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Description
Technological advances in low power wearable electronics and energy optimization techniques

make motion energy harvesting a viable energy source. However, it has not been

widely adopted due to bulky energy harvester designs that are uncomfortable to wear. This

work addresses this problem by analyzing the feasibility of powering low wearable power

devices using piezoelectric

Technological advances in low power wearable electronics and energy optimization techniques

make motion energy harvesting a viable energy source. However, it has not been

widely adopted due to bulky energy harvester designs that are uncomfortable to wear. This

work addresses this problem by analyzing the feasibility of powering low wearable power

devices using piezoelectric energy generated at the human knee. We start with a novel

mathematical model for estimating the power generated from human knee joint movements.

This thesis’s major contribution is to analyze the feasibility of human motion energy harvesting

and validating this analytical model using a commercially available piezoelectric

module. To this end, we implemented an experimental setup that replicates a human knee.

Then, we performed experiments at different excitation frequencies and amplitudes with

two commercially available Macro Fiber Composite (MFC) modules. These experimental

results are used to validate the analytical model and predict the energy harvested as a function

of the number of steps taken in a day. The model estimates that 13μWcan be generated

on an average while walking with a 4.8% modeling error. The obtained results show that

piezoelectricity is indeed a viable approach for powering low-power wearable devices.
ContributorsBandyopadhyay, Shiva (Author) / Ogras, Umit Y. (Thesis advisor) / Fan, Deliang (Committee member) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2020
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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

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.
ContributorsMurali, Sanjay (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
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Description
The presence of huge amounts of waste heat and the constant demand for electric energy makes this an appreciable research topic, yet at present there is no commercially viable technology to harness the inherent energy resource provided by the temperature differential between the inside and outside of buildings. In a

The presence of huge amounts of waste heat and the constant demand for electric energy makes this an appreciable research topic, yet at present there is no commercially viable technology to harness the inherent energy resource provided by the temperature differential between the inside and outside of buildings. In a newly developed technology, electricity is generated from the temperature gradient between building walls through a Seebeck effect. A 3D-printed triply periodic minimal surface (TPMS) structure is sandwiched in copper electrodes with copper (I) sulphate (Cu2SO4) electrolyte to mimic a thermogalvanic cell. Previous studies mainly concentrated on mechanical properties and the electric power generation ability of these structures; however, the goal of this study is to estimate the thermal resistance of the 3D-printed TPMS experimentally. This investigation elucidates their thermal resistances which in turn helps to appreciate the power output associated in the thermogalvanic structure. Schwarz P, Gyroid, IWP, and Split P geometries were considered for the experiment with electrolyte in the thermogalvanic brick. Among these TPMS structures, Split P was found more thermally resistive than the others with a thermal resistance of 0.012 m2 K W-1. The thermal resistances of Schwarz D and Gyroid structures were also assessed experimentally without electrolyte and the results are compared to numerical predictions in a previous Mater's thesis.
ContributorsDasinor, Emmanuel (Author) / Phelan, Patrick (Thesis advisor) / Milcarek, Ryan (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Energy is one of the wheels on which the modern world runs. Therefore, standards and limits have been devised to maintain the stability and reliability of the power grid. This research shows a simple methodology for increasing the amount of Inverter-based Renewable Generation (IRG), which is also known as Inverter-based

Energy is one of the wheels on which the modern world runs. Therefore, standards and limits have been devised to maintain the stability and reliability of the power grid. This research shows a simple methodology for increasing the amount of Inverter-based Renewable Generation (IRG), which is also known as Inverter-based Resources (IBR), for that considers the voltage and frequency limits specified by the Western Electricity Coordinating Council (WECC) Transmission Planning (TPL) criteria, and the tie line power flow limits between the area-under-study and its neighbors under contingency conditions. A WECC power flow and dynamic file is analyzed and modified in this research to demonstrate the performance of the methodology. GE's Positive Sequence Load Flow (PSLF) software is used to conduct this research and Python was used to analyze the output data.

The thesis explains in detail how the system with 11% of IRG operated before conducting any adjustments (addition of IRG) and what procedures were modified to make the system run correctly. The adjustments made to the dynamic models are also explained in depth to give a clearer picture of how each adjustment affects the system performance. A list of proposed IRG units along with their locations were provided by SRP, a power utility in Arizona, which were to be integrated into the power flow and dynamic files. In the process of finding the maximum IRG penetration threshold, three sensitivities were also considered, namely, momentary cessation due to low voltages, transmission vs. distribution connected solar generation, and stalling of induction motors. Finally, the thesis discusses how the system reacts to the aforementioned modifications, and how IRG penetration threshold gets adjusted with regards to the different sensitivities applied to the system.
ContributorsAlbhrani, Hashem A M H S (Author) / Pal, Anamitra (Thesis advisor) / Holbert, Keith E. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2020
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Description
About 20-50% of industrial processes energy is lost as waste heat in their operations. The thermal hydraulic engine relies on the thermodynamic properties of supercritical carbon dioxide (CO2) to efficiently perform work. Carbon dioxide possesses great properties that makes it a safe working fluid for the engine’s applications. This research

About 20-50% of industrial processes energy is lost as waste heat in their operations. The thermal hydraulic engine relies on the thermodynamic properties of supercritical carbon dioxide (CO2) to efficiently perform work. Carbon dioxide possesses great properties that makes it a safe working fluid for the engine’s applications. This research aims to preliminarily investigate the actual efficiency which can be obtained through experimental data and compare that to the Carnot or theoretical maximum efficiency. The actual efficiency is investigated through three approaches. However, only the efficiency results from the second method are validated since the other approaches are based on a complete actual cycle which was not achieved for the engine. The efficiency of the thermal hydraulic engine is found to be in the range of 0.5% to 2.2% based on the second method which relies on the boundary work by the piston. The heating and cooling phases of the engine’s operation are viewed on both the T-s (temperature-entropy) and p-v (pressure-volume) diagrams. The Carnot efficiency is also found to be 13.7% from a temperature difference of 46.20C based on the measured experimental data. It is recommended that the thermodynamic cycle and efficiency investigation be repeated using an improved heat exchanger design to reduce energy losses and gains during both the heating and cooling phases. The temperature of CO2 can be measured through direct contact with the thermocouple and pressure measurements can be improved using a digital pressure transducer for the thermodynamic cycle investigation.
ContributorsManford, David (Author) / Phelan, Patrick (Thesis advisor) / Calhoun, Ronald (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Lithium titanium oxide (LTO), is a crystalline (spinel) anode material that has recently been considered as an alternative to carbon anodes in conventional lithium-ion batteries (LIB), mainly due to the inherent safety and durability of this material. In this paper commercial LTO anode 18650 cells with lithium cobalt oxide (LCO)

Lithium titanium oxide (LTO), is a crystalline (spinel) anode material that has recently been considered as an alternative to carbon anodes in conventional lithium-ion batteries (LIB), mainly due to the inherent safety and durability of this material. In this paper commercial LTO anode 18650 cells with lithium cobalt oxide (LCO) cathodes have been cycled to simulate EV operating condition (temperature and drive profiles) in Arizona. The capacity fade of battery packs (pack #1 and pack#2), each consisting 6 such cells in parallel was studied. While capacity fades faster at the higher temperature (40°C), fading is significantly reduced at the lower temperature limit (0°C). Non-invasive techniques such as Electrochemical Impedance Spectroscopy (EIS) show a steady increase in the high-frequency resistance along with capacity fade indicating Loss of Active Material (LAM) and formation of co-intercalation products like Solid Electrolyte Interface (SEI). A two-stage capacity fade can be observed as previously reported and can be proved by differential voltage curves. The first stage is gradual and marks the slow degradation of the anode while the second stage is marked by a drastic capacity fade and can be attributed to the fading cathode. After an effective capacity fading of ~20%, the battery packs were disassembled, sorted and repackaged into smaller packs of 3 cells each for second-life testing. No major changes were seen in the crystal structure of LTO, establishing its electrochemical stability. However, the poor built of the 18650-cell appears to have resulted in failures like gradual electrolytic decomposition causing prominent swelling and failure in a few cells and LAM from the cathode along with cation dissolution. This result is important to understand how LTO batteries fail to better utilize the batteries for specific secondary-life applications.
ContributorsWadikar, Harshwardhan (Author) / Crozier, Peter (Thesis advisor) / Wang, Qing H (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Accurate forecasting of electricity prices has been a key factor for bidding strategies in the electricity markets. The increase in renewable generation due to large scale PV and wind deployment in California has led to an increase in day-ahead and real-time price volatility. This has also led to prices going

Accurate forecasting of electricity prices has been a key factor for bidding strategies in the electricity markets. The increase in renewable generation due to large scale PV and wind deployment in California has led to an increase in day-ahead and real-time price volatility. This has also led to prices going negative due to the supply-demand imbalance caused by excess renewable generation during instances of low demand. This research focuses on applying machine learning models to analyze the impact of renewable generation on the hourly locational marginal prices (LMPs) for California Independent System Operator (CAISO). Historical data involving the load, renewable generation from solar and wind, fuel prices, aggregated generation outages is extracted and collected together in a dataset and used as features to train different machine learning models. Tree- based machine learning models such as Extra Trees, Gradient Boost, Extreme Gradient Boost (XGBoost) as well as models based on neural networks such as Long short term memory networks (LSTMs) are implemented for price forecasting. The focus is to capture the best relation between the features and the target LMP variable and determine the weight of every feature in determining the price.

The impact of renewable generation on LMP forecasting is determined for several different days in 2018. It is seen that the prices are impacted significantly by solar and wind generation and it ranks second in terms of impact after the electric load. The results of this research propose a method to evaluate the impact of several parameters on the day-ahead price forecast and would be useful for the grid operators to evaluate the parameters that could significantly impact the day-ahead price prediction and which parameters with low impact could be ignored to avoid an error in the forecast.
ContributorsVad, Chinmay (Author) / Honsberg, C. (Christiana B.) (Thesis advisor) / King, Richard R. (Committee member) / Kurtz, Sarah (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Demand for green energy alternatives to provide stable and reliable energy

solutions has increased over the years which has led to the rapid expansion of global

markets in renewable energy sources such as solar photovoltaic (PV) technology. Newest

amongst these technologies is the Bifacial PV modules, which harvests incident radiation

from both sides of

Demand for green energy alternatives to provide stable and reliable energy

solutions has increased over the years which has led to the rapid expansion of global

markets in renewable energy sources such as solar photovoltaic (PV) technology. Newest

amongst these technologies is the Bifacial PV modules, which harvests incident radiation

from both sides of the module. The overall power generation can be significantly increased

by using these bifacial modules. The purpose of this research is to investigate and maximize

the effect of back reflectors, designed to increase the efficiency of the module by utilizing

the intercell light passing through the module to increase the incident irradiance, on the

energy output using different profiles placed at varied distances from the plane of the array

(POA). The optimum reflector profile and displacement of the reflector from the module

are determined experimentally.

Theoretically, a 60-cell bifacial module can produce 26% additional energy in

comparison to a 48-cell bifacial module due to the 12 excess cells found in the 60-cell

module. It was determined that bifacial modules have the capacity to produce additional

energy when optimized back reflectors are utilized. The inverted U reflector produced

higher energy gain when placed at farther distances from the module, indicating direct

dependent proportionality between the placement distance of the reflector from the module

and the output energy gain. It performed the best out of all current construction geometries

with reflective coatings, generating more than half of the additional energy produced by a

densely-spaced 60-cell benchmark module compared to a sparsely-spaced 48-cell reference

module.ii

A gain of 11 and 14% was recorded on cloudy and sunny days respectively for the

inverted U reflector. This implies a reduction in the additional cells of the 60-cell module

by 50% can produce the same amount of energy of the 60-cell module by a 48-cell module

with an inverted U reflector. The use of the back reflectors does not only affect the

additional energy gain but structural and land costs. Row to row spacing for bifacial

systems(arrays) is reduced nearly by half as the ground height clearance is largely

minimized, thus almost 50% of height constraints for mounting bifacial modules, using

back reflectors resulting in reduced structural costs for mounting of bifacial modules
ContributorsMARTIN, PEDRO JESSE (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2019
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Description
This is a two part thesis:

Part 1 of this thesis determines the most dominant failure modes of field aged photovoltaic (PV) modules using experimental data and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 5900 crystalline-Si glass/polymer modules fielded for 6 to

This is a two part thesis:

Part 1 of this thesis determines the most dominant failure modes of field aged photovoltaic (PV) modules using experimental data and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 5900 crystalline-Si glass/polymer modules fielded for 6 to 16 years in three different photovoltaic (PV) power plants with different mounting systems under the hot-dry desert climate of Arizona are evaluated. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is performed for each PV power plant to determine the dominant failure modes in the modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives, and thus, comes to the conclusion that solder bond fatigue/failure with/without gridline/metallization contact fatigue/failure is the most dominant failure mode for these module types in the hot-dry desert climate of Arizona.

Part 2 of this thesis determines the best method to compute degradation rates of PV modules. Three different PV systems were evaluated to compute degradation rates using four methods and they are: I-V measurement, metered kWh, performance ratio (PR) and performance index (PI). I-V method, being an ideal method for degradation rate computation, were compared to the results from other three methods. The median degradation rates computed from kWh method were within ±0.15% from I-V measured degradation rates (0.9-1.37 %/year of three models). Degradation rates from the PI method were within ±0.05% from the I-V measured rates for two systems but the calculated degradation rate was remarkably different (±1%) from the I-V method for the third system. The degradation rate from the PR method was within ±0.16% from the I-V measured rate for only one system but were remarkably different (±1%) from the I-V measured rate for the other two systems. Thus, it was concluded that metered raw kWh method is the best practical method, after I-V method and PI method (if ground mounted POA insolation and other weather data are available) for degradation computation as this method was found to be fairly accurate, easy, inexpensive, fast and convenient.
ContributorsShrestha, Sanjay (Author) / Tamizhmani, Govindsamy (Thesis advisor) / Srinivasan, Devrajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2014
Description
Surface roughness has a negative impact on several failures of materials medium. It can accelerate the pitting corrosion, increase effective heat transfer and increase the rate of effective charge loss. However, the controlled surface roughness may be desirable in many situations. The automotive lead-acid battery is very sensitive to such

Surface roughness has a negative impact on several failures of materials medium. It can accelerate the pitting corrosion, increase effective heat transfer and increase the rate of effective charge loss. However, the controlled surface roughness may be desirable in many situations. The automotive lead-acid battery is very sensitive to such effects. The cast-on-strap machine has the largest effect on the surface roughness of the lead-antimony alloy in our case study. The two-point correlation function is an efficient characterization tool for two-phase heterogeneous materials. Considering the nature that the two-point correlation function is a spatial statistical function, it cannot distinguish between a two-phase material or materials with surfaces containing protrusion of distinct heights. A case study to examine its capability in quantifying surface roughness isintroduced. The possibility of applying a simulated annealing procedure to optimize using information obtained from the two-point correlation function is investigated. Outcomes show a successful surface representation, as well as optimization, that agrees with the initially proposed hypothesis.
ContributorsBasyoni, Mohamed Nasser (Author) / Jiao, Yang Prof. (Thesis advisor) / Yang, Sui Dr. (Committee member) / Zhuang, Houlong Dr. (Committee member) / Arizona State University (Publisher)
Created2022