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- Creators: Arizona State University
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Description
Infants born before 37 weeks of pregnancy are considered to be preterm. Typically, preterm infants have to be strictly monitored since they are highly susceptible to health problems like hypoxemia (low blood oxygen level), apnea, respiratory issues, cardiac problems, neurological problems as well as an increased chance of long-term health issues such as cerebral palsy, asthma and sudden infant death syndrome. One of the leading health complications in preterm infants is bradycardia - which is defined as the slower than expected heart rate, generally beating lower than 60 beats per minute. Bradycardia is often accompanied by low oxygen levels and can cause additional long term health problems in the premature infant.The implementation of a non-parametric method to predict the onset of brady- cardia is presented. This method assumes no prior knowledge of the data and uses kernel density estimation to predict the future onset of bradycardia events. The data is preprocessed, and then analyzed to detect the peaks in the ECG signals, following which different kernels are implemented to estimate the shared underlying distribu- tion of the data. The performance of the algorithm is evaluated using various metrics and the computational challenges and methods to overcome them are also discussed.
It is observed that the performance of the algorithm with regards to the kernels used are consistent with the theoretical performance of the kernel as presented in a previous work. The theoretical approach has also been automated in this work and the various implementation challenges have been addressed.
It is observed that the performance of the algorithm with regards to the kernels used are consistent with the theoretical performance of the kernel as presented in a previous work. The theoretical approach has also been automated in this work and the various implementation challenges have been addressed.
ContributorsMitra, Sinjini (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Moraffah, Bahman (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2020
Description
The quest to find efficient algorithms to numerically solve differential equations isubiquitous in all branches of computational science. A natural approach to address
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
this problem is to try all possible algorithms to solve the differential equation and
choose the one that is satisfactory to one's needs. However, the vast variety of algorithms
in place makes this an extremely time consuming task. Additionally, even
after choosing the algorithm to be used, the style of programming is not guaranteed
to result in the most efficient algorithm. This thesis attempts to address the same
problem but pertinent to the field of computational nanoelectronics, by using PETSc
linear solver and SLEPc eigenvalue solver packages to efficiently solve Schrödinger
and Poisson equations self-consistently.
In this work, quasi 1D nanowire fabricated in the GaN material system is considered
as a prototypical example. Special attention is placed on the proper description
of the heterostructure device, the polarization charges and accurate treatment of the
free surfaces. Simulation results are presented for the conduction band profiles, the
electron density and the energy eigenvalues/eigenvectors of the occupied sub-bands
for this quasi 1D nanowire. The simulation results suggest that the solver is very
efficient and can be successfully used for the analysis of any device with two dimensional
confinement. The tool is ported on www.nanoHUB.org and as such is freely
available.
ContributorsBaikadi, Pranay Kumar Reddy (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Povolotskyi, Mykhailo (Committee member) / Arizona State University (Publisher)
Created2020
Description
Power management circuits have been more and more widely used in various applications, while providing fully integrated voltage regulation remains a challenging topic. Switched-capacitor (SC) voltage converters have received attentions in integrated power conversion for fixed-ratio voltage conversions with good efficiency and feasibility of integration. During my PhD study, an on-chip current sensing technique is proposed to dynamically modulate both switching frequency and switch widths of SC voltage converters, enhancing fast transient response and higher efficiency across a wide range of load currents. In conjunction with SC converters, a low-dropout regulator (LDO) is implemented which is driven by a push-pull operational transconductance amplifier (OTA), whose current is mirrored and sensed with minimal power and efficiency overhead. The sensed load current directly controls the frequency and width of SC converters through a voltage-controlled oscillator (VCO) and a time-to-digital converter, respectively.
Theoretical analysis and optimization for SC DC-DC converters have been presented in prior works, however optimization of different capacitors, namely flying and input/output decoupling capacitors, in SC voltage regulators (SCVRs) under an area constraint has not been addressed. A methodology to optimize flying and decoupling capacitance for area-constrained on-chip SCVRs to achieve the highest system-level power efficiency. Considering both conversion efficiency and droop voltage against fast load transients, the proposed model determines the optimal ratio between flying and decoupling.
Based on the previous design, a fully integrated switched-capacitor voltage regulator with voltage comparison and on-chip lossless current sensing control is proposed. Based on the voltage comparison result and sensed current as the load current changes, the frequency of the SC converters are modulated for optimal efficiency. The voltage regulator targets 2.1V input voltage and 0.9V output voltage, which offers higher-voltage power transfer across chip package. A 17-phase interleaved structure is used to reduce output voltage ripple.
In 65nm CMOS, the regulator is implemented with MIM-capacitor, targeting 2.1V input voltage and 0.9V output voltage. According to the measurement results, the proposed SC voltage regulator achieves 69.6% peak efficiency at 60mA load current, which corresponds to a 4.2mW/mm2 power-area density and 12.5mW
F power-capacitance density. The efficiency across 20mA to 92mA regulator load current range is above 62%. The steady-state output voltage ripple across 22x load current range of 3.5mA-76mA is between 50mV to 60mV.
Theoretical analysis and optimization for SC DC-DC converters have been presented in prior works, however optimization of different capacitors, namely flying and input/output decoupling capacitors, in SC voltage regulators (SCVRs) under an area constraint has not been addressed. A methodology to optimize flying and decoupling capacitance for area-constrained on-chip SCVRs to achieve the highest system-level power efficiency. Considering both conversion efficiency and droop voltage against fast load transients, the proposed model determines the optimal ratio between flying and decoupling.
Based on the previous design, a fully integrated switched-capacitor voltage regulator with voltage comparison and on-chip lossless current sensing control is proposed. Based on the voltage comparison result and sensed current as the load current changes, the frequency of the SC converters are modulated for optimal efficiency. The voltage regulator targets 2.1V input voltage and 0.9V output voltage, which offers higher-voltage power transfer across chip package. A 17-phase interleaved structure is used to reduce output voltage ripple.
In 65nm CMOS, the regulator is implemented with MIM-capacitor, targeting 2.1V input voltage and 0.9V output voltage. According to the measurement results, the proposed SC voltage regulator achieves 69.6% peak efficiency at 60mA load current, which corresponds to a 4.2mW/mm2 power-area density and 12.5mW
F power-capacitance density. The efficiency across 20mA to 92mA regulator load current range is above 62%. The steady-state output voltage ripple across 22x load current range of 3.5mA-76mA is between 50mV to 60mV.
ContributorsMi, Xiaoyang (Author) / Seo, Jae-Sun (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ogras, Umit Y. (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2020
Description
Lattice-based Cryptography is an up and coming field of cryptography that utilizes the difficulty of lattice problems to design lattice-based cryptosystems that are resistant to quantum attacks and applicable to Fully Homomorphic Encryption schemes (FHE). In this thesis, the parallelization of the Residue Number System (RNS) and algorithmic efficiency of the Number Theoretic Transform (NTT) are combined to tackle the most significant bottleneck of polynomial ring multiplication with the hardware design of an optimized RNS-based NTT polynomial multiplier. The design utilizes Negative Wrapped Convolution, the NTT, RNS Montgomery reduction with Bajard and Shenoy extensions, and optimized modular 32-bit channel arithmetic for nine RNS channels to accomplish an RNS polynomial multiplication. In addition to a full software implementation of the whole system, a pipelined and optimized RNS-based NTT unit with 4 RNS butterflies is implemented on the Xilinx Artix-7 FPGA(xc7a200tlffg1156-2L) for size and delay estimates. The hardware implementation achieves an operating frequency of 47.043 MHz and utilizes 13239 LUT's, 4010 FF's, and 330 DSP blocks, allowing for multiple simultaneously operating NTT units depending on FGPA size constraints.
ContributorsBrist, Logan Alan (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2020
Description
Lateral programmable metallization cells (PMC) utilize the properties of electrodeposits grown over a solid electrolyte channel. Such devices have an active anode and an inert cathode separated by a long electrodeposit channel in a coplanar arrangement. The ability to transport large amount of metallic mass across the channel makes these devices attractive for various More-Than-Moore applications. Existing literature lacks a comprehensive study of electrodeposit growth kinetics in lateral PMCs. Moreover, the morphology of electrodeposit growth in larger, planar devices is also not understood. Despite the variety of applications, lateral PMCs are not embraced by the semiconductor industry due to incompatible materials and high operating voltages needed for such devices. In this work, a numerical model based on the basic processes in PMCs – cation drift and redox reactions – is proposed, and the effect of various materials parameters on the electrodeposit growth kinetics is reported. The morphology of the electrodeposit growth and kinetics of the electrodeposition process are also studied in devices based on Ag-Ge30Se70 materials system. It was observed that the electrodeposition process mainly consists of two regimes of growth – cation drift limited regime and mixed regime. The electrodeposition starts in cation drift limited regime at low electric fields and transitions into mixed regime as the field increases. The onset of mixed regime can be controlled by applied voltage which also affects the morphology of electrodeposit growth. The numerical model was then used to successfully predict the device kinetics and onset of mixed regime. The problem of materials incompatibility with semiconductor manufacturing was solved by proposing a novel device structure. A bilayer structure using semiconductor foundry friendly materials was suggested as a candidate for solid electrolyte. The bilayer structure consists of a low resistivity oxide shunt layer on top of a high resistivity ion carrying oxide layer. Devices using Cu2O as the low resistivity shunt on top of Cu doped WO3 oxide were fabricated. The bilayer devices provided orders of magnitude improvement in device performance in the context of operating voltage and switching time. Electrical and materials characterization revealed the structure of bilayers and the mechanism of electrodeposition in these devices.
ContributorsChamele, Ninad (Author) / Kozicki, Michael (Thesis advisor) / Barnaby, Hugh (Committee member) / Newman, Nathan (Committee member) / Gonzalez-Velo, Yago (Committee member) / Arizona State University (Publisher)
Created2020
Description
The primary goal of this thesis is to evaluate the influence of ethyl vinyl acetate (EVA) and polyolefin elastomer (POE) encapsulant types on the glass-glass (GG) photovoltaic (PV) module reliability. The influence of these two encapsulant types on the reliability of GG modules was compared with baseline glass-polymer backsheet (GB) modules for a benchmarking purpose. Three sets of modules, with four modules in each set, were constructed with two substrates types i.e. glass-glass (GG) and glass- polymer backsheet (GB); and 2 encapsulants types i.e. ethyl vinyl acetate (EVA) and polyolefin elastomer (POE). Each module set was subjected to the following accelerated tests as specified in the International Electrotechnical Commission (IEC) standard and Qualification Plus protocol of NREL: Ultraviolet (UV) 250 kWh/m2; Thermal Cycling (TC) 200 cycles; Damp Heat (DH) 1250 hours. To identify the failure modes and reliability issues of the stressed modules, several module-level non-destructive characterizations were carried out and they include colorimetry, UV-Vis-NIR spectral reflectance, ultraviolet fluorescence (UVF) imaging, electroluminescence (EL) imaging, and infrared (IR) imaging. The above-mentioned characterizations were performed on the front side of the modules both before the stress tests (i.e. pre-stress) and after the stress tests (i.e. post-stress). The UV-250 extended stress results indicated slight changes in the reflectance on the non-cell area of EVA modules probably due to minor adhesion loss at the cell and module edges. From the DH-1250 extended stress tests, significant changes, in both encapsulant types modules, were observed in reflectance and UVF images indicating early stages of delamination. In the case of the TC-200 stress test, practically no changes were observed in all sets of modules. From the above short-term stress tests, it appears although not conclusive at this stage of the analysis, delamination seems to be the only failure mode that could possibly be affecting the module performance, as observed from UV and DH extended stress tests. All these stress tests need to be continued to identify the wear-out failure modes and their impacts on the performance parameters of PV modules.
ContributorsBhaskaran, Rahul (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2020
Description
The origins of carrier mobility (μe) were thoroughly investigated in hydrogenated indium oxide (IO:H) and zinc-tin oxide (ZTO) transparent conducting oxide (TCO) thin films. A carrier transport model was developed for IO:H which studied the effects of ionized impurity scattering, polar optical phonon scattering, and grain boundary scattering. Ionized impurity scattering dominated at temperatures below ~240 K. A reduction in scattering charge Z from +2 to +1 as atomic %H increased from ~3 atomic %H to ~5 atomic %H allowed μe to attain >100 cm^2/Vs at ~5 atomic %H.
In highly hydrogenated IO:H, ne significantly decreased as temperature increased from 5 K to 140 K. To probe this unusual behavior, samples were illuminated, then ne, surface work function (WF), and spatially resolved microscopic current mapping were measured and tracked. Large increases in ne and corresponding decreases in WF were observed---these both exhibited slow reversions toward pre-illumination values over 6-12 days. A hydrogen-related defect was proposed as source of the photoexcitation, while a lattice defect diffusion mechanism causes the extended decay. Both arise from an under-coordination of the In.
An enhancement of μe was observed with increasing amorphous fraction in IO:H. An increase in population of corner- and edge-sharing polyhedra consisting of metal cations and oxygen anions is thought to be the origin. This indicates some measure of medium-range order in the amorphous structure, and gives rise to a general principle dictating μe in TCOs---even amorphous TCOs. Testing this principle resulted in observing an enhancement of μe up to 35 cm^2/Vs in amorphous ZTO (a-ZTO), one of the highest reported a-ZTO μe values (at ne > 10^19 cm^-3) to date. These results highlight the role of local distortions and cation coordination in determining the microscopic origins of carrier generation and transport. In addition, the strong likelihood of under-coordination of one cation species leading to high carrier concentrations is proposed. This diverges from the historical indictment of oxygen vacancies controlling carrier population in crystalline oxides, which by definition cannot occur in amorphous systems, and provides a framework to discuss key structural descriptors in these disordered phase materials.
In highly hydrogenated IO:H, ne significantly decreased as temperature increased from 5 K to 140 K. To probe this unusual behavior, samples were illuminated, then ne, surface work function (WF), and spatially resolved microscopic current mapping were measured and tracked. Large increases in ne and corresponding decreases in WF were observed---these both exhibited slow reversions toward pre-illumination values over 6-12 days. A hydrogen-related defect was proposed as source of the photoexcitation, while a lattice defect diffusion mechanism causes the extended decay. Both arise from an under-coordination of the In.
An enhancement of μe was observed with increasing amorphous fraction in IO:H. An increase in population of corner- and edge-sharing polyhedra consisting of metal cations and oxygen anions is thought to be the origin. This indicates some measure of medium-range order in the amorphous structure, and gives rise to a general principle dictating μe in TCOs---even amorphous TCOs. Testing this principle resulted in observing an enhancement of μe up to 35 cm^2/Vs in amorphous ZTO (a-ZTO), one of the highest reported a-ZTO μe values (at ne > 10^19 cm^-3) to date. These results highlight the role of local distortions and cation coordination in determining the microscopic origins of carrier generation and transport. In addition, the strong likelihood of under-coordination of one cation species leading to high carrier concentrations is proposed. This diverges from the historical indictment of oxygen vacancies controlling carrier population in crystalline oxides, which by definition cannot occur in amorphous systems, and provides a framework to discuss key structural descriptors in these disordered phase materials.
ContributorsHusein, Sebastian S.T. (Author) / Bertoni, Mariana I. (Thesis advisor) / Stuckelberger, Michael (Committee member) / Holman, Zachary C. (Committee member) / Crozier, Peter (Committee member) / Arizona State University (Publisher)
Created2020
Description
In the current photovoltaic (PV) industry, the O&M (operations and maintenance) personnel in the field primarily utilize three approaches to identify the underperforming or defective modules in a string: i) EL (electroluminescence) imaging of all the modules in the string; ii) IR (infrared) thermal imaging of all the modules in the string; and, iii) current-voltage (I-V) curve tracing of all the modules in the string. In the first and second approaches, the EL images are used to detect the modules with broken cells, and the IR images are used to detect the modules with hotspot cells, respectively. These two methods may identify the modules with defective cells only semi-qualitatively, but not accurately and quantitatively. The third method, I-V curve tracing, is a quantitative method to identify the underperforming modules in a string, but it is an extremely time consuming, labor-intensive, and highly ambient conditions dependent method. Since the I-V curves of individual modules in a string are obtained by disconnecting them individually at different irradiance levels, module operating temperatures, angle of incidences (AOI) and air-masses/spectra, all these measured curves are required to be translated to a single reporting condition (SRC) of a single irradiance, single temperature, single AOI and single spectrum. These translations are not only time consuming but are also prone to inaccuracy due to inherent issues in the translation models. Therefore, the current challenges in using the traditional I-V tracers are related to: i) obtaining I-V curves simultaneously of all the modules and substrings in a string at a single irradiance, operating temperature, irradiance spectrum and angle of incidence due to changing weather parameters and sun positions during the measurements, ii) safety of field personnel when disconnecting and reconnecting of cables in high voltage systems (especially field aged connectors), and iii) enormous time and hardship for the test personnel in harsh outdoor climatic conditions. In this thesis work, a non-contact I-V (NCIV) curve tracing tool has been integrated and implemented to address the above mentioned three challenges of the traditional I-V tracers.
This work compares I-V curves obtained using a traditional I-V curve tracer with the I-V curves obtained using a NCIV curve tracer for the string, substring and individual modules of crystalline silicon (c-Si) and cadmium telluride (CdTe) technologies. The NCIV curve tracer equipment used in this study was integrated using three commercially available components: non-contact voltmeters (NCV) with voltage probes to measure the voltages of substrings/modules in a string, a hall sensor to measure the string current and a DAS (data acquisition system) for simultaneous collection of the voltage data obtained from the NCVs and the current data obtained from the hall sensor. This study demonstrates the concept and accuracy of the NCIV curve tracer by comparing the I-V curves obtained using a traditional capacitor-based tracer and the NCIV curve tracer in a three-module string of c-Si modules and of CdTe modules under natural sunlight with uniform light conditions on all the modules in the string and with partially shading one or more of the modules in the string to simulate and quantitatively detect the underperforming module(s) in a string.
This work compares I-V curves obtained using a traditional I-V curve tracer with the I-V curves obtained using a NCIV curve tracer for the string, substring and individual modules of crystalline silicon (c-Si) and cadmium telluride (CdTe) technologies. The NCIV curve tracer equipment used in this study was integrated using three commercially available components: non-contact voltmeters (NCV) with voltage probes to measure the voltages of substrings/modules in a string, a hall sensor to measure the string current and a DAS (data acquisition system) for simultaneous collection of the voltage data obtained from the NCVs and the current data obtained from the hall sensor. This study demonstrates the concept and accuracy of the NCIV curve tracer by comparing the I-V curves obtained using a traditional capacitor-based tracer and the NCIV curve tracer in a three-module string of c-Si modules and of CdTe modules under natural sunlight with uniform light conditions on all the modules in the string and with partially shading one or more of the modules in the string to simulate and quantitatively detect the underperforming module(s) in a string.
ContributorsMurali, Sanjay (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
Description
In many biological research studies, including speech analysis, clinical research, and prediction studies, the validity of the study is dependent on the effectiveness of the training data set to represent the target population. For example, in speech analysis, if one is performing emotion classification based on speech, the performance of the classifier is mainly dependent on the number and quality of the training data set. For small sample sizes and unbalanced data, classifiers developed in this context may be focusing on the differences in the training data set rather than emotion (e.g., focusing on gender, age, and dialect).
This thesis evaluates several sampling methods and a non-parametric approach to sample sizes required to minimize the effect of these nuisance variables on classification performance. This work specifically focused on speech analysis applications, and hence the work was done with speech features like Mel-Frequency Cepstral Coefficients (MFCC) and Filter Bank Cepstral Coefficients (FBCC). The non-parametric divergence (D_p divergence) measure was used to study the difference between different sampling schemes (Stratified and Multistage sampling) and the changes due to the sentence types in the sampling set for the process.
This thesis evaluates several sampling methods and a non-parametric approach to sample sizes required to minimize the effect of these nuisance variables on classification performance. This work specifically focused on speech analysis applications, and hence the work was done with speech features like Mel-Frequency Cepstral Coefficients (MFCC) and Filter Bank Cepstral Coefficients (FBCC). The non-parametric divergence (D_p divergence) measure was used to study the difference between different sampling schemes (Stratified and Multistage sampling) and the changes due to the sentence types in the sampling set for the process.
ContributorsMariajohn, Aaquila (Author) / Berisha, Visar (Thesis advisor) / Spanias, Andreas (Committee member) / Liss, Julie (Committee member) / Arizona State University (Publisher)
Created2020
Description
The electric power system (EPS) is an extremely complex system that has operational interdependencies with the water delivery and treatment system (WDTS). The term water-energy nexus is commonly used to describe the critical interdependencies that naturally exist between the EPS and water distribution systems (WDS). Presented in this work is a framework for simulating interactions between these two critical infrastructure systems in short-term and long-term time-scales. This includes appropriate mathematical models for system modeling and for optimizing control of power system operation with consideration of conditions in the WDS. Also presented is a complete methodology for quantifying the resilience of the two interdependent systems.
The key interdependencies between the two systems are the requirements of water for the cooling cycle of traditional thermal power plants as well as electricity for pumping and/or treatment in the WDS. While previous work has considered the dependency of thermoelectric generation on cooling water requirements at a high-level, this work considers the impact from limitations of cooling water into network simulations in both a short-term operational framework as well as in the long-term planning domain.
The work completed to set-up simulations in operational length time-scales was the development of a simulator that adequately models both systems. This simulation engine also facilitates the implementation of control schemes in both systems that take advantage of the knowledge of operating conditions in the other system. Initial steps for including the influence of anticipated water availability and water rights attainability within the combined generation and transmission expansion planning problem is also presented. Lastly, the framework for determining the infrastructural-operational resilience (IOR) of the interdependent systems is formulated.
Adequately modeling and studying the two systems and their interactions is becoming critically important. This importance is illustrated by the possibility of unforeseen natural or man-made events or by the likelihood of load increase in the systems, either of which has the risk of putting extreme stress on the systems beyond that experienced in normal operating conditions. Therefore, this work addresses these concerns with novel modeling and control/policy strategies designed to mitigate the severity of extreme conditions in either system.
The key interdependencies between the two systems are the requirements of water for the cooling cycle of traditional thermal power plants as well as electricity for pumping and/or treatment in the WDS. While previous work has considered the dependency of thermoelectric generation on cooling water requirements at a high-level, this work considers the impact from limitations of cooling water into network simulations in both a short-term operational framework as well as in the long-term planning domain.
The work completed to set-up simulations in operational length time-scales was the development of a simulator that adequately models both systems. This simulation engine also facilitates the implementation of control schemes in both systems that take advantage of the knowledge of operating conditions in the other system. Initial steps for including the influence of anticipated water availability and water rights attainability within the combined generation and transmission expansion planning problem is also presented. Lastly, the framework for determining the infrastructural-operational resilience (IOR) of the interdependent systems is formulated.
Adequately modeling and studying the two systems and their interactions is becoming critically important. This importance is illustrated by the possibility of unforeseen natural or man-made events or by the likelihood of load increase in the systems, either of which has the risk of putting extreme stress on the systems beyond that experienced in normal operating conditions. Therefore, this work addresses these concerns with novel modeling and control/policy strategies designed to mitigate the severity of extreme conditions in either system.
ContributorsZuloaga, Scott (Author) / Vittal, Vijay (Thesis advisor) / Zhang, Junshan (Committee member) / Mays, Larry (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2020