSU_FALL2017_XI_fsu_0071E_14193
Format: Thesis

Title: Designing Time Efficient Real Time Hardware in the Loop Simulation Using Input Profile Temporal Compression.
Creator: Chatterjee, Sourindu, Faruque, Md Omar, Steurer, Mischa, Li, Hui, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: The modern day smart grid technology relies heavily on data acquisition and analysis. A distributed controller governs smart microgrid functions with one or more renewable sources and smart controllable loads. This sort of intelligent, scalable system is the primary drive for the Energy Internet (EI). Hence, in modern-day power systems engineering to analyze, understand and make efficient system design choices that capture robustness and scalability, Hardware in the Loop (HIL) simulations are...
Show moreThe modern day smart grid technology relies heavily on data acquisition and analysis. A distributed controller governs smart microgrid functions with one or more renewable sources and smart controllable loads. This sort of intelligent, scalable system is the primary drive for the Energy Internet (EI). Hence, in modern-day power systems engineering to analyze, understand and make efficient system design choices that capture robustness and scalability, Hardware in the Loop (HIL) simulations are required. Real-Time Simulations (RTS) is the state of the art technology thrusting the capstone of innovation for this industry. As engineers, we can model, simulate and validate smart grids operations more rapidly, robustly and reliably using RTS. With enough smaller time step for the simulation, the boundary between the real and the simulated systems slowly vanishes. It also enables the system to be simulated as Controller Hardware in the Loop (CHIL) or Power Hardware in the Loop (PHIL) setups, evolving and imitating the real physical world. The HIL (Hardware in the Loop) setup also enables a real data source or sink to be in the system to form the loop of exchange between the simulated system and real-world hardware which is most often a control hardware. The implementation of such a setup is made possible at Center for Advanced Power Systems (CAPS), named as Hardware in the Loop Test-Bed (HIL-TB). This evaluation architecture provides a systematic solution to HIL simulations. Now the sampling time for real-world sensors is generally in the order of microseconds, enabling this collected data to emulate the cyber-physical domain accurately. Thus, the challenge previously was to address the throughput of real-world input data into the simulated system efficiently and correctly. The quality of the Design of Simulation (DoS) using the real world data in the form of Real Time Input Profile (RTIP), improves, affects the quality of response of the real-time cyber-physical system simulation. Thus great care needs to be taken to prepare, prune and project the RTIPs to improve and enhance the system performance evaluation index. To solve this problem, partially successful attempts have been made in the direction of machine learning by using methods like clustering and regression to characterize large input profiles or by breaking them into subsections using fixed length sliding window techniques. These classic methods then perform data analysis on those sub-pieces to distinguish among a variety of input profiles and assign an index. These sub-profiles or sections would be then loaded into the simulation as environmental input to represent the physical system in the HIL simulations. This traditional procedure is observed to be arbitrary because clustering algorithms and metrics for methods like regression or classification are user-defined and there exists no standard practice to deal with huge input profiles. There have also been confusions regarding the size of the sliding window to create subsections, subsection joining logic, etc. Thus, to address this issue, the primary focus of this study is to present a systematic, controlled, reliable procedure to explore, screen, crop large input profiles and then to compress the same by selecting sections with most relative importance using a modified version of “knapsack” dynamic programming algorithm. This compression primarily aims to shrink down the total simulation time without much loss of information. The latter part of this study focuses towards response driven performance evaluation of the HIL simulations. This is ensured by targeted compression of original input profile based on the certain requirement of the simulation. This approach ensures that the control algorithm (CHIL simulations) or any other system operator is driven in a specific direction in the simulation response space by effectively sampling the input parameters space. The fully automated HIL-TB evaluation framework aided with Input Profile Time Compression (IPTC) module delivers a fast-convergent validation for the performance evaluation with relatively similar system response. In this study, the IPTC module has been applied to seven load profiles to compress their temporal length by a third. The case study used for the simulation with these RTIPs is the Future Renewable Electric Energy Delivery and Management (FREEDM) IEEE seven node system. The test results show great coherence between the uncompressed and compressed response and validate the performance of the IPTC module applied to real-world HIL simulations. Thus, it can conclude that the functionality of the IPTC module is validated by the quality of simulation response gained out of the compressed simulation as compared to uncompressed simulation. In future, endeavors can be made in this path by expanding the functionality of this compression module to not only identifying and managing important sections based on some initial assumption about the objective of the control application but also providing cognitive, autonomous understanding of the behavior of the controls and using that knowledge accomplishing compression of large input profiles.
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Date Issued: 2017
Identifier: FSU_FALL2017_CHATTERJEE_fsu_0071N_14274
Format: Thesis

Title: Fixed-Point Implementation of Discrete Hirschman Transform.
Creator: Thomas, Rajesh, DeBrunner, Victor E., DeBrunner, Linda S., Harvey, Bruce A., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer...
Show moreThomas, Rajesh, DeBrunner, Victor E., DeBrunner, Linda S., Harvey, Bruce A., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Digital Signal Processing (DSP) performs a very important role in various applications of electrical engineering like communications and signal enhancement. In many situations one finds that the DSP hardware available are fixed point processors. In these situations, it is necessary to perform DSP with high accuracy using the least amount of hardware resources. This thesis looks into an approach to calculate the two dimensional Discrete Hirschman Transform (DHT), the inverse DHT, the Hirschman...
Show moreDigital Signal Processing (DSP) performs a very important role in various applications of electrical engineering like communications and signal enhancement. In many situations one finds that the DSP hardware available are fixed point processors. In these situations, it is necessary to perform DSP with high accuracy using the least amount of hardware resources. This thesis looks into an approach to calculate the two dimensional Discrete Hirschman Transform (DHT), the inverse DHT, the Hirschman Cosine Transform (HCT) and the inverse HCT using fixed-point hardware. The complex coefficients required for the transform are calculated beforehand and saved as vectors. Special attention has been given to minimize errors due to scaling. The processed image and the original image does not show significant difference even for DFT or DCT length of 128. Mean square errors of -37 dB for the DHT and -40 dB for the HCT could be obtained for DFT and DCT lengths of 128.
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Date Issued: 2017
Identifier: FSU_FALL2017_Thomas_fsu_0071N_14271
Format: Thesis

Title: Small Signal Instability Assessment and Mitigation in Power Electronics Based Power Systems.
Creator: Ye, Qing, Li, Hui, Collins, E. (Emmanuel), Steurer, Mischa, Yu, Ming, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: Power electronics technology has been widely used in electric power system to achieve high energy efficiency and high renewable energy penetration. Small signal instability phenomena could easily occur in systems with abundant power electronics because of high order passive elements and controller interactions among power converters. These instability issues degrade power quality or even cause system failure. Therefore it is necessary to build accurate small signal models for stability...
Show morePower electronics technology has been widely used in electric power system to achieve high energy efficiency and high renewable energy penetration. Small signal instability phenomena could easily occur in systems with abundant power electronics because of high order passive elements and controller interactions among power converters. These instability issues degrade power quality or even cause system failure. Therefore it is necessary to build accurate small signal models for stability analysis and develop effective resonance mitigation techniques for stability improvement. The general stability analysis methods including eigenvalues-based method, component connection method, passivity-based method and impedance-based method have been evaluated and summarized. The impedance-based method is selected as the stability analysis tool for this research due to its advantages compared to other methods. Besides, three popular resonance suppression techniques, i.e. passive damper, active damper and virtual impedance control, are also studied and evaluated. The virtual impedance control is of interest because it does not reduce system efficiency or reliability compared to both the passive and active damper. A unified impedance-based stability criterion (UIBSC) has been proposed for paralleled grid-tied inverters. Compared to the traditional IBSC which evaluates all minor loop gains (MLGs) of individual inverter, the UIBSC assesses the derived global minor loop gain (GMLG) only once to determine system stability. As a result, the computation efforts can be significantly reduced when system contains a large number of inverters. In addition, a stability-oriented design guideline has been derived for the paralleled grid-tied inverters based on the GMLG. By using the guideline, the grid impedance, inverter filter parameters, time delays of digital control and control parameters can be analyzed or designed to meet the system stability requirement. The small signal stability of the FREEDM system is a critical issue due to the abundant power electronics devices and flexible control strategies. The impedance modeling methods for current controlled inverters, inverter stage of the SST, DAB converters are developed. The influences of control schemes on power converter terminal behaviors are analyzed as well. Stability criteria for several types of grid enabled by the SST are derived. The bidirectional power flow effect is also considered. These instability phenomena are demonstrated in ac, dc, and hybrid ac/dc grids of FREEDM system using HIL test bed. Finally, the conclusions are given and the scope of future work is discussed.
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Date Issued: 2017
Identifier: FSU_FALL2017_Ye_fsu_0071E_14130
Format: Thesis

Title: Application of Thermal Network Model for Designing Superconducting Cable Components.
Creator: Indrakanti, Shiva Charan, Pamidi, Sastry V., Foo, Simon Y., Moss, Pedro L., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer...
Show moreIndrakanti, Shiva Charan, Pamidi, Sastry V., Foo, Simon Y., Moss, Pedro L., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: High Temperature Superconductors (HTS) have the advantage of carrying direct current at zero resistance when operated below their critical temperature. At lower temperatures, these superconductors have the capability of carrying higher current densities. HTS power systems have applications in electrical power grids, defense, naval, aircraft, and industrial sectors. HTS devices enable higher efficiency while providing resiliency and reliability to power systems. This study developed models for...
Show moreHigh Temperature Superconductors (HTS) have the advantage of carrying direct current at zero resistance when operated below their critical temperature. At lower temperatures, these superconductors have the capability of carrying higher current densities. HTS power systems have applications in electrical power grids, defense, naval, aircraft, and industrial sectors. HTS devices enable higher efficiency while providing resiliency and reliability to power systems. This study developed models for superconducting cable system with two terminations, HTS cable, and cryo-cooler. The models combined electrical and cryogenic thermal aspects of the superconducting cable system. Several operating scenarios were simulated. Some contingencies such as cryo-cooler failure, circulation system failure were also modeled. A comparison of AC and DC cables was also analyzed in the system. The simulation models help in the analysis of the effects of system failure and to estimate the time required to turn off the system before the cable is affected. The results indicate that most of the heat load into the system is due to the terminations which are the interfaces between the superconducting cable and the room temperature components. In the contingency situations such as cryo-cooler failure, the time required to turn-off the system is several minutes. These results help us protect the cable from catastrophic damage during unexpected situations. Through these models, it is possible to calculate the maximum current that can be run through the system before the cable reaches a potential quench.
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Date Issued: 2017
Identifier: FSU_FALL2017_Indrakanti_fsu_0071N_14273
Format: Thesis

Title: Some Theory and an Experiment on the Fundamentals of Hirschman Uncertainty.
Creator: Ghuman, Kirandeep, DeBrunner, Victor E., Srivastava, Anuj, DeBrunner, Linda S. (Linda Sumners), Harvey, Bruce A., Roberts, Rodney G., Florida State University, FAMU-FSU College...
Show moreGhuman, Kirandeep, DeBrunner, Victor E., Srivastava, Anuj, DeBrunner, Linda S. (Linda Sumners), Harvey, Bruce A., Roberts, Rodney G., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: The Heisenberg Uncertainty principle is a fundamental concept from Quantum Mechanics that also describes the Fourier Transform. Unfortunately, it does not directly apply to the digital signals. However, it can be generalized if we use entropy rather than energy to form an uncertainty relation. This form of uncertainty, called the Hirschman Uncertainty, uses the Shannon Entropy. The Hirschman Uncertainty is defined as the average of the Shannon entropies of the discrete-time signal and its...
Show moreThe Heisenberg Uncertainty principle is a fundamental concept from Quantum Mechanics that also describes the Fourier Transform. Unfortunately, it does not directly apply to the digital signals. However, it can be generalized if we use entropy rather than energy to form an uncertainty relation. This form of uncertainty, called the Hirschman Uncertainty, uses the Shannon Entropy. The Hirschman Uncertainty is defined as the average of the Shannon entropies of the discrete-time signal and its Fourier Transform. The functions that minimize this uncertainty are not the wellknown Gaussians from the Heisenberg theory, but are the picket fence functions first noticed in wavelet denoising. This connection suggests that the Hirschman Uncertainty is fundamental, but not conclusively. Here in this research, we develop two new uncertainty measures that are derived from the Hirschman Uncertainty. We want to use these measures to explore the fundamental nature of the Hirschman Uncertainty. In the first case, we replace the Shannon entropy with the Rényi entropy and study the impact of varying the Rényi order on the uncertainty of various digital signals. We call this new uncertainty measure, the Hirschman-Rényi uncertainty denoted by U[alpha over ½](x). We find that the derived uncertainty measure is invariant to the Rényi order in case of the picket fence signals and varies in case of other the digital signals like rectagular, cosine, square wave signals to name a few. This new uncertainty measure that utilizes the Rényi entropy decays with the increase in Rényi order value. Considering the invariance in uncertainty in case of picket fence signal, we can use either Shannon or Rényi entropy with any value of Rényi order to calculate Hirschman Uncertainty. In the second case, we derive an uncertainty measure that replaces the Fourier Transform with the Fractional Fourier Transform. The Hirschman Uncertainty using dFRT denoted by U[alpha over ½](x) is explored with the help of the minimizers of the Hirschman Uncertainty (the picket fence signals) along with the other digital signals. In this case, we find that the degree of rotation in the Fractional Fourier Transform does impact the uncertainty at the integer values of the transfer order. But for the non-interger values of the transfer order, the uncertainty variations are greatly reduced or are minimal. Finally to help verify our theory, we perform a classical texture recognition experiment. We find that the recognition performance follows directly as our developed Hirschman Rényi Uncertainty and the Hirschman Uncertainty using dFRT theory suggests. Additionally, it appears that a predictive solution for the proper selection of the Rényi order and the rotation angle can be developed that could significantly aid in image analysis. Our recognition results are consistent with entropic invariance theory in case of the two uncertainty measures. These results suggests that the Hirschman Uncertainty may be a fundamental characteristic of the digital signals.
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Date Issued: 2015
Identifier: FSU_2015fall_Ghuman_fsu_0071E_12257
Format: Thesis

Title: Modeling, Simulation, and Experimental Verification of Impedance Spectra in Li-Air Batteries.
Creator: Mehta, Mohit Rakesh, Andrei, Petru, Schlenoff, Joseph B., Zheng, Jianping P., Moss, Pedro L., Li, Hui, Florida State University, College of Engineering, Department of Electrical...
Show moreMehta, Mohit Rakesh, Andrei, Petru, Schlenoff, Joseph B., Zheng, Jianping P., Moss, Pedro L., Li, Hui, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: There has been a growing interest in electrochemical storage devices such as batteries, fuel cells and supercapacitors in recent years. This interest is due to our increasing dependence on portable electronic devices and on the high demand for energy storage from the electric transport vehicles and electrical power grid industries. As we transition towards cleaner renewable fuel sources such as solar, wind, tidal, etc. our dependence on energy storage devices will continue to grow. Li-air...
Show moreThere has been a growing interest in electrochemical storage devices such as batteries, fuel cells and supercapacitors in recent years. This interest is due to our increasing dependence on portable electronic devices and on the high demand for energy storage from the electric transport vehicles and electrical power grid industries. As we transition towards cleaner renewable fuel sources such as solar, wind, tidal, etc. our dependence on energy storage devices will continue to grow. Li-air offers much higher energy density than all other batteries based on electrochemical storage. However, these batteries currently suffer from a number of issues such as a low cyclability and a reduced practical energy density compared to the theoretical energy density. The deposition of lithium peroxide on the surface of the cathode is one of the main causes for the low practical specific capacity of lithium-air batteries with organic electrolyte. Electrochemical impedance spectroscopy (EIS) has been used in the past to extract physical parameters such as chemical diffusion coefficient, effective diffusion coefficient, Faradaic reaction rate, degradation and stability of an electrochemical device. In this dissertation, a physics based analytical model is developed to study the EIS of Li-air batteries, in which the mass transport inside the cathode is limited by oxygen diffusion, during charge and discharge. The model takes into consideration the effects of double layer, Faradaic processes, and oxygen diffusion in the cathode, but neglects the effects of anode, separator, conductivity of the deposit layer, and Li-ion transport. The analytical model predicts that the effects of Faradaic impedance can be hidden by the double layer capacitance. Therefore, the dissertation focuses separately on two cases: 1) the case when the Faradaic process and the double layer capacitance are separate and can be observed as two different semicircles on the Nyquist plot and 2) the case when the Faradaic process is shadowed by the double layer capacitance and shows up as only one large semicircle on the Nyquist plot. A simple expression is developed to extract physical parameters such as the values of the diffusion coefficient of oxygen and Faradaic reaction rate from experimental impedance spectrum for each of the two cases. The diffusion coefficient can be determined by using the resistances (real impedance intercept on the Nyquist plot) of both the semicircles for the first case and by using the combined resistance for the second case. Once, the effective oxygen diffusion coefficient is estimated, it can be used to estimate the value of the reaction constant. This method of extracting the values of the diffusion coefficient and reaction constant can serve as a tool in identifying an effective electrolyte or cathode material. It can also serve as a noninvasive technique to identify and also quantify the use of the catalyst to improve the reaction kinetics in an electrochemical system. Finally, finite element simulations are used to validate the analytical models and to study the effects of discharge products on the impedance spectra of Li-air batteries with organic electrolyte. The finite element simulations are based on the theory of concentrated solutions and the complex impedance spectra are computed by linearizing the partial differential equations that describe the mass and charge transport in Li-air batteries. These equations include the oxygen diffusion equation, the Li drift-diffusion equation, and the electron conduction equation. The reaction at the anode and cathode are described by Butler-Volmer kinetics. The total impedance of a Li-air battery increases by more than 200% when the response is measured near the end of the discharge cycle as compared to on a fresh battery. The resistivity of the deposition layer significantly affects the deposition profile and the total impedance. Using electrolytes with high oxygen solubility and concentrated O2 gas at high pressures will reduce the total impedance of Li-air batteries.
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Date Issued: 2015
Identifier: FSU_2015fall_Mehta_fsu_0071E_12827
Format: Thesis

Title: Coupled Subspace Analysis and PCA Variants: A Computer Vision Application.
Creator: Nelson, Richard A., Roberts, Rodney G., Foo, Simon Y., Tung, Leonard J., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: In numerous applications involving high dimensional data, certain subspace techniques such as principal components analysis (PCA) may be utilized in feature extraction. Often, PCA can reduce the dimensionality while retaining most of the significant information of the original data. This can be beneficial not only for representation of the data more compactly (compression), but also for transforming the data into a more useful form for applications involving feature extraction and...
Show moreIn numerous applications involving high dimensional data, certain subspace techniques such as principal components analysis (PCA) may be utilized in feature extraction. Often, PCA can reduce the dimensionality while retaining most of the significant information of the original data. This can be beneficial not only for representation of the data more compactly (compression), but also for transforming the data into a more useful form for applications involving feature extraction and classification. Relatively recent developments with PCA extend conventional principal components analysis to newer variants of PCA which appear particularly useful in computer vision and image applications: (1) two dimensional PCA ("2D PCA"), and (2) bidirectional or bilateral two dimensional PCA ("B2DPCA", "Bi2DPCA", or "(2D)² PCA"). The latter category includes an iterative version which is an example of coupled subspace analysis or "CSA"; the non-iterative version is known as projective Bi2DPCA. In this thesis, these PCA variants are considered as special cases of the more general CSA. Theoretical advantages of 2D PCA and bidirectional PCA over conventional PCA should arise from the fact that significant information about the spatial relationship between image pixels may be discarded in conventional PCA as the image is represented by a large column vector, whereas 2D PCA and bidirectional PCA techniques can preserve more of this information by representing the image as a matrix rather than a long vector. The problems of small sample size, and curse of dimensionality are also alleviated to some extent, particularly in the cases of B2DPCA and iterated CSA. Some of these PCA variants have been proposed in various image recognition applications recently, including biometric identification using iris texture, face images, and palm prints, and categorization of wood species based on wood grain texture to name a few examples. So, while much focus has been placed on feature extraction methods such as use of Gabor wavelets or similar techniques for some applications such as iris recognition, some subspace techniques, including some of these PCA variants, have shown promise in conjunction with image preprocessing techniques for removal of uneven background illumination and contrast enhancement. In this thesis, the image application of biometric iris recognition is chosen as the means of evaluating potential advantages of these newer PCA variants, including CSA, in the context of feature extraction and classification. The rich texture information of these images, and the utilization of effective image registration techniques, yields images which are well suited for this purpose. As the primary focus of this thesis, these PCA variants are evalulated using closed set identification test mode, and are compared using Euclidean distance single nearest neighbor classifier; images are preprocessed using top-hat filtering and contrast limiting adaptive histogram equalization (CLAHE). Use of multiple test (probe) images is considered, and the impact on performance is considered also for training image sets with 2, 3, and 4 sample images per class. Concurrently, the application of iris image recognition is addressed in detail. Other applications for which these PCA variants and preprocessing techniques may be beneficial are discussed in the concluding section.
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Date Issued: 2015
Identifier: FSU_2015fall_Nelson_fsu_0071N_12964
Format: Thesis

Title: Alternative Measurement Approach Using Inverse Scattering Theory to Improve Modeling of Rotating Machines in Ungrounded Shipboard Power Systems.
Creator: Breslend, Patrick Ryan, Edrington, Christopher S., Graber, Lukas, Steurer, Michael, Florida State University, College of Engineering, Department of Electrical and Computer...
Show moreBreslend, Patrick Ryan, Edrington, Christopher S., Graber, Lukas, Steurer, Michael, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: The Navy has proposed to use a shipboard power system operating at medium voltage direct current to distribute power for their all-electric ship. The power is generated by electric machines as alternating current and requires power electronic rectifiers to output direct current. Power electronics converters are needed to convert the direct current to alternating current for ship propulsion and service loads. An increase in the use of fast switching power electronics is expected in future...
Show moreThe Navy has proposed to use a shipboard power system operating at medium voltage direct current to distribute power for their all-electric ship. The power is generated by electric machines as alternating current and requires power electronic rectifiers to output direct current. Power electronics converters are needed to convert the direct current to alternating current for ship propulsion and service loads. An increase in the use of fast switching power electronics is expected in future ships. The increased voltage rise time on switches is known to produce unwanted high frequencies with corresponding wavelengths of the same order of magnitude as the length of the ship hull. These high frequency transients can cause the ship system to couple with the surrounding ship hull causing adverse effects. The amount of high frequency content and the impact it has on the ship system performance is difficult to calculate with current models. Increased voltage and performance requirements for power electronics has led to advancements in switching frequencies into the 10s to 100s of kilohertz and increased voltage edge rates. The faster switching corresponds to higher frequency responses from the shipboard power system. Research has shown that high frequency content in electrical power systems is responsible for parasitic coupling and ultimately damage to the equipment. Electric machines, for instance, have increased winding and iron losses, overvoltages at the terminals, and even bearing currents via shaft voltages. The Navy is interested in simulating ship systems to test their electromagnetic compatibility before implementing or committing to a specific design. There are numerous techniques used to acquire machine parameters that have been proven to be useful in modeling electric machine behavior. The approaches were considered by the amount of proprietary information needed to acquire accurate results, the complexity of the modeling methods, and the overall time it takes for implementation. A majority of system simulations gravitate towards simple solutions for machine behavior which require assumptions to be made that deviate from the actual machine behavior. Exact inner dimensions, winding layouts, end winding dimensions, insulation thickness, and other information are proprietary and often not accurate representations of the physical machine once built. It is time consuming to obtain an accurate working model when assumptions are made or when detailed computer aided design models are needed to calculate machine response quantities. The research modeling approach put forth in this paper is not aimed at capturing the steady-state behavior of the machine. It is shown that a detailed understanding of the motor may not be necessary to accurately model the high frequency effects. It is the transient behavior at non-operating frequencies that need to be modeled correctly to develop new models of shipboard power systems for grounding research. The frequency dependent information is most useful to determine frequencies of interest that other modeling techniques are less likely to capture and point out. Previously suggested measurement techniques have been considered useful in determining parameters of machines but are not always accurately implemented without in-depth knowledge of the motor that may be proprietary. Lumped-parameter models are based on extracting information at transitional frequencies or looking at the slope of a variable over a frequency range. These models tend to be over simplified representations of the component by averaging the parameters for given ranges. In reality a machine's impedance varies with all frequencies. Lumped parameter based models typically over simplify the grounding behavior of the machine by not varying the impedance as a function of frequency. The technique used in this research is based on scattering parameters, a way of determining the terminal behavior of the machine without the knowledge of the actual inner workings of the machine. The inverse scattering technique uses steady-state stimuli to calculate reflection and transmission coefficients of system components allowing the device to be considered as a black box. This can be understood as electrical snapshots of how the machine would respond when subjected to a range of spectral content. The approach could have a significant impact on the modeling of ground interactions with machines. The machine can now be measured and characterized with no prior knowledge of the machine. The measurements are placed in simulation software in the typical measurement configurations used in other approaches to extract parametric data. It was discovered that these different configuration setups could now be measured in software without the need to physically reconfigure the machine's wiring for each measurement. This modeling approach was coined 'virtual measurement modeling.' To the best of the author's knowledge there are not any known techniques for fast model prototyping of electric machines which cover a broad range of frequencies with high accuracy. This thesis will present a possible solution for consideration in future models developed for grounding studies. This approach outlines a promising technique that can be easily implemented with high accuracy and reproducibility. The technique was derived from inverse scattering theory and was implemented on electric machines for characterizing high frequency behaviors.
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Date Issued: 2015
Identifier: FSU_2015fall_Breslend_fsu_0071N_12834
Format: Thesis

Title: Mechanism and Robot Design: Compliance Synthesis and Optimal Fault Tolerant Manipulator Design.
Creator: Yu, Hyun Geun, Roberts, Rodney G., III, Carl D. Crane, Park, Young-Bin, Meyer-Baese, Anke, Foo, Simon Y., Department of Electrical and Computer Engineering, Florida State...
Show moreYu, Hyun Geun, Roberts, Rodney G., III, Carl D. Crane, Park, Young-Bin, Meyer-Baese, Anke, Foo, Simon Y., Department of Electrical and Computer Engineering, Florida State University
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Abstract/Description: In this research, two important concepts concerning parallel robots are investigated: compliance and fault tolerance. First, we address the issue of synthesizing a suitable compliance. This is an important problem since a well-designed compliance/stiffness mechanism can provide proper force regulation and compensate for the inevitable inaccuracy of traditional control systems. Mathematically, the compliance/stiffness of a robotic mechanism is usually modeled by a 6 by 6 symmetric positive...
Show moreIn this research, two important concepts concerning parallel robots are investigated: compliance and fault tolerance. First, we address the issue of synthesizing a suitable compliance. This is an important problem since a well-designed compliance/stiffness mechanism can provide proper force regulation and compensate for the inevitable inaccuracy of traditional control systems. Mathematically, the compliance/stiffness of a robotic mechanism is usually modeled by a 6 by 6 symmetric positive definite matrix at an equilibrium point using screw theory. Synthesis of unloaded spatial stiffness problems has attracted some attention recently and several techniques have been developed to systemically synthesize compliance mechanisms with a given symmetric positive definite spatial stiffness matrix. However, when an external wrench is exerted on the mechanism and the mechanism moves away from its unloaded equilibrium, the modeled compliance/stiffness matrix becomes non-symmetric. In this study, the non-symmetric stiffness matrix for a robotic mechanism is derived and converted into a particularly simple form using matrix algebra. Based on the canonical form of the stiffness matrix, two novel procedures are presented for the first time for synthesizing a desired non-symmetric stiffness matrix for a planar structure when there is an external load that puts the system in a loaded equilibrium. The second part of the dissertation focuses on the problem of designing nominal manipulator Jacobians that are optimally fault tolerant to one or more joint failures. In this work, optimality is defined in terms of the worst case relative manipulability index. While this approach is applicable to both serial and parallel mechanisms, it is especially applicable to parallel mechanisms with a limited workspace. It is shown that a previously derived inequality for the worst case relative manipulability index is generally not achieved for fully spatial manipulators and that the concept of optimal fault tolerance to multiple failures is more subtle than previously indicated. The final goal of this work is to identify the class of eight degree-of-freedom Gough-Stewart platforms that are optimally fault tolerant to up to two locked joint failures. Configurations of serial and parallel robots that achieve optimal fault tolerance for a give Jacobian are presented as results of this study.
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Date Issued: 2007
Identifier: FSU_migr_etd-0797
Format: Thesis

Title: Morphological Image Segmentation for Co-Aligned Multiple Images Using Watersheds Transformation.
Creator: Yu, Hyun Geun, Roberts, Rodney G., Foo, Simon Y., Meyer-Baese, Anke, Department of Electrical and Computer Engineering, Florida State University
Abstract/Description: Image segmentation is one of the most important categories of image processing. The purpose of image segmentation is to divide an original image into homogeneous regions. It can be applied as a pre-processing stage for other image processing methods. There exist several approaches for image segmentation methods for image processing. The watersheds transformation is studied in this thesis as a particular method of a region-based approach to the segmentation of an image. The complete...
Show moreImage segmentation is one of the most important categories of image processing. The purpose of image segmentation is to divide an original image into homogeneous regions. It can be applied as a pre-processing stage for other image processing methods. There exist several approaches for image segmentation methods for image processing. The watersheds transformation is studied in this thesis as a particular method of a region-based approach to the segmentation of an image. The complete transformation incorporates a pre-processing and post-processing stage that deals with embedded problems such as edge ambiguity and the output of a large number of regions. Multiscale Morphological Gradient (MMG) and Region Adjacency Graph (RAG) are two methods that are pre-processing and post-processing stages, respectively. RAG incorporates dissimilarity criteria to merge adjacent homogeneous regions. In this thesis, the proposed system has been applied to a set of co-aligned images, which include a pair of intensity and range images. It is expected that the hidden edges within the intensity image can be detected by observing range data or vice versa. Also it is expected that the contribution of the range image in region merging can compensate for the dominance of shadows within the intensity image regardless of the original intensity of the object.
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Date Issued: 2004
Identifier: FSU_migr_etd-0785
Format: Thesis

Title: Simulation of Li-Ion Coin Cells Using COMSOL Multiphysics.
Creator: Chepyala, Seshuteja, Moss, Pedro L., Weatherspoon, Mark H., Andrei, Petru, Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer...
Show moreChepyala, Seshuteja, Moss, Pedro L., Weatherspoon, Mark H., Andrei, Petru, Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Lithium batteries have played an important role since early 1980’s to provide us with energy for small portable devices. Due to the increasing demand and limited availability of fossil fuels there is a need to shift to renewable energy. In this thesis, the fabrication procedure for the lithium ion coin cell is extensively analyzed. A brief introduction into the lithium ion battery is discussed, the physics and chemistry of the materials is explained. Emphasis is made on the importance of...
Show moreLithium batteries have played an important role since early 1980’s to provide us with energy for small portable devices. Due to the increasing demand and limited availability of fossil fuels there is a need to shift to renewable energy. In this thesis, the fabrication procedure for the lithium ion coin cell is extensively analyzed. A brief introduction into the lithium ion battery is discussed, the physics and chemistry of the materials is explained. Emphasis is made on the importance of calendaring an electrode. LiFePO4 was mixed with the Super P, PVDF and NMP at appropriate stoichiometric amounts and half coin cells were produced with the reference electrode as lithium foil. The effects of calendaring in terms of discharge capacity, density profile and ac impedance was analyzed. The resulting material sample were analyzed in two parts, Sample A was left as is and Sample B was calendared. The calendared electrode exhibited a lower impedance when observed with the impedance test. The calendared electrode exhibited a higher discharge capacity of about 162 mAh/g at C/10 rate when compared to the uncalendared electrode with a discharge capacity of about 152 mAh/g at C/10. The experimental results were than compared to the simulated model constructed in Comsol Multiphysics. The coin cell model in COMSOL was started with use of the existing model for cylindrical cells. The parameters and equations required for the setup were analyzed and discussed. The comparison of the experimental vs simulated results yielded some preliminary information. However, this work is still in progress, for building further models with different materials for the coin cells.
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Date Issued: 2017
Identifier: FSU_SUMMER2017_Chepyala_fsu_0071N_14110
Format: Thesis

Title: Estimation of Power Density of Modular Multilevel Converter Employing Set Based Design.
Creator: Toshon, Tanvir Ahmed, Faruque, Md Omar (Professor of Electrical and Computer Engineering), Foo, Simon Y., Bernadin, Shonda Lachelle, Soman, Ruturaj, Florida State University,...
Show moreToshon, Tanvir Ahmed, Faruque, Md Omar (Professor of Electrical and Computer Engineering), Foo, Simon Y., Bernadin, Shonda Lachelle, Soman, Ruturaj, Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Medium Voltage DC (MVDC) system is becoming a captivating alternative for designing All Electric Ship (AES) for the US Navy. Modular Multilevel Converter (MMC) is considered as an essential component of MVDC systems for its scalability and efficacy. Designing such a power electronic converter for an electric ship is a challenging task in terms of volume constraints in an electric ship.Preliminary naval ship design used point based spiral design techniques, but the complexity and some...
Show moreMedium Voltage DC (MVDC) system is becoming a captivating alternative for designing All Electric Ship (AES) for the US Navy. Modular Multilevel Converter (MMC) is considered as an essential component of MVDC systems for its scalability and efficacy. Designing such a power electronic converter for an electric ship is a challenging task in terms of volume constraints in an electric ship.Preliminary naval ship design used point based spiral design techniques, but the complexity and some disadvantages of such design techniques don’t necessarily produce the most feasible cost effective design. To overcome the issue, the US Navy is exploring the application of Set Based Design(SBD) for designing naval architecture through Smart Ship System Design (S3D) to aid the early stage ship design.This thesis explores the areas of SBD to have a better understanding and knowledge of the design techniques. This is accomplished by design exercise employing SBD to design an essential component of the MVDC breaker-less architecture which is Modular Multilevel Converter. The effort begins with investigating the scaling factors for MMC and apply them to estimate the power density of the converter through exploration of SBD.The outcome of this work is expected to aid early stage ship design exercises using S3D which will enable a guideline for applying SBD concepts to integrate into ship system design.
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Date Issued: 2017
Identifier: FSU_SUMMER2017_TOSHON_fsu_0071N_14095
Format: Thesis

Title: Low Voltage Ride-through for Photovoltaic Systems Using Finite Control-Set Model Predictive Control.
Creator: Franco, Fernand Diaz, Edrington, Christopher S., Ordóñez, Juan Carlos, Faruque, Md Omar (Professor of Electrical and Computer Engineering), Foo, Simon Y., Florida State...
Show moreFranco, Fernand Diaz, Edrington, Christopher S., Ordóñez, Juan Carlos, Faruque, Md Omar (Professor of Electrical and Computer Engineering), Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Grid codes impose immunity requirements to the generation systems that are connected to the transmission lines. Immunity refers to the generator’s capability to overcome grid abnormal conditions. One of the requirements is to remain connected during a certain time when a fault, like voltage sag, is presented. During the fault scenario, a generator unit should remain connected for a pre-determined amount of time, and also provide reactive power to support the grid voltage. This is called low...
Show moreGrid codes impose immunity requirements to the generation systems that are connected to the transmission lines. Immunity refers to the generator’s capability to overcome grid abnormal conditions. One of the requirements is to remain connected during a certain time when a fault, like voltage sag, is presented. During the fault scenario, a generator unit should remain connected for a pre-determined amount of time, and also provide reactive power to support the grid voltage. This is called low-voltage ride through (LVRT). Initially, LVRT requirements were imposed for large generator units like wind farms connected to the transmission network; however, due to the increased penetration of distributed generation (DG) on the distribution system, new grid codes extend the mentioned capability to generator units connected to the distribution grid. Due to matured photovoltaic (PV) technology and the decreased price of PV panels, PV grid tied installations are proliferating in the utility grids; this is creating new challenges related to voltage control. In the past, DG such as PV were allowed to trip from the grid when a fault or unbalance occurred and reconnect within several seconds (sometimes minutes) once the fault had been cleared. Nevertheless, thanks to high PV penetration nowadays, the same method cannot be used because it will further deteriorate the power quality and potentially end in a power blackout. Different approaches have been considered to fulfill the LVRT requirement on PV systems. A large amount of literature focuses on the control of the grid side converter of the PV installation rather than the control of PV operation during the fault, and most control designs applied to the grid side follow classical control methods. Moreover, the effects of the grid fault on the generator side impose a challenge for controlling the PV systems since the quality of the synthesized converter voltages and currents depends on the dc link power/voltage control. This document proposes a Model based Predictive Control (MPC) for controlling a two stage PV system to fulfill LVRT requirements. MPC offers important advantages over traditional linear control strategies since the MPC cost function can include constraints that are difficult to achieve in classical control. Special attention is given to implementation of the proposed control algorithms. Simplified MPC algorithms that do not compromise the converter performance and immunity requirement are discussed.
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Date Issued: 2017
Identifier: FSU_SUMMER2017_DiazFranco_fsu_0071E_14045
Format: Thesis

Title: Modeling and Application of Effective Channel Utilization in Wireless Networks.
Creator: Ng, Jonathan, Yu, Ming (Professor of scientific computing), Zhang, Zhenghao, Harvey, Bruce A., Andrei, Petru, Florida State University, College of Engineering, Department of...
Show moreNg, Jonathan, Yu, Ming (Professor of scientific computing), Zhang, Zhenghao, Harvey, Bruce A., Andrei, Petru, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: As a natural scarcity in wireless networks, radio spectrum becomes a major investment in network deployment. How to improve the channel utilization (CU) of the spectrum is a challenging topic in recent research. In a network environment, the utilization of a channel is measured by the effective CU (ECU), i.e., the effective time for transmission or when the medium being sensed busy over its total operation time. However, existing work does not provide a valid model for ECU. We investigate the...
Show moreAs a natural scarcity in wireless networks, radio spectrum becomes a major investment in network deployment. How to improve the channel utilization (CU) of the spectrum is a challenging topic in recent research. In a network environment, the utilization of a channel is measured by the effective CU (ECU), i.e., the effective time for transmission or when the medium being sensed busy over its total operation time. However, existing work does not provide a valid model for ECU. We investigate the relationship between ECU and the interference from other wireless transmission nodes in a wireless network, as well as from potential malicious attacking interfering sources. By examining the relationship between their transmission time and co-transmission time ratios between two or more interferers, we propose a new model based on the channel occupation time of all nodes in a network. The model finds its mathematical foundation on the set theory. By eliminating the overlapping transmission time intervals instead of simply adding the transmission time of all interferers together, the model can obtain the expected total interference time by properly combining the transmission time of all individual nodes along with the time when two or more nodes transmit simultaneously. Through dividing the interferers into groups according to the strength levels of their received interference power at the interested node, less significant interfering signals can be ignored to reduce the complexity when investigating real scenarios. The model provides an approach to a new detection method for jamming attacks in wireless networks based on a criterion with combined operations of ECU and CU. In the experiments, we find a strong connection between ECU and the received interference power and time. In many cases, strong and frequent interference is accompanied by a declination of ECU. The descending slope though may be steep or flat. When the decrease of ECU is not significant, CU can be observed with a sharp drop instead. Therefore, the two metrics, ECU and CU when properly combined together, demonstrate to be an effective measurement for judging strong interference. In addition, relating to other jamming detection methods in the literature, we build a mathematical connection between the new jamming detection conditions and PDR, the Packet Delivery Ratio, which has been proved effective by previous researchers. Thus, the correlation between the new criteria and PDR guarantees the validity of the former by relating itself to a tested mechanism. Both the ECU model and the jamming detection method are thoroughly verified with OPNET through simulation scenarios. The experiment scenarios are depicted with configuration data and collected statistical results. Especially, the radio jamming detection experiments simulate a dynamic radio channel allocation (RCA) module with a user-friendly graphical interface, through which the interference, the jamming state, and the channel switching process can be monitored. The model can further be applied to other applications such as global performance optimization based on the total ECU of all nodes in a wireless communications environment because ECU relates one node's transmission as the interference for others using the same channel for its global attribute, which is our work planned for the next step. We would also like to compare its effectiveness with other jamming detection methods by exploring more extensive experiment research.
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Date Issued: 2017
Identifier: FSU_SUMMER2017_Ng_fsu_0071E_14083
Format: Thesis

Title: Investigation of Alternative Cryogenic Dielectric Materials and Designs for High Temperature Superconducting Devices.
Creator: Cheetham, Peter Graham, Pamidi, Sastry V., Ordóñez, Juan Carlos, Edringtion, Christopher S., Graber, Lukas, Foo, Simon Y., Florida State University, FAMU-FSU College of...
Show moreCheetham, Peter Graham, Pamidi, Sastry V., Ordóñez, Juan Carlos, Edringtion, Christopher S., Graber, Lukas, Foo, Simon Y., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show moreThe 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.
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Date Issued: 2017
Identifier: FSU_SUMMER2017_Cheetham_fsu_0071E_13956
Format: Thesis

Title: Impedance Measurement Techniques in Noisy Medium Voltage Power Hardware-in-the-Loop Environments.
Creator: Chauncey, Gunnar Luke, Li, Hui, Steurer, Michael, Yu, Ming, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: 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...
Show moreIn 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.
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Date Issued: 2018
Identifier: 2018_Su_Chauncey_fsu_0071N_14782
Format: Thesis

Title: A New Two-Stage Game Framework for Power Demand Response Management in Smart Grids.
Creator: Fan, Huipu, Yu, Ming, Liu, Xiuwen, Tung, Leonard J., Andrei, Petru, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: 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 ...
Show moreRecently, 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.
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Date Issued: 2018
Identifier: 2018_Su_Fan_fsu_0071E_14654
Format: Thesis

Title: Distributed Adaptive Droop Control for Power Management in DC Distribution Systems.
Creator: Perkins, Dallas, Edrington, Christopher S., Ordóñez, Juan Carlos, Foo, Simon Y., Moss, Pedro L., Florida State University, College of Engineering, Department of Electrical and...
Show morePerkins, Dallas, Edrington, Christopher S., Ordóñez, Juan Carlos, Foo, Simon Y., Moss, Pedro L., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show moreThe 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.
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Date Issued: 2018
Identifier: 2018_Su_Perkins_fsu_0071E_14716
Format: Thesis

Title: Distributed Energy Management Utilizing Model Predictive Control for Naval Ship Applications.
Creator: Gonsoulin, David E., Clark, Jonathan E., Faruque, Md Omar, Pamidi, Sastry V., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: 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...
Show moreFuture 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).
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Date Issued: 2018
Identifier: 2018_Su_Gonsoulin_fsu_0071E_14741
Format: Thesis

Title: Design and Implementing Multipurpose Sensor Network for Smart City Monitoring.
Creator: Cai, Donglin, Arghandeh, Reza, Pamidi, Sastry V., Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: 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...
Show moreWeather 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.
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Date Issued: 2018
Identifier: 2018_Su_CAI_fsu_0071N_14789
Format: Thesis

Title: Sensor Fault Detection and Isolation in Power Systems.
Creator: Yang, Huawei, Edrington, Christopher S., Ordóñez, Juan Carlos, Moss, Pedro L., Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and...
Show moreYang, Huawei, Edrington, Christopher S., Ordóñez, Juan Carlos, Moss, Pedro L., Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show moreIn 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.
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Date Issued: 2018
Identifier: 2018_Su_Yang_fsu_0071E_14730
Format: Thesis

Title: Identification of the Inertial Parameters of Manipulator Payloads.
Creator: Reyes, Ryan-David, Department of Electrical and Computer Engineering
Abstract/Description: Momentum based motion planning allows small and lightweight manipulators to lift loads that exceed their rated load capacity. One such planner, Sampling Based Model Predictive Optimization (SBMPO) developed at the Center for Intelligent Systems, Control, and Robotics (CISCOR), uses dynamic and kinematic models to produce trajectories that take advantage of momentum. However, the inertial parameters of the payload must be known before the trajectory can be generated. This research utilizes a...
Show moreMomentum based motion planning allows small and lightweight manipulators to lift loads that exceed their rated load capacity. One such planner, Sampling Based Model Predictive Optimization (SBMPO) developed at the Center for Intelligent Systems, Control, and Robotics (CISCOR), uses dynamic and kinematic models to produce trajectories that take advantage of momentum. However, the inertial parameters of the payload must be known before the trajectory can be generated. This research utilizes a method based on least squares techniques for determining the inertial parameters of a manipulator payload. It is applied specifically to a two degree of freedom manipulator. A set of exciting trajectories, i.e., trajectories that sufficiently excite the manipulator dynamics, in task space will be commanded to the system. Inverse kinematics are then used to determine the desired angle, angular velocity, and angular acceleration for the manipulator joints. Using the sampled torque, joint position, velocity, and acceleration data, the least squares technique produces an estimate of the inertial parameters of the payload. This paper focuses on determining which trajectories produce sufficient excitation so that an adequate estimate can be obtained.
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Date Issued: 2014
Identifier: FSU_migr_uhm-0418
Format: Thesis

Title: An Isolated Modular Multilevel Multifunctional DC/DC Converter Based Battery Energy Storage System with Enhanced Fault Performance.
Creator: Mo, Ran, Li, Hui, Ordóñez, Juan Carlos, Lipo, T. A., Edrington, Christopher S., Steurer, Michael, Florida State University, College of Engineering, Department of Electrical and...
Show moreMo, Ran, Li, Hui, Ordóñez, Juan Carlos, Lipo, T. A., Edrington, Christopher S., Steurer, Michael, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show moreNowadays 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.
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Date Issued: 2017
Identifier: 2018_Sp_Mo_fsu_0071E_14211
Format: Thesis

Title: Intelligent Energy and Operation Management of AC, DC and Hybrid Microgrids Based on Evolutionary Techniques.
Creator: Papari, Behnaz, Edrington, Christopher S., Clark, Jonathan E., Pamidi, Sastry V., Moss, Pedro L., Florida State University, College of Engineering, Department of Electrical and...
Show morePapari, Behnaz, Edrington, Christopher S., Clark, Jonathan E., Pamidi, Sastry V., Moss, Pedro L., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Intelligent energy management systems (EMSs) play pivotal roles for microgrids (MGs). The integration of distributed generators (DGs), energy storage devices (ESDs), electrical vehicles (EVs), and flexible loads in a large-scale system of interconnected MGs needs a local management and control platforms to avoid probable integration issues. Most of the small scale aforementioned components are operated in low voltage (LV) power networks which require optimal strategies to achieve sufficient...
Show moreIntelligent energy management systems (EMSs) play pivotal roles for microgrids (MGs). The integration of distributed generators (DGs), energy storage devices (ESDs), electrical vehicles (EVs), and flexible loads in a large-scale system of interconnected MGs needs a local management and control platforms to avoid probable integration issues. Most of the small scale aforementioned components are operated in low voltage (LV) power networks which require optimal strategies to achieve sufficient performance to operate interconnected to other MGs and upstream networks. Thus, an active energy management strategy is required for off and on grid modes of terrestrial and shipboard MGs to satisfy all demands and minimize unwanted outcomes. Due to the high penetration of renewable energy sources (RESs) and their output fluctuations in MGs, stochastic analysis besides deterministic should be considered to reduce the uncertainty effects of RESs based on their probabilistic nature. Robust EMSs are needed to diminish prediction errors and improve the reliability of power supplies in hybrid and interconnected MGs. Nevertheless, qualified approach to fulfill EMS for LV MGs in the large-scale will be challenging in both grid operation modes. Optimization modules into tertiary management layer have considered as a potential solution in order to actualize control strategy of the terrestrial or ship MGs with different types of practical constraints. However, each of these methods not only yield benefits but also bring new challenges related to their shortage. Different approaches have been considered to fulfill the EMS requirements of MGs. A large amount of literature focuses on the management strategy of MG in an off-line manner rather than multiple MGs which interact with each other and an upstream network in an on-line manner. In addition, the most commonly used optimization modules in EMSs do not meet the computational burden and convergence capability trade-off required for real-time applications. This report proposes a heuristic optimization approach for distributed control and management of hybrid MGs for real-time requirements. The Crow Search Algorithm (CSA) offers a superior method to move traditional non-linear optimization approaches since its fewer control parameters permit a rapid response compared to other search approaches. Moreover, a distributed fashion CSA (DCSA) is implemented to fulfill linear and non-linear solver requirements of real-time EMSs for hybrid power distribution system.
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Date Issued: 2018
Identifier: 2018_Sp_Papari_fsu_0071E_14436
Format: Thesis

Title: Component Analysis-Based Change Detection for Sea Floor Imagery and Prelude to Sea-Surface Object Detection.
Creator: G-Michael, Tesfaye, Roberts, Rodney G., Meyer-Bäse, Anke, Meyer-Baese, U., Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and Computer...
Show moreG-Michael, Tesfaye, Roberts, Rodney G., Meyer-Bäse, Anke, Meyer-Baese, U., Foo, Simon Y., Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show moreIn 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.
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Date Issued: 2017
Identifier: 2018_Sp_GMichael_fsu_0071E_14301
Format: Thesis

Title: Combined Electrical and Thermal Models for Integrated Cryogenic Systems of Multiple Superconducting Power Devices.
Creator: Satyanarayana, Sharath R. (Sharath Raghav), Pamidi, Sastry V., Foo, Simon Y., Bernadin, Shonda, Florida State University, College of Engineering, Department of Electrical and...
Show moreSatyanarayana, Sharath R. (Sharath Raghav), Pamidi, Sastry V., Foo, Simon Y., Bernadin, Shonda, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: High Temperature Superconducting (HTS) technology is a potential option for applications that require high power densities for lightweight and compact solutions for transportation systems such as electric aircrafts and all-electric Navy ships. Several individual HTS power devices have been successfully demonstrated for these systems. However, the real benefit lies in providing the system level design flexibility and operational advantages with an integrated cryogenic system. A centralized...
Show moreHigh Temperature Superconducting (HTS) technology is a potential option for applications that require high power densities for lightweight and compact solutions for transportation systems such as electric aircrafts and all-electric Navy ships. Several individual HTS power devices have been successfully demonstrated for these systems. However, the real benefit lies in providing the system level design flexibility and operational advantages with an integrated cryogenic system. A centralized cryogenic cooling technology is being explored to serve multiple HTS devices in a closed loop system. This provides high efficiency and permits directing the cooling power to where it is needed depending on the mission at hand which provides operational flexibility. Design optimization, risk mitigation and the operational characteristics under various conditions need to be studied to increase the confidence level in HTS technology. Development of simpler and cost-efficient cryogenic systems are essential to make HTS systems attractive. Detailed electrical and cryogenic thermal models of the devices are also necessary to understand the of risks in HTS power systems and to devise mitigation techniques for all the potential failure modes. As the thermal and electrical characteristics of HTS devices are intertwined, coupled thermal and electrical models are necessary to perform system level studies. To enable versatile and fast models, the thermal network method is introduced for cryogenic systems. The effectiveness of the modelling technology was demonstrated using case studies of multiple HTS devices in a closed loop cryogenic helium circulation system connected in different configurations to access the relative merits of each configuration. Studies of transient behavior of HTS systems are also important to understand the response of a large HTS system after one of the cryogenic cooling components fails. These studies are essential to understand the risks and potential options in the design or in operations to mitigate some of the risks. Thermal network models developed in this study are also useful to study the temperature evolution along the whole system as a function of time after a component fails. The models are useful in exploring the design options to extend the time of operation of a device such as a HTS cable after the failure of the cryogenic system.
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Date Issued: 2018
Identifier: 2018_Su_Satyanarayana_fsu_0071N_14787
Format: Thesis

Title: Application and Analysis of the Extended Lawrence Teleoperation Architecture to Power Hardware-in-the-Loop Simulation.
Creator: Langston, James, Edrington, Christopher S., Vanli, Omer Arda, Steurer, Michael, Roberts, Rodney G., Faruque, Md Omar, Florida State University, College of Engineering,...
Show moreLangston, James, Edrington, Christopher S., Vanli, Omer Arda, Steurer, Michael, Roberts, Rodney G., Faruque, Md Omar, Florida State University, College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: 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...
Show morePower 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.
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Date Issued: 2018
Identifier: 2018_Sp_Langston_fsu_0071E_14321
Format: Thesis

Title: Intelligent Transport System and Wireless Communication Technology Overview for Safety in Connected Vehicles.
Creator: Raj, Jayesh, Harvey, Bruce A., Foo, Simon Y., Bernadin, Shonda, Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: Vehicular communication network consists of different wireless communication technologies working in conjunction with each other. These different wireless communication technologies have different technical parameters. Wireless communication technology includes Dedicated Short-Range Communication, WiFi, WiMAX etc. depending upon their network range, data bit transfer rate, safe effective maximum intended communication range, modulation technique adopted and many more, are deployed for...
Show moreVehicular communication network consists of different wireless communication technologies working in conjunction with each other. These different wireless communication technologies have different technical parameters. Wireless communication technology includes Dedicated Short-Range Communication, WiFi, WiMAX etc. depending upon their network range, data bit transfer rate, safe effective maximum intended communication range, modulation technique adopted and many more, are deployed for specific safety application. The main objective of Intelligent Transport System (ITS) is Safety. Under safety application there are many objectives including safe approach to the intersection, pre and post-crash warning, total loss control correction etc. these safety applications require specific parameter of communication technology i.e. for safe intersection approach data bit rate need not to be high and other safety application seeks different parameter. It is obvious that no single wireless communication technology could fulfill all the specifics of communication technology and objective of ITS. In this research important wireless communication discussed. Their pros and cons are summarized in the vehicular environment. In order to show the importance of wireless communication technology in Vehicular network, one among many safety applications is simulated. In the simulation, safe approach to unsignalized intersection is simulated. Simulation is performed on VISSIM software developed by PTV group, Germany. Simulation is based on Nakagami Wireless probabilistic model under relaxed radio condition (no interferences) and finally conclusion is made.
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Date Issued: 2018
Identifier: 2018_Fall_RAJ_fsu_0071N_14945
Format: Thesis

Title: Shape Data Analysis for Machine Learning in Power Systems Applications.
Creator: Cordova Guillen, Jose David, Pamidi, Sastry V., Srivastava, Anuj, Ozguven, Eren Erman, Li, Hui, Foo, Simon Y., Florida State University, FAMU-FSU College of Engineering,...
Show moreCordova Guillen, Jose David, Pamidi, Sastry V., Srivastava, Anuj, Ozguven, Eren Erman, Li, Hui, Foo, Simon Y., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: This dissertation proposes the use of the shape of data as a new feature to improve and develop new in machine learning and deep learning algorithms utilized for different power systems applications. The new features are obtained through Shape Data Analysis (SDA), an emerging field in Statistics. SDA is used to obtain the shape of the data structure to observe different patterns developed under distribution networks abnormal conditions, as well as determining the shape of load curves to...
Show moreThis dissertation proposes the use of the shape of data as a new feature to improve and develop new in machine learning and deep learning algorithms utilized for different power systems applications. The new features are obtained through Shape Data Analysis (SDA), an emerging field in Statistics. SDA is used to obtain the shape of the data structure to observe different patterns developed under distribution networks abnormal conditions, as well as determining the shape of load curves to improve existing electrical load forecasting algorithms. Specifically, shape-based data analysis is implemented and developed for two different applications: electrical fault detection and electrical consumption short-term load forecasting. The algorithms proposed are implemented on data collected from Intelligent Electronic Devices (IEDs), Phasor Measurement Units (PMUs), and Supervisory Control and Data Acquisition (SCADA) systems in power distribution networks.
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Date Issued: 2019
Identifier: 2019_Spring_CordovaGuillen_fsu_0071E_12807
Format: Thesis

Title: Heterogeneous Data Fusion for Performance Improvement in Electric Power Systems.
Creator: Gilanifar, Mostafa, Wang, Hui, Moses, Ren, Ozguven, Eren Erman, Park, Chiwoo, Vanli, Omer Arda, Florida State University, FAMU-FSU College of Engineering, Department of...
Show moreGilanifar, Mostafa, Wang, Hui, Moses, Ren, Ozguven, Eren Erman, Park, Chiwoo, Vanli, Omer Arda, Florida State University, FAMU-FSU College of Engineering, Department of Industrial and Manufacturing Engineering
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Abstract/Description: The performance of the electric power system determines the cost-effective and reliable energy supply to maintain operations in a city. Electric power system performance improvement is important for utility companies in different aspects from maintenance and reliability to the environment. In a modern city, new monitoring devices are deployed to collect data in the electric power system and other city systems such as transportation. The heterogeneous data collected by new monitoring devices...
Show moreThe performance of the electric power system determines the cost-effective and reliable energy supply to maintain operations in a city. Electric power system performance improvement is important for utility companies in different aspects from maintenance and reliability to the environment. In a modern city, new monitoring devices are deployed to collect data in the electric power system and other city systems such as transportation. The heterogeneous data collected by new monitoring devices reveal the multi-community interactions in the electric power system and also reveal the interdependencies between different city systems such as electric power system and transportation system. This dissertation research studied the development of data fusion and multi-task learning algorithms in improving short-term load forecasting, fault detection, and rare faulty event detection by leveraging heterogeneous and multi-community data. The theoretical contribution of this study lies in the method selection and comparison for fusing transportation and electricity consumption data, and new methods of capturing between-community relatedness in guiding the knowledge transfer for the learning of Bayesian spatiotemporal Gaussian Process model, fault classification, and semi-supervised learning so that the performance of these algorithms are not limited by the specificity in the dataset and can reduce overfitting issues. The first study aims to forecast the electric load consumption and traffic counts accurately which benefits from the data fusion techniques in order to fill the lack of sufficient data. Accurate forecasting is mostly dependent on sufficient and reliable data. Traditional data collection methods may be necessary but not sufficient due to their limited coverage and expensive cost of implementation and maintenance. The advances in sensor networks and recent technological developments emerge a new opportunity. Specifically, data fusion tools can be used for improving the limited resolution in the data due to limitations on time frame, cost, accuracy, and reliability. In this study, a Bayesian spatiotemporal Gaussian Process model is proposed which employs the most informative spatiotemporal interdependency among its system, and covariates from other city systems. Results obtained from real-world data from the City of Tallahassee in Florida show that the multi-network data fusion framework improves the accuracy of load forecasting, and the proposed model outperforms all the existing methods. The second study is conducted for short-term electricity load forecasting for a residential community in a city which suffers from low-resolution data. Historically, extensive research has been conducted to improve the load forecasting accuracy using single-task machine learning methods, which rely on the information from one single data source. Such methods have limitations with low-resolution data from meters. Fusing the electricity consumption data from multiple communities can improve forecasting accuracy. Recently, an emerging family of machine learning algorithms, multi-task learning (MTL), have been developed and can be utilized for short-term load forecasting. However, appropriate modeling of the relatedness to enable the between-community knowledge transfer remains a challenge. This research proposes an improved MTL algorithm for a Bayesian spatiotemporal Gaussian process model (BSGP) to characterize the relatedness among the different communities in a city. It hypothesizes on the similar impacts of environmental and traffic conditions on electricity consumption in improving the accuracy of short-term electricity load forecasting. Furthermore, this study proposes a low ranked dirty model along with an iterative algorithm to improve the learning of model parameters under an MTL framework. This study used real-world data from two residential communities to demonstrate the proposed method through comparison with state-of-the-art methods. The third study investigates the fault (type) detection in power distribution systems by using the Distribution Phasor Measurement Unit (D-PMU) data. Historically, Traveling-wave and impedance-based methods are among the most notable fault detection techniques. The disadvantage of the impedance methods is that they rely on the knowledge of the network components characteristics. Although Traveling-wave methods have shown to be accurate, they require high-frequency measurements for reliable performance. Such high-resolution measurement data is expensive and may not be available all the times. More recently, D-PMU devices are used to observe better, record, and provide high-resolution voltage and current phasor measurements. In this study, a Multi-task Logistic Low-Ranked Dirty Model (MT-LLRDM) for fault detection is proposed to improve the accuracy by utilizing the similarities in the fault data streams among multiple locations across a power distribution network. The captured similarities supplement the information to the task of fault detection at a location of interest, creating a multi-task learning framework and thereby improving the learning accuracy. The algorithm is validated with real-time D-PMU streams from a hardware-in-the-loop testbed that emulates real field communication and monitoring conditions in distribution networks. Finally, a study is conducted for the fault (type) detection in power distribution systems when data suffers from the lack of labeled data. Supervised multi-task learning methods have limitations when there are a lot of missing data in the target domain especially records on fault data are lacking label. Labeled fault data can be very limited in the target community since fault data labeling is very time-consuming. Therefore, in this study, a multi-task semi-supervised learning method is proposed to simultaneously explore the latent structure in the unlabeled data to learn the labels and leverage the data from multiple locations in the power systems to improve the fault detection.
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Date Issued: 2019
Identifier: 2019_Spring_Gilanifar_fsu_0071E_15164
Format: Thesis

Title: Current Control Strategies for Three-Phase Paralleled SiC Inverters.
Creator: Wang, Lu, Li, Hui, Clark, Jonathan E., Lipo, T. A., Steurer, Michael, Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
Abstract/Description: With more renewable energy integrated into the existing power consumption, power electronics play an important part to convert and control the power. Power inverters employ power semiconductors to converter DC into AC, which is an essential part in the renewable energy utilization. The paralleled transformer-less inverters are well adopted in the industry for large capacity grid-tie application. Compared with the centralized inverter, inverters in parallel can offer higher power rating,...
Show moreWith more renewable energy integrated into the existing power consumption, power electronics play an important part to convert and control the power. Power inverters employ power semiconductors to converter DC into AC, which is an essential part in the renewable energy utilization. The paralleled transformer-less inverters are well adopted in the industry for large capacity grid-tie application. Compared with the centralized inverter, inverters in parallel can offer higher power rating, higher reliability, and lower grid-side current harmonics. Transformers are commonly used in the grid-tie system to provide galvanic isolation and voltage ratio transformations. Eliminating transformers will be a great benefit to further improve the system efficiency, reduce the size and weight. However, removal of the transformer would result in ground leakage current between the DC input side and the grid ground. The emerging wide band gap (WBG) devices are bringing significant opportunities for inverters towards higher efficiency and higher power density, due to their substantial switching loss reduction over Si devices. Silicon carbide (SiC) adoption also brings new control challenges to the three-phase paralleled transformer-less inverters. The voltage slew rate can be as high as dozens or hundreds of volts per nanosecond and the harmonic frequency related with the turning-on and turning-off of the devices may be up to several hundreds of mega-hertz, these high dv/dt and di/dt can generate high frequency EMI noise that propagates to the whole system including the power stage and control circuits, and raise the issue of increased electromagnetic interference (EMI). With high switching frequency, it is more difficult to control the circulating current among paralleled inverters. The conventional carrier synchronization method cannot be applied due to the impact of communication and sample delay. Limited controller resource also prevents sophisticated control algorithms. In this research, a five-level T-type (5LT2) PV inverter paralleled through inter-cell transformer (ICT) is presented to elaborate the challenges and demonstrate the advantages in three-phase SiC inverter. There are three key current in the 5LT2 PV inverter: circulating current, grid current, and ground leakage current. Circulating current is suppressed by the ICT and further controlled by a current controller. With increased switching frequency and multilevel topology, it is possible for a SiC device based grid connected converter to achieve filter-less function and utilize the grid impedance for its switching harmonic attenuation. Analysis shows that the conventional control method with instantaneous grid voltage feedforward (IGVF) will significantly limit the bandwidth or stability margin of a filter-less grid-connected inverter, thus make the inverter sensitive to grid disturbance. Two proposed grid voltage feedforward control methods, which require little additional computation resources, are presented to suppress the grid voltage disturbance. The increased switching efficiency is beneficial to the high frequency (HF) ground leakage current suppression, since the common mode (CM) choke can be much smaller. The 5LT2 inverter has a significant common mode voltage (CMV) reduction compared to that of a 3-level T-type (3LT2) inverter. However, the low frequency (LF) ground leakage current caused by neutral point (NP) voltage oscillation becomes a new issue in larger power rating multi-level inverters. A LF CMV compensation method is proposed to suppress the LF CMV. In this research, a control system is developed for a 60 kW three-phase paralleled transformer-less filter-less SiC PV inverter, which achieves a power density of 27 W/in3 and 3 kW/kg with nature convection, and measured peak efficiency of 99.2%.
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Date Issued: 2018
Identifier: 2019_Spring_Wang_fsu_0071E_14943
Format: Thesis

Title: A Steady-State Stability Analysis of Uniform Synchronous Power Grid Topologies.
Creator: Stright, James, Edrington, Christopher S., Oates, William, Faruque, Omar, Andrei, Petru P., Florida State University, FAMU-FSU College of Engineering, Department of Electrical...
Show moreStright, James, Edrington, Christopher S., Oates, William, Faruque, Omar, Andrei, Petru P., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Electric power grids are evolving rapidly as increased emphasis is placed on integration of renewable resources into existing power infrastructures and as new paradigms for power production and distribution, such as microgrids, are developed. Resultant grid configurations must meet the needs and requirements of existing and evolving population distributions, feasible production facilities placement, and environmental stewardship associated with power transmission and distribution...
Show moreElectric power grids are evolving rapidly as increased emphasis is placed on integration of renewable resources into existing power infrastructures and as new paradigms for power production and distribution, such as microgrids, are developed. Resultant grid configurations must meet the needs and requirements of existing and evolving population distributions, feasible production facilities placement, and environmental stewardship associated with power transmission and distribution infrastructures. In most developed regions, large-scale transmission infrastructures are well established, and their geographic routing is increasingly difficult to alter or amend. Renewables integration, however, directs far more attention at the power distribution level. As more local power is produced, often intermittent in nature and sometimes by consumers themselves, power distribution becomes more problematic in several respects. Conceptually, “the grid” becomes less a fixed entity and more an ever-changing amalgam of sources, loads, and preferred routes among them. All such routes must meet certain fundamental physical requirements, such as current and voltage handling capabilities. For power quality and reliability reasons, however, they also need to be “stable” in several senses, and there is currently no comprehensive approach to selecting available or potential routes to optimize the resultant “stability” of the configuration, in any of the various senses. This work develops such an approach, applicable to the steady-state stability of grids subject to several simplifying constraints. That is, it provides a framework for analyzing the steady-state stabilities of all grid topologies for grids that meet those constraints. The approach is general and abstract in nature, as this work focuses not on particular commonly studied grids but instead on the characteristics of grid topologies that lend themselves to greater or lesser degrees of steady-state stability. As a baseline study, only grids having synchronous generators are considered, with the expectation that future work will adapt inertia-based models of renewable sources to this or a similar approach. Although the approach itself is the main contribution, several interesting discoveries have already been made regarding optimal configurations of some simple topologies and on quantifying how richness of grid interconnections influences grid steady-state stability.
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Date Issued: 2019
Identifier: 2019_Spring_Stright_fsu_0071E_15115
Format: Thesis

Title: Speaker-Dependent Acoustic Emotion Recognition for Vehicle-Centric Applications.
Creator: Udhan, Tejal, Bernadin, Shonda, Sobanjo, John Olusegun, Foo, Simon Y., Harvey, Bruce A., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and...
Show moreUdhan, Tejal, Bernadin, Shonda, Sobanjo, John Olusegun, Foo, Simon Y., Harvey, Bruce A., Florida State University, FAMU-FSU College of Engineering, Department of Electrical and Computer Engineering
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Abstract/Description: Speech is the most natural and fastest method of communication between humans. This fact compelled researchers to study acoustic signals as a fast and efficient means of interaction between humans and machines. For authentic human-machine interaction, the method requires that the machines should have the sufficient intelligence to recognize human voices and their emotional state. It is well-known that the emotional state of human drivers highly influences his/her driving performance. For...
Show moreSpeech is the most natural and fastest method of communication between humans. This fact compelled researchers to study acoustic signals as a fast and efficient means of interaction between humans and machines. For authentic human-machine interaction, the method requires that the machines should have the sufficient intelligence to recognize human voices and their emotional state. It is well-known that the emotional state of human drivers highly influences his/her driving performance. For example, there are many reports that describe road-rage incidents where drivers become emotionally enraged due to the actions of another driver. This anger may lead to a high-speed chase, tailgating, and sometimes even death due to a traffic crash or physical contact. If a car is ‘intelligent-enough’ to respond to a driver’s emotional state, it may be able to thwart negative outcomes of road-rage incidents. Speech emotion recognition, extracting the emotional state of speakers from acoustic data, plays an important role in enabling machines to be ‘intelligent’. Speech emotion recognition is an emerging field and presents many challenges. The set of most powerful features which can distinguish different emotions is not defined; hence, the selection of features is a critical task. Acoustic variability presented by numerous speech properties, such as length and complexity of human speech utterance, speaker’s gender, speaking styles and rate of speech, directly affects the most common speech features; thereby affecting the system performance. Most of the researchers used statistical approaches to recognize human speech; however statistical methods are complex and need more computational time. Moreover, emotion recognition being the developing field, researchers are exploring facial, gestural and acoustical features for emotion recognition. However, for vehicle-centric applications, audio and speech processing may provide better noninvasive and less distracting solutions than other interactive in-vehicle infotainment systems. Hence, acoustic feature extraction for emotion recognition in human drivers is a preferred design choice of this research. The goal of this research is to develop an optimal feature extraction algorithm for emotion recognition of four most common emotions (anger, happy, sad and no emotion). In this dissertation, six acoustic features are studied using decision-tree based algorithms to recognize speech-based human emotions and reduce the complexity of the system. The speech features used are pitch, intensity, frequency formants, jitter, shimmer and zero crossing rate. Pitch and intensity are qualitative voice feature, frequency formants and jitter provide the spectral features and zero-crossing rate and shimmer suffice as temporal features of human acoustical speech. The combination of different types of speech features is utilized to increase the accuracy of system. The decision tree-based algorithms are designed in MATLAB and are calculated using confidentiality-interval for each feature. For acoustic data visualization, PRAAT software is used. The system is designed for speaker-dependent emotion recognition since the accuracy of system is more as the utilized features are qualitative voice features; which are best-suited for emotion recognition. Data from two males and two females is analyzed for this dissertation. For the actual realization of system, noise analysis is performed using 5dB, and 15 dB signal-to-noise ratio levels. These are minimum and maximum noise levels experienced while driving on a freeway and parking lot. This dissertation is composed of five chapters. Chapter 1 presents the mechanism of human speech production and human emotions in speech. It comprises of various emotions and importance of acoustic signal for emotion recognition. Chapter 2 includes different local and global acoustic features, existing methods of speech recognition and emotion recognition and discusses the weaknesses of existing speech recognition systems for acoustical emotion recognition using various acoustic features and analysis algorithms. Chapter 3 outlines the proposed solution for acoustic emotion recognition using decision-tree based algorithm. It includes a description of each acoustical feature, data preparation techniques, data analysis methods, and algorithm design. Chapter 4 consists of results, discussion and comparison of proposed algorithm with state-of-the-art acoustic emotion recognition algorithms. Finally, conclusion, limitations and future work is discussed in chapter 5.
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Date Issued: 2018
Identifier: 2019_Spring_Udhan_fsu_0071E_14833
Format: Thesis

Title: High Voltage Insulation Systems for Gas-Cooled Superconducting Power Devices.
Creator: Al-Taie, Aws Habeeb Mohammed, Pamidi, Sastry V., Ordóñez, Juan Carlos, Foo, Simon Y., Graber, Lukas, Anubi, Olugbenga Moses, Florida State University, FAMU-FSU College of...
Show moreAl-Taie, Aws Habeeb Mohammed, Pamidi, Sastry V., Ordóñez, Juan Carlos, Foo, Simon Y., Graber, Lukas, Anubi, Olugbenga Moses, Florida State University, FAMU-FSU College of Engineering (Tallahassee, Fla.), Department of Electrical and Computer Engineering
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Abstract/Description: Demand for electrical power is increasing around the globe to keep up with the ever-increasing annual load growth, which in turn requires new power sources to be installed. As a society, there is a greater emphasis for power sources to be environmentally friendly, such as wind and solar. For large-scale wind and solar power sources, electric utilities need to install them in the optimal regions which are generally far away from the load centers. Hence, efficient and high capacity power...
Show moreDemand for electrical power is increasing around the globe to keep up with the ever-increasing annual load growth, which in turn requires new power sources to be installed. As a society, there is a greater emphasis for power sources to be environmentally friendly, such as wind and solar. For large-scale wind and solar power sources, electric utilities need to install them in the optimal regions which are generally far away from the load centers. Hence, efficient and high capacity power transmission solutions are required to integrate these energy sources into the power grid. Another new trend of electrifying the transportation sector with electric ships and aircrafts requires compact electric power devices with high volumetric and gravimetric power densities. Therefore, electric utilities and the transportation sector have been exploring innovative solutions for energy efficient and high-power density technology options, which include utilizing superconducting power devices. High temperature superconducting (HTS) power cables and other devices have been developed and installed in several countries around the world to achieve more efficient and significantly compact devices compared to their copper counterparts. A long-term vision for the future power transmission is a cross-country multi-terminal DC HTS cable transmission system. Gas-cooled HTS power cables are being explored for electric transportation applications, including aircrafts and ships, due to asphyxiation risks associated with liquid nitrogen. Use of a gas as the cryogen instead of a liquid, however, poses technical challenges resulting from the reduced heat capacity and lower dielectric strength which could affect the overall performance of HTS cables. When helium gas is used as the cryogen in HTS power devices, the electrical insulation method and materials utilized for liquid nitrogen cooled HTS cables are not applicable. For liquid nitrogen cooled HTS power cables for electric utility applications, lapped tape insulation has been used to achieve operating voltages in excess of 100 kV. When this same design is utilized for electrical insulation system of helium gas cooled HTS cables, partial discharge (PD) occurs at voltages <10 kV, limiting the operational voltages. The butt gaps within the lapped tape insulation layers trap helium gas and cause the associated field enhancements leading to low partial discharge inception voltages. The research described in this dissertation focused on extending the understanding the technology challenges associated with the use of gas media as part of the electrical insulation system at cryogenic temperatures. The emphasis was on the development of the concept of superconducting gas insulated line (S-GIL) as an alternative to lapped tape electrical insulation system to HTS power cables to enable higher operating voltages for helium gas cooled HTS power cables. The S GIL, which is similar to the Gas Insulated Line (GIL), was conceptualized recently at Florida State University's Center for Advanced Power Systems (FSU-CAPS). The S-GIL utilizes the flow of pressurized cryogenic gas instead of stagnant room temperature gas for GIL. The S-GIL addresses the challenge of low partial discharge inception voltages (PDIV) in lapped tape insulated, gas cooled HTS cables by eliminating the need for solid insulation layers on the cable. However, the need to maintain the cable on the axis of the cryostat imposes the requirement of insulator spacers. This work explored bundled tubular spacers for S-GIL as an option for spacers and 1-m long prototype cables were fabricated and characterized in gaseous helium and helium-based gas mixtures. Surface flashover along the surface of the spacers is expected to be one of the design factors which influences the voltage rating for S-GIL. The designs considered different tube materials and gases and a variety of experiments were conducted at room temperature and at cryogenic temperatures to gain a thorough understanding of the S-GIL design limitations. To gain further understanding of the limits of the S-GIL concept, the design was tested with liquid nitrogen as the insulation medium to decipher the role of the intrinsic dielectric strength of the insulation medium. Besides providing additional insights into S-GIL concept, the liquid cooled alternative will have applications in terrestrial power systems and transportation sector where higher operating voltages and efficient thermal designs are needed. The research also focused on investigating the surface flashover phenomenon in GHe environment. This included investigating the triple point where the conductor, solid insulation material, and gas insulation media meet. Surface flashover measurements were performed with varying gas density, temperature, gas composition, solid insulation material, applied voltage waveform, and electric field strength and distribution.
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Date Issued: 2019
Identifier: 2019_Summer_AlTaie_fsu_0071E_15386
Format: Thesis

Title: Enhancing the Observability of Distribution Systems State Estimation.
Creator: Sanchez Cifuentes, Andres F. (Andres Felipe), Anubi, Olugbenga Moses, Li, Hui, Florida State University, FAMU-FSU College of Engineering (Tallahassee, Fla.), Department of...
Show moreSanchez Cifuentes, Andres F. (Andres Felipe), Anubi, Olugbenga Moses, Li, Hui, Florida State University, FAMU-FSU College of Engineering (Tallahassee, Fla.), Department of Electrical Engineering
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Abstract/Description: Monitoring distribution systems via state estimation can be affected negatively if the measurements are modified by malicious attacks. Under the assumption that the measurements devices were successfully attacked is necessary to detect the presence of the bad data. After detecting bad data artificial measurements, called Pseudomeasurements, are used to replace the and then run again the state estimation algorithm for system monitoring. The procedure previously described is shown in this project.
Date Issued: 2019
Identifier: 2019_Summer_Sanchez_fsu_0071N_15452
Format: Thesis

Title: A Novel Approach for AI Based Driver Behavior Analysis Model Using Visual and Cognitive Data.
Creator: Bhattacharya, Sylvia, Bernadin, Shonda, Sobanjo, John Olusegun, Foo, Simon Y., Roberts, Rodney G., Florida State University, FAMU-FSU College of Engineering (Tallahassee, Fla.),...
Show moreBhattacharya, Sylvia, Bernadin, Shonda, Sobanjo, John Olusegun, Foo, Simon Y., Roberts, Rodney G., Florida State University, FAMU-FSU College of Engineering (Tallahassee, Fla.), Department of Electrical and Computer Engineering
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Abstract/Description: In recent years there has been increasing research on incorporating intelligent driver assistance systems (IDAS) into vehicular platforms to help drivers make better driving decisions and to make the roadways safer. The percentage of highway accidents in United States is steadily increasing every year. Current IDAS such as collision detection and avoidance systems use models of human behavior to improve the reliability of these systems and to help decrease driver workload. Modeling driver...
Show moreIn recent years there has been increasing research on incorporating intelligent driver assistance systems (IDAS) into vehicular platforms to help drivers make better driving decisions and to make the roadways safer. The percentage of highway accidents in United States is steadily increasing every year. Current IDAS such as collision detection and avoidance systems use models of human behavior to improve the reliability of these systems and to help decrease driver workload. Modeling driver behavior is not a simple task. It involves aspects of psychology, physiology, data analysis, signal processing and engineering, to name a few. In the case of lane changing events, early detection of a driver's intent to change lanes can be beneficial to systems that involve vehicle- to- vehicle communications. Moreover, a lane change prediction system, could be integrated into automatic aviation of the turn signal. Most published studies of lane change events are based on large scale vehicle trajectory data i.e steering angle, velocity and accelerations. Using this approach, a lane change prediction event is typically detected as soon as the driver initiates a lane change maneuver. Most vehicular trajectory model fails when a driver forgets to enable a turn signal before making a lane change. Hence, irrespective of having many automatic features equipped in modern day cars, the accident rate is still not decreasing. In such cases, biomedical signals may play an important role in detecting early driver intention. Besides vehicle dynamics (lane change, braking, acceleration), it is also important to understand the mental workload of the driver to maintain safety while travelling. Mental workload is directly related to distracted or non- distracted driving which varies with emotional changes. The mental workload can tremendously impact driving behavior and hence the detection of these factors will add driver safety on roadway. In this dissertation, we propose to utilize visual and cognitive information to detect a driver's intent to change lanes and predict their mental distraction. Mental workload varies in different situations. For example, the amount of focus required during a lane change maneuver can be disrupted due to a secondary task like cell phone usage, talking to a co-passenger, a baby crying in the back seat or an unexpected news broadcasted on the car radio. Most of the research focuses on distracted driving using a cell phone, although more number of accidents are accounted on highways during talking to passengers. In this research, conversational task with co –passengers are considered as a situation, for intent analysis and cognitive workload analysis of the driver. A novel approach is developed that considers eye movements and cognitive attentiveness as distraction levels are increased during two different scenarios (i) single passenger driving and (ii) driving with passengers. This involves aspects of statistical analysis, signal processing, software engineering and machine learning techniques. Different types of statistical analysis techniques like normalization, correlation models are used in this research. Software development with TCL scripting is utilized to design real time virtual scenario for data collection. Signal Processing techniques like power spectral analysis, cognitive engagement ratio etc. are utilized to analyze brain signals. Artificial Intelligence methods are applied to help make accurate predictions of driver intent. Finally, Artificial Intelligence is a broad field that uses deep learning and machine learning algorithms to mimic human cognition. This research utilizes innovative machine learning tools like sklearn and tensor flow, to automate the process of behavior analysis. This work will inform research on lane-change prediction, behavior prediction and vehicular feedback analysis using an IDAS environment. Furthermore, this work considers factors that may impact the lane change detection and prediction of differential drivers including elderly drivers. This work also contributes an individual database that records driving behaviors during conversational tasks that other researchers can use to conduct behavior analysis research associated with this driving scenario. To author's knowledge this is the first database that will be made available publicly for use in conversational task scenario in driving. This dissertation is composed of five chapters. Chapter 1 presents the introduction and back ground of IDAS research. It highlights various factors that contribute to detrimental road crashes and describes the research gap in this field. Chapter 2 includes a detailed literature review of all the studies that has been conducted in this field and also includes essential biological and artificial intelligence methods that are important to know in order this field. Chapter 3 outlines the methodology that has been adopted in this project. It includes description of virtual reality development procedure for collecting data from driver simulator, data collection procedure for various parameter in this research and also describes the mathematical models of each concept. Chapter 4 consists of results, discussion and the importance of novel distraction recognition algorithm. Finally, conclusion, limitations and future work are discussed in chapter 5.
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Date Issued: 2019
Identifier: 2019_Summer_Bhattacharya_fsu_0071E_15258
Format: Thesis

Title: Improved MCVDC Breaker Operation by Existing Power Converters in Shipboard Applications.
Creator: Xie, Ren, Li, Hui, Zhang, Jinfeng, Peng, Fang, Zheng, Jianping, Steurer, Michael, Florida State University, FAMU-FSU College of Engiineering, Department of Electrical and...
Show moreXie, Ren, Li, Hui, Zhang, Jinfeng, Peng, Fang, Zheng, Jianping, Steurer, Michael, Florida State University, FAMU-FSU College of Engiineering, Department of Electrical and Computer Engineering
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Abstract/Description: The medium voltage dc (MVDC) power system is gaining increasing attention in applications such as renewable energy and shipboard power systems due to its advantages in reliability, efficiency, power quality and power density. However, the short-circuit fault management in a MVDC system is a key issue because of the lack of natural zero-crossing point and conventional mechanical circuit breaker (CB) design challenge. So solid state CBs (SSCB) or hybrid CBs (HCB) are under development to enable...
Show moreThe medium voltage dc (MVDC) power system is gaining increasing attention in applications such as renewable energy and shipboard power systems due to its advantages in reliability, efficiency, power quality and power density. However, the short-circuit fault management in a MVDC system is a key issue because of the lack of natural zero-crossing point and conventional mechanical circuit breaker (CB) design challenge. So solid state CBs (SSCB) or hybrid CBs (HCB) are under development to enable the breaker-based fault protection approach. Another breaker-less approach utilizing the inherent current-limiting capability of power semiconductor devices is also promising in a MVDC system. The state-of-the-art of the two fault management approaches are reviewed. This thesis is focused on developing a technology originated from the breaker-less method to improve the performance of breaker-based fault protection approach. In the shipboard breaker-based MVDC system, converters are normally shut down to react to the fault. The diodes freewheeling phenomenon is a concern but a quantitative analysis is still not available. Moreover, the potential of converter during fault has not been exploited completely. Considering large number of converters already existing in the shipboard MVDC system, the overall benefits at no extra hardware cost may be significant. Therefore, a converter fault ride through (FRT) strategy aiming at improving CB operation is proposed in this thesis. The proposed research found that there are some converters located in parallel with activated CBs during the fault and thus, active fault current sharing (FCS) by these converters are possible. In addition, this peak fault current reduction effect on CBs can be amplified from the systematic perspective because multiple CBs in various fault scenarios can be benefited from a single converter. As a first step, the short-circuit fault scenarios of a shipboard breaker-based MVDC system are analyzed comprehensively and fault equivalent circuits including power converters adjacent to CBs are developed. The equivalent circuits are analyzed mathematically and the reaction of passive mode converters to the fault are discussed, which can be a benchmark to evaluate the proposed active FCS strategy. Next, the proposed converter FCS strategy to reduce the CB fault current is illustrated in detail, together with the device stress analysis. Finally, the experimental verifications on a down-scaled test setup are provided.
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Date Issued: 2019
Identifier: 2019_Summer_Xie_fsu_0071E_15185
Format: Thesis

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