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How Does Technology Development Influence the Assessment of Parkinson’s Disease? A Systematic Review
Description
Parkinson’s disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The pathology for PD is difficult and expensive. Furthermore, it depends on patient diaries and the neurologist’s subjective assessment of clinical scales. Objective, accurate, and continuous patient monitoring have become possible with the advancement in mobile and portable equipment. Consequently, a significant amount of work has been done to explore new cost-effective and subjective assessment methods or PD symptoms. For example, smart technologies, such as wearable sensors and optical motion capturing systems, have been used to analyze the symptoms of a PD patient to assess their disease progression and even to detect signs in their nascent stage for early diagnosis of PD.
This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review.
This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review.
ContributorsDeb, Ranadeep (Author) / Ogras, Umit Y. (Thesis advisor) / Shill, Holly (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2019
Description
The following report details the motivation, design, analysis, simulation and hardware implementation of a DC/DC converter in EV drivetrain architectures. The primary objective of the project was to improve overall system efficiency in an EV drivetrain. The methodology employed to this end required a variable or flexible DC-Link voltage at the input of the inverter stage. Amongst the several advantages associated with such a system are the independent optimization of the battery stack and the inverter over a wide range of motor operating conditions. The incorporation of a DC/DC converter into the drivetrain helps lower system losses but since it is an additional component, a number of considerations need to be made during its design. These include stringent requirements on power density, converter efficiency and reliability.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
ContributorsRaza, Bassam (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Large-scale blackouts that have occurred across North America in the past few decades have paved the path for substantial amount of research in the field of security assessment of the grid. With the aid of advanced technology such as phasor measurement units (PMUs), considerable work has been done involving voltage stability analysis and power system dynamic behavior analysis to ensure security and reliability of the grid. Online dynamic security assessment (DSA) analysis has been developed and applied in several power system control centers. Existing applications of DSA are limited by the assumption of simplistic load profiles, which often considers a normative day to represent an entire year. To overcome these aforementioned challenges, this research developed a novel DSA scheme to provide security prediction in real-time for load profiles corresponding to different seasons. The major contributions of this research are to (1) develop a DSA scheme incorporated with PMU data, (2) consider a comprehensive seasonal load profile, (3) account for varying penetrations of renewable generation, and (4) compare the accuracy of different machine learning (ML) algorithms for DSA. The ML algorithms that will be the focus of this study include decision trees (DTs), support vector machines (SVMs), random forests (RFs), and multilayer neural networks (MLNNs).
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
This thesis describes the development of a novel DSA scheme using synchrophasor measurements that accounts for the load variability occurring across different seasons in a year. Different amounts of solar generation have also been incorporated in this study to account for increasing percentage of renewables in the modern grid. To account for the security of the operating conditions different ML algorithms have been trained and tested. A database of cases for different operating conditions has been developed offline that contains secure as well as insecure cases, and the ML models have been trained to classify the security or insecurity of a particular operating condition in real-time. Multiple scenarios are generated every 15 minutes for different seasons and stored in the database. The performance of this approach is tested on the IEEE-118 bus system.
ContributorsNATH, ANUBHAV (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2019
Description
The universe since its formation 13.7 billion years ago has undergone many changes. It began with expanding and cooling down to a temperature low enough for formation of atoms of neutral Hydrogen and Helium gas. Stronger gravitational pull in certain regions caused some regions to be denser and hotter than others. These regions kept getting denser and hotter until they had centers hot enough to burn the hydrogen and form the first stars, which ended the Dark Ages. These stars did not live long and underwent violent explosions. These explosions and the photons from the stars caused the hydrogen gas around them to ionize. This went on until all the hydrogen gas in the universe was ionized. This period is known as Epoch Of Reionization. Studying the Epoch Of Reionization will help understand the formation of these early stars, the timeline of the reionization and the formation of the stars and galaxies as we know them today. Studying the radiations from the 21cm line in neutral hydrogen, redshifted to below 200MHz can help determine details such as velocity, density and temperature of these early stars and the media around them.
The EDGES program is one of the many programs that aim to study the Epoch of Reionization. It is a ground-based project deployed in Murchison Radio-Astronomy Observatory in Western Australia. At ground level the Radio Frequency Interference from the ionosphere and various man-made transmitters in the same frequency range as the EDGES receiver make measurements, receiver design and extraction of useful data from received signals difficult. Putting the receiver in space can help majorly escape the RFI. The EDGES In Space is a proposed project that aims at designing a receiver similar to the EDGES receiver but for a cubesat.
This thesis aims at designing a prototype receiver that is similar in architecture to the EDGES low band receiver (50-100MHz) but is significantly smaller in size (small enough to fit on a PCB for a cubesat) while keeping in mind different considerations that affect circuit performance in space.
The EDGES program is one of the many programs that aim to study the Epoch of Reionization. It is a ground-based project deployed in Murchison Radio-Astronomy Observatory in Western Australia. At ground level the Radio Frequency Interference from the ionosphere and various man-made transmitters in the same frequency range as the EDGES receiver make measurements, receiver design and extraction of useful data from received signals difficult. Putting the receiver in space can help majorly escape the RFI. The EDGES In Space is a proposed project that aims at designing a receiver similar to the EDGES receiver but for a cubesat.
This thesis aims at designing a prototype receiver that is similar in architecture to the EDGES low band receiver (50-100MHz) but is significantly smaller in size (small enough to fit on a PCB for a cubesat) while keeping in mind different considerations that affect circuit performance in space.
ContributorsJambagi, Ashwini (Author) / Mauskopf, Philip (Thesis advisor) / Aberle, James T., 1961- (Thesis advisor) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2019
Description
Gallium Nitride (GaN) based Current Aperture Vertical Electron Transistors (CAVETs) present many appealing qualities for applications in high power, high frequency devices. The wide bandgap, high carrier velocity of GaN make it ideal for withstanding high electric fields and supporting large currents. The vertical topology of the CAVET allows for more efficient die area utilization, breakdown scaling with the height of the device, and burying high electric fields in the bulk where they will not charge interface states that can lead to current collapse at higher frequency.
Though GaN CAVETs are promising new devices, they are expensive to develop due to new or exotic materials and processing steps. As a result, the accurate simulation of GaN CAVETs has become critical to the development of new devices. Using Silvaco Atlas 5.24.1.R, best practices were developed for GaN CAVET simulation by recreating the structure and results of the pGaN insulated gate CAVET presented in chapter 3 of [8].
From the results it was concluded that the best simulation setup for transfer characteristics, output characteristics, and breakdown included the following. For methods, the use of Gummel, Block, Newton, and Trap. For models, SRH, Fermi, Auger, and impact selb. For mobility, the use of GANSAT and manually specified saturation velocity and mobility (based on doping concentration). Additionally, parametric sweeps showed that, of those tested, critical CAVET parameters included channel mobility (and thus doping), channel thickness, Current Blocking Layer (CBL) doping, gate overlap, and aperture width in rectangular devices or diameter in cylindrical devices.
Though GaN CAVETs are promising new devices, they are expensive to develop due to new or exotic materials and processing steps. As a result, the accurate simulation of GaN CAVETs has become critical to the development of new devices. Using Silvaco Atlas 5.24.1.R, best practices were developed for GaN CAVET simulation by recreating the structure and results of the pGaN insulated gate CAVET presented in chapter 3 of [8].
From the results it was concluded that the best simulation setup for transfer characteristics, output characteristics, and breakdown included the following. For methods, the use of Gummel, Block, Newton, and Trap. For models, SRH, Fermi, Auger, and impact selb. For mobility, the use of GANSAT and manually specified saturation velocity and mobility (based on doping concentration). Additionally, parametric sweeps showed that, of those tested, critical CAVET parameters included channel mobility (and thus doping), channel thickness, Current Blocking Layer (CBL) doping, gate overlap, and aperture width in rectangular devices or diameter in cylindrical devices.
ContributorsWarren, Andrew (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2019
Description
Non-line-of-sight (NLOS) imaging of objects not visible to either the camera or illumina-
tion source is a challenging task with vital applications including surveillance and robotics.
Recent NLOS reconstruction advances have been achieved using time-resolved measure-
ments. Acquiring these time-resolved measurements requires expensive and specialized
detectors and laser sources. In work proposes a data-driven approach for NLOS 3D local-
ization requiring only a conventional camera and projector. The localisation is performed
using a voxelisation and a regression problem. Accuracy of greater than 90% is achieved
in localizing a NLOS object to a 5cm × 5cm × 5cm volume in real data. By adopting
the regression approach an object of width 10cm to localised to approximately 1.5cm. To
generalize to line-of-sight (LOS) scenes with non-planar surfaces, an adaptive lighting al-
gorithm is adopted. This algorithm, based on radiosity, identifies and illuminates scene
patches in the LOS which most contribute to the NLOS light paths, and can factor in sys-
tem power constraints. Improvements ranging from 6%-15% in accuracy with a non-planar
LOS wall using adaptive lighting is reported, demonstrating the advantage of combining
the physics of light transport with active illumination for data-driven NLOS imaging.
tion source is a challenging task with vital applications including surveillance and robotics.
Recent NLOS reconstruction advances have been achieved using time-resolved measure-
ments. Acquiring these time-resolved measurements requires expensive and specialized
detectors and laser sources. In work proposes a data-driven approach for NLOS 3D local-
ization requiring only a conventional camera and projector. The localisation is performed
using a voxelisation and a regression problem. Accuracy of greater than 90% is achieved
in localizing a NLOS object to a 5cm × 5cm × 5cm volume in real data. By adopting
the regression approach an object of width 10cm to localised to approximately 1.5cm. To
generalize to line-of-sight (LOS) scenes with non-planar surfaces, an adaptive lighting al-
gorithm is adopted. This algorithm, based on radiosity, identifies and illuminates scene
patches in the LOS which most contribute to the NLOS light paths, and can factor in sys-
tem power constraints. Improvements ranging from 6%-15% in accuracy with a non-planar
LOS wall using adaptive lighting is reported, demonstrating the advantage of combining
the physics of light transport with active illumination for data-driven NLOS imaging.
ContributorsChandran, Sreenithy (Author) / Jayasuriya, Suren (Thesis advisor) / Turaga, Pavan (Committee member) / Dasarathy, Gautam (Committee member) / Arizona State University (Publisher)
Created2019
Description
Space exploration is a large field that requires high performing circuitry due to the harsh environment. Within a space environment one of the biggest factors leading to circuit failure is radiation. Circuits must be robust enough to continue operation after being exposed to the high doses of radiation. Bandgap reference (BGR) circuits are designed to be voltage references that stay stable across a wide range of supply voltages and temperatures. A bandgap reference is a piece of a large circuit that supplies critical elements of the large circuit with a constant voltage. When used in a space environment with large amounts of radiation a BGR needs to maintain its output voltage to enable the rest of the circuit to operate under proper conditions. Since a BGR is not a standalone circuit it is difficult and expensive to test if a BGR is maintaining its reference voltage.
This thesis describes a methodology of isolating and simulating bandgap references. Both NPN and PNP bandgap references are simulated over a variety of radiation doses and dose rates. This methodology will allow the degradation due to radiation of a BGR to be modeled easily and affordably. It can be observed that many circuits experience enhanced low dose rate sensitivity (ELDRS) which can lead to failure at low total ionizing doses (TID) of radiation. A compact model library demonstrating degradation of transistors at both high and low dose rates (HDR and LDR) will be used to show bandgap references reliability. Specifically, two bandgap references being utilized in commercial off the shelf low dropout regulators (LDO) will be evaluated. The LDOs are reverse engineered in a simulation program with integrated circuit emphasis (SPICE). Within the two LDOs the bandgaps will be the points of interest. Of the LDOs one has a positive regulated voltage and one has a negative regulated voltage. This requires an NPN and a PNP based BGR respectively. This simulation methodology will draw conclusions about the above bandgap references, and how they operate under radiation at different doses and dose rates.
This thesis describes a methodology of isolating and simulating bandgap references. Both NPN and PNP bandgap references are simulated over a variety of radiation doses and dose rates. This methodology will allow the degradation due to radiation of a BGR to be modeled easily and affordably. It can be observed that many circuits experience enhanced low dose rate sensitivity (ELDRS) which can lead to failure at low total ionizing doses (TID) of radiation. A compact model library demonstrating degradation of transistors at both high and low dose rates (HDR and LDR) will be used to show bandgap references reliability. Specifically, two bandgap references being utilized in commercial off the shelf low dropout regulators (LDO) will be evaluated. The LDOs are reverse engineered in a simulation program with integrated circuit emphasis (SPICE). Within the two LDOs the bandgaps will be the points of interest. Of the LDOs one has a positive regulated voltage and one has a negative regulated voltage. This requires an NPN and a PNP based BGR respectively. This simulation methodology will draw conclusions about the above bandgap references, and how they operate under radiation at different doses and dose rates.
ContributorsDavis, Parker William (Author) / Barnaby, Hugh (Thesis advisor) / Kitchen, Jennifer (Committee member) / Privat, Aymeric (Committee member) / Arizona State University (Publisher)
Created2019
Description
The detection and segmentation of objects appearing in a natural scene, often referred to as Object Detection, has gained a lot of interest in the computer vision field. Although most existing object detectors aim to detect all the objects in a given scene, it is important to evaluate whether these methods are capable of detecting the salient objects in the scene when constraining the number of proposals that can be generated due to constraints on timing or computations during execution. Salient objects are objects that tend to be more fixated by human subjects. The detection of salient objects is important in applications such as image collection browsing, image display on small devices, and perceptual compression.
This thesis proposes a novel evaluation framework that analyses the performance of popular existing object proposal generators in detecting the most salient objects. This work also shows that, by incorporating saliency constraints, the number of generated object proposals and thus the computational cost can be decreased significantly for a target true positive detection rate (TPR).
As part of the proposed framework, salient ground-truth masks are generated from the given original ground-truth masks for a given dataset. Given an object detection dataset, this work constructs salient object location ground-truth data, referred to here as salient ground-truth data for short, that only denotes the locations of salient objects. This is obtained by first computing a saliency map for the input image and then using it to assign a saliency score to each object in the image. Objects whose saliency scores are sufficiently high are referred to as salient objects. The detection rates are analyzed for existing object proposal generators with respect to the original ground-truth masks and the generated salient ground-truth masks.
As part of this work, a salient object detection database with salient ground-truth masks was constructed from the PASCAL VOC 2007 dataset. Not only does this dataset aid in analyzing the performance of existing object detectors for salient object detection, but it also helps in the development of new object detection methods and evaluating their performance in terms of successful detection of salient objects.
This thesis proposes a novel evaluation framework that analyses the performance of popular existing object proposal generators in detecting the most salient objects. This work also shows that, by incorporating saliency constraints, the number of generated object proposals and thus the computational cost can be decreased significantly for a target true positive detection rate (TPR).
As part of the proposed framework, salient ground-truth masks are generated from the given original ground-truth masks for a given dataset. Given an object detection dataset, this work constructs salient object location ground-truth data, referred to here as salient ground-truth data for short, that only denotes the locations of salient objects. This is obtained by first computing a saliency map for the input image and then using it to assign a saliency score to each object in the image. Objects whose saliency scores are sufficiently high are referred to as salient objects. The detection rates are analyzed for existing object proposal generators with respect to the original ground-truth masks and the generated salient ground-truth masks.
As part of this work, a salient object detection database with salient ground-truth masks was constructed from the PASCAL VOC 2007 dataset. Not only does this dataset aid in analyzing the performance of existing object detectors for salient object detection, but it also helps in the development of new object detection methods and evaluating their performance in terms of successful detection of salient objects.
ContributorsKotamraju, Sai Prajwal (Author) / Karam, Lina J (Thesis advisor) / Yu, Hongbin (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2019
Description
High Voltage Direct Current (HVDC) Technology has several features that make it particularly attractive for specific transmission applications. Recent years have witnessed an unprecedented growth in the number of the HVDC projects, which demonstrates a heightened interest in the HVDC technology. In parallel, the use of renewable energy sources has dramatically increased. For instance, Kuwait has recently announced a renewable project to be completed in 2035; this project aims to produce 15% of the countrys energy consumption from renewable sources. However, facilities that use renewable sources, such as solar and wind, to provide clean energy, are mostly placed in remote areas, as their installation requires a massive space of free land. Consequently, considerable challenges arise in terms of transmitting power generated from renewable sources of energy in remote areas to urban areas for further consumption.
The present thesis investigates different transmission line systems for transmitting bulk energy from renewable sources. Specifically, two systems will be focused on: the high-voltage alternating current (HVAC) system and the high-voltage direct current (HVDC) system. In order to determine the most efficient way of transmitting bulk energy from renewable sources, different aspects of the aforementioned two types of systems are analyzed. Limitations inherent in both HVAC and HVDC systems have been discussed.
At present, artificial intelligence plays an important role in power system control and monitoring. Consequently, in this thesis, the fault issue has been analyzed in transmission systems, with a specific consideration of machine learning tools that can help monitor transmission systems by detecting fault locations. These tools, called models, are used to analyze the collected data. In the present thesis, a focus on such models as linear regression (LR), K-nearest neighbors (KNN), linear support vector machine (LSVM) , and adaptive boost (AdaBoost). Finally, the accuracy of each model is evaluated and discussed. The machine learning concept introduced in the present thesis lays down the foundation for future research in this area so that to enable further research on the efficient ways to improve the performance of transmission line components and power systems.
The present thesis investigates different transmission line systems for transmitting bulk energy from renewable sources. Specifically, two systems will be focused on: the high-voltage alternating current (HVAC) system and the high-voltage direct current (HVDC) system. In order to determine the most efficient way of transmitting bulk energy from renewable sources, different aspects of the aforementioned two types of systems are analyzed. Limitations inherent in both HVAC and HVDC systems have been discussed.
At present, artificial intelligence plays an important role in power system control and monitoring. Consequently, in this thesis, the fault issue has been analyzed in transmission systems, with a specific consideration of machine learning tools that can help monitor transmission systems by detecting fault locations. These tools, called models, are used to analyze the collected data. In the present thesis, a focus on such models as linear regression (LR), K-nearest neighbors (KNN), linear support vector machine (LSVM) , and adaptive boost (AdaBoost). Finally, the accuracy of each model is evaluated and discussed. The machine learning concept introduced in the present thesis lays down the foundation for future research in this area so that to enable further research on the efficient ways to improve the performance of transmission line components and power systems.
ContributorsAlbannai, Bassam Ahmad (Author) / Weng, Yang (Thesis advisor) / Wu, Meng (Committee member) / Dahal, Som (Committee member) / Arizona State University (Publisher)
Created2019
Description
Until late 1970’s the primary focus in power system modeling has been largely directed towards power system generation and transmission. Over the years, the importance of load modeling grew and having an accurate representation of load played an important role in the planning and operation studies. With an emphasis on tackling the topic of load modeling, this thesis presents the following intermediary steps in developing accurate load models:
1. Synthesis of a three-phase standard feeder and load model using the measured voltages and currents, for events such as faults and feeder pickup cases, obtained at the head of the feeder.
2. Investigated the impact of the synthesized standard feeder and load model on the sub-transmission system for a feeder pick-up case.
In the first phase of this project, a standard feeder and load model had been synthesized by capturing the current transients when three-phase voltage measurements (obtained from a local electric utility) are played-in as input to the synthesized model. The comparison between the measured currents and the simulated currents obtained using an electromagnetic transient analysis software (PSCAD) are made at the head of the designed feeder. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor loads and three-phase induction motor loads. The parameters of the motor models are adjusted to obtain a good correspondence between measured three-phase currents and simulated current responses at the head of the feeder when subjected to events under which measurements were obtained on the feeder. These events include faults which occurred upstream of the feeder at a higher voltage level and a feeder pickup event that occurred downstream from the head of the feeder. Two different load compositions have been obtained for this feeder and load model depending on the types of load present in the surrounding area (residential or industrial/commercial).
The second phase of this project examines the impact of the feeder pick-up event on the 69 kV sub-transmission system using the obtained standard feeder and load model. Using the 69 kV network data obtained from a local utility, a sub-transmission network has been built in PSCAD. The main difference between the first and second phase of this project is that no measurements are played-in to the model in the latter case. Instead, the feeder pick-up event at a particular substation is simulated using the reduced equivalent of the 69 kV sub-transmission circuit together with the synthesized three-phase models of the feeder and the loads obtained in the first phase of the project. Using this analysis, it is observed that a good correspondence between the PSCAD simulated values of both three-phase voltages and currents with their corresponding measured responses at the substation is achieved.
1. Synthesis of a three-phase standard feeder and load model using the measured voltages and currents, for events such as faults and feeder pickup cases, obtained at the head of the feeder.
2. Investigated the impact of the synthesized standard feeder and load model on the sub-transmission system for a feeder pick-up case.
In the first phase of this project, a standard feeder and load model had been synthesized by capturing the current transients when three-phase voltage measurements (obtained from a local electric utility) are played-in as input to the synthesized model. The comparison between the measured currents and the simulated currents obtained using an electromagnetic transient analysis software (PSCAD) are made at the head of the designed feeder. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor loads and three-phase induction motor loads. The parameters of the motor models are adjusted to obtain a good correspondence between measured three-phase currents and simulated current responses at the head of the feeder when subjected to events under which measurements were obtained on the feeder. These events include faults which occurred upstream of the feeder at a higher voltage level and a feeder pickup event that occurred downstream from the head of the feeder. Two different load compositions have been obtained for this feeder and load model depending on the types of load present in the surrounding area (residential or industrial/commercial).
The second phase of this project examines the impact of the feeder pick-up event on the 69 kV sub-transmission system using the obtained standard feeder and load model. Using the 69 kV network data obtained from a local utility, a sub-transmission network has been built in PSCAD. The main difference between the first and second phase of this project is that no measurements are played-in to the model in the latter case. Instead, the feeder pick-up event at a particular substation is simulated using the reduced equivalent of the 69 kV sub-transmission circuit together with the synthesized three-phase models of the feeder and the loads obtained in the first phase of the project. Using this analysis, it is observed that a good correspondence between the PSCAD simulated values of both three-phase voltages and currents with their corresponding measured responses at the substation is achieved.
ContributorsNekkalapu, Sameer (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John M (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2018