Master of Science in Engineering (MSEgr), Wright State University, 2014, Mechanical Engineering

Agriculture is a significant measure of an economy for a number of countries in the world. Currently, the agriculture sector relies heavily on conventional sources of energy for irrigation and other purposes. When, considering factors such as increasing costs of fossil fuels and extending new power lines, especially to remote locations where grid electricity is either inaccessible or expensive, a solar PV (photovoltaic) irrigation system can be an effective choice for irrigating farmland. Solar power eliminates the need to run electrical power lines to remote agriculture locations, which quickly turns the monetary equation in favor of solar irrigation over grid-powered irrigation. In addition, the cost of delivering fossil fuels to remote locations can be expensive. Solar power is ideal for agricultural irrigation, as most irrigation is required when the sun is shining brightly. Consequently, a PV powered irrigation system is a promising technology that could help meet the irrigation needs of remote agricultural. The two major goals of this research are to get an existing solar PV irrigation system working and to acquire experimental data using this system under various operating conditions. This research work is built upon a series of three senior design projects. These three senior design projects were to design and construct a solar irrigation system, an instrumentation system for this solar irrigation system, and a single axis solar translator. Specifically this thesis work entailed getting the instrumentation system to work properly, writing a LabVIEW program to automatically acquire data from installed sensors, integrating all three of these senior design projects into one PV irrigation system, getting the PV irrigation system installed on the roof of the Russ Engineering Building, and collecting a large amount of data on the system. All have been accomplished successfully. The PV irrigation system work presented in this thesis use two 224 watt PV modu (open full item for complete abstract)

Committee: James Menart Ph.D. (Advisor); Rory Roberts Ph.D. (Committee Member); Zifeng Yang Ph.D. (Committee Member) Subjects: Alternative Energy; Energy; Engineering; Mechanical Engineering

Master of Science (MS), Ohio University, 2017, Environmental Studies (Voinovich)

Ohio University demands over 120,000 Megawatt Hours of electricity annually and plans to reduce the institutional greenhouse gas emissions to 0 by 2075. The demand for electricity includes a significant environmental footprint under the current electricity procurement contract. Addressing the best option for an energy user therefore requires careful examination of the environmental, social, and financial costs and benefits of each scenario. This research develops optimal scenarios for a solar PV installation in Athens, OH and assesses the sustainability of four solar PV installation scenarios and two status quo scenarios. Finally, Analytical hierarchy process is used to simulate decision making process with multiple criteria. The criteria are categorized as environmental, social, and financial and decisions are simulated with three sets of weighting on each criterion. A solar installation helps verify modeled results within the research which concludes that a solar PV farm with tracking or rooftop would serve as the most sustainable electricity procurement decision for OHIO University.

Committee: Derek Kauneckis Ph. D (Advisor); Daniel Karney Ph. D (Committee Member); Greg Kremer Ph. D (Committee Member) Subjects: Environmental Management; Environmental Studies; Sustainability

Master of Engineering, Case Western Reserve University, 2025, EMC - Aerospace Engineering

Analysis of three missions has been carried out with a set of three power and three propulsion systems to determine system synergy as well as to find an optimal system for each mission. The three missions are GTO to LLO, LMO, and Titan flyby. The three propulsion systems of analysis are Hall Effect Thrusters, Magnetoplasmadynamic Thrusters, and VASIMR Thrusters. The three power systems of analysis are Silicon photovoltaics, multi-junction photovoltaics, and nuclear reactors. The mission to Low Lunar Orbit has a maximum trip time of 8 weeks, and four systems are capable of achieving this result. Those systems are Hall-Nuclear, MPDNuclear, VASIMR-MJ, and VASIMR-Nuclear, the last of which achieves the target in just 26 days. The VASIMR-Nuclear system is also capable of bringing the most passengers with a total capacity of 255 people. The mission to LMO was limited to a maximum trip time of 9 months, and 1 system is capable of achieving this result. This system is again VASIMR-Nuclear, capable of bringing 31 people the LMO in 241 days, or about 8 months. The mission to Titan flyby using the VASIMR-Nuclear system is capable of bringing 54500 kg of dry mass to Titan flyby at 1000 km at 3.13 km/s relative to the planet.

Committee: Paul Barnhart (Advisor); Majid Rashidi (Committee Member); Richard Bachmann (Committee Member) Subjects: Aerospace Engineering

Master of Science (MS), Bowling Green State University, 2024, Physics

Cd(Se,Te) has emerged as a leading choice for commercial thin-film PV devices, owing to their lower cost of production, high energy yields, and low degradation rates compared to silicon technology. Despite significant advancements, Cd(Se,Te) cells suffer from recombination losses, reducing the open-circuit voltage (Voc). This thesis aims to identify, distinguish, and quantify recombination losses and their locations within Cd(Se,Te) solar cells via temperature and light intensity-dependent current-voltage (JVTi) analysis. Cd(Se,Te) solar cells were modeled using COMSOL Multiphysics, simulating parameters such as temperature (T ), light intensity (i), front surface recombination velocity (Sf), back surface recombination velocity (Sb), bulk lifetime (τ ), conduction and valence band offset (CBO and VBO at heterojunctions), and back contact Schottky barrier height (Φbp). Additionally, graded and uniform selenium devices were studied, and ZnTe:Cu was investigated as a back contact interface. In this work, recombination activation energies, Ea, from JVTi studies were shown to quantify the front interface conduction band offset losses when the interface band gap is smaller than the bulk band gap and when front interface recombination dominates. If the Ea equals the bulk band gap, then Voc losses may occur at the front interface or within the bulk. When the front surface recombination and bulk lifetime are moderately low, a transition from front surface (low Ea) to bulk (higher Ea) mechanisms can be observed with increasing light intensity, i. Back surface recombination has negligible effects on Voc for the device parameters specified herein. Comparison of Cd(Se,Te) JVTi data provided by NREL to simulations in this work indicates that front surface recombination dominates Voc losses for Sf = 103 cm/s and CBO = -0.2 eV for that particular device. Adjusting the band alignment to CBO = 0 eV and reducing Sf would significantly increase Voc.

Committee: Marco Nardone (Committee Chair); Mikhail Zamkov (Committee Member); Alexy Zayak (Committee Member) Subjects: Physics

Master of Science, University of Toledo, 2022, Electrical Engineering

The push for renewable energy has certainly driven the world towards sustainability. However, the incorporation of clean energy into the electric power grid does not come without challenges. When synchronous generators are replaced by inverter based Photovoltaic (PV) generators, the voltage profile of the grid gets considerably degraded. The effect in voltage profile, added with the unpredictable generation capacity, and lack of good reactive power control eases opportunities for sneaky False Data Injection (FDI) attacks that could go undetected. The challenge is to differentiate these two phenomena. In this thesis work, an attack is exposed in a grid environment with high PV penetration, and challenges associated with designing a detector that accounts for inefficiencies that comes with it is discussed. The detector is a popular Kalman Filter based anomaly detection engine that tracks deviation from the predicted behavior of the system. Chi-squared fitness test is used to check if the current states are within the normal bounds of operation. The work concludes by exposing a vulnerability in using static and dynamic threshold detectors which are directly affected by day-ahead demand prediction algorithms that have not been fully evolved yet. Finally, some of the widely used machine learning based anomaly detection algorithms is used to overcome the drawbacks of model-based algorithm.

Committee: Weiqing Sun (Committee Chair); Ahmad Javaid (Committee Member); Junghwan Kim (Committee Member) Subjects: Electrical Engineering

Master of Science, The Ohio State University, 2022, Comparative and Veterinary Medicine

Pseudomonas syringae pv. syringae (Pss) is an emerging seed-borne pathogen that causes Pseudomonas leaf spot (PLS) disease in bell peppers. It causes severe necrotic lesions on pepper leaves that can spread to 50-80% of the field under favorable environmental conditions. PLS can cause significant economic losses to pepper production if the disease is left uncontrolled. However, not much is known about the genes that Pss carries to be able to cause disease in peppers. It is important to understand the virulence genes that Pss carries so that appropriate measures can be developed to control Pss in peppers. Therefore, part of my research aimed to use comparative genomic analysis to understand the genes in Pss that are important for virulence in pepper seedlings. The Pss strains (n=16) evaluated showed varying levels of virulence (disease severity and Pss population) at 3-, 7-, and 14-days post-infection (dpi) on the susceptible 'California Wonder' pepper variety in a controlled growth chamber environment. The Pss strains also displayed varying growth, biofilm development, and motility in vitro in M9 minimal broth at 28˚C, however, the variation in in vitro performance did not explain the variation in the virulence of the Pss strains in pepper seedlings. Whole genome sequencing was performed on these Pss strains. The genes were functionally characterized, and core genomes were separated from the variable genomes between the Pss strains. A total of 812 genes were variable among the Pss strains including known virulence genes. Additionally, a multivariate correlation analysis identified 285 genes that were significantly correlated to the virulence of Pss in pepper seedlings (r2 of  0.5 to 0.675; P<0.01). The genes that were significantly correlated with the virulence of Pss strains included known virulence genes associated with motility (n=2), biofilm (n=5), and Type III and VI secretion systems (T3SS and T6SS) (n=9). Further, the two strains (SM156-18 and SM226-1) that (open full item for complete abstract)

Committee: Gireesh Rajashekara (Advisor); Sally Miller (Committee Member); James Fuchs (Committee Member) Subjects: Biology; Microbiology; Plant Pathology

Doctor of Philosophy, University of Toledo, 2022, Engineering

As the world transitions from fossil to renewable sources of electricity, management of the electrical grid is becoming increasingly complex. Where once generation flowed unidirectionally from large spinning generation to variable loads, in the new world generation is often also stochastic and power flows in multiple directions, including from sources deep within the distribution system. This necessitates changes to the manner in which the grid is controlled. This dissertation explores the possibilities of transactive energy as a means of dis- tributing control throughout this complex system. A transactive energy testbed has been created on the University of Toledo campus which is used to study various con- trol strategies, both transactive and non-transactive, which are useful for integrating distributed energy resources and bringing demand-side assets such as buildings into the control equation. Several experiments with non-transactive control strategies for buildings and DER, which have been performed on this testbed, are discussed. These include experiments with peak-demand management, mitigation of variability from photovoltaic generation using a battery energy storage system, and load following applications. The university is now building a transactive energy network which will allow testing of transactive control systems. Before these experiments take place, it is necessary to understand which use cases which can best be deployed, which will be of the greatest value to participants, and how these can be evaluated for success. The core of this work is a valuation study of transactive energy use cases which develops metrics for operation and evaluation of their performance in both technical and economic terms. Additionally, one transactive supply-side use case is discussed which seeks to build a single transactive actor from the combination of a nuclear power facility with on-site renewable generation and hydrogen electrolysis.

Committee: Raghav Khanna (Advisor); Michael Heben (Committee Member); Ahmad Javaid (Committee Member); Mohammed Niamat (Committee Member); Daniel Georgiev (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2020, Electrical and Computer Engineering

The abundance of solar resources in Saudi Arabia motivates analyzing the possibility of supplying the Saudi electric power demand using solely renewable resources and storage. This is the main objective of this research work. First, a generation and transmission expansion planning model is developed and tailored to the power system of Saudi Arabia, targeting the year 2040. We consider utility-scale generation technologies including wind power plants, solar power plants, storage facilities, and also flexible combined cycle gas turbines. We represent long-term uncertainty in terms of demand growth via scenarios, and short-term uncertainty to characterize daily solar, wind, and demand patterns via typical days. We analyze a number of case studies with increasing renewable integration targets to characterize the Saudi Arabian power system in 2040. Health, environment, and security analyses are out of the scope of this research. We conclude that it is important to actively promote the integration of renewable power in the Saudi Arabia power sector if a high renewable integration is desired. Second, a stochastic all-solar operation model is developed. The aim of this model is to operate the Saudi electric power system considering only solar power units and storage facilities. We use the long-term planning model above to generate an all-solar power system and focus on the operation problem from the perspective of the operator, considering an operation horizon of one year. We use a number of year-long cases to characterize the operation of an all-solar power system in Saudi Arabia. We conclude that an only PV generation mix requires higher storage capacity and higher installed generation capacity than both an only CSP generation mix and a hybrid PV-CSP generation mix. Third, a model to coordinate the supply of electricity and the production and transport of freshwater is developed. The time span of the model is one year and is relevant to countries like Saudi Ara (open full item for complete abstract)

Committee: Antonio Conejo Prof. (Advisor); Mahesh Illindala Prof. (Committee Member); Theodore Allen Prof. (Committee Member) Subjects: Electrical Engineering

Master of Sciences, Case Western Reserve University, 2020, EECS - Computer and Information Sciences

Linear Performance Loss Rate (PLR) has been widely used in the photovoltaic (PV) community as a tool for modeling the degradation of PV modules over time. In the real-world commercial deployment of solar power, PV modules are manufactured by different companies to varying degrees of quality, deployed in a wide variety of locations, and undergo system damage and degradation. Since factors such as these will affect the performance of PV modules in different ways after data is already recorded, a linear model would not be fully able to effectively capture their lifetime performances. Many tools and models have been developed for specific lab tested PV systems, but have failed to generalize to large quantities of commercial powerplants. In this work, we introduce a new solar power plant analysis tool that uses a non-linear PLR method that better models the degradation of PV modules over their lifetime, and we will be testing our model on a population of 1100 commercial PV systems that have been operating for up to 6 years. In this dataset, the median adjusted R2 value of the Linear PLR method is 0.03, while the median adjusted R2 of a Segmented method is increased at 0.21. Decomposition by season can further increase the performance of both linear and segmented methods to median adjusted R2 values of 0.19 and 0.28, respectively. Comparing the metadata factors to the calculated PLR values can lead to insights regarding which factors contribute to the greatest change in PLR and degradation of PV systems.

Committee: Roger French (Advisor); Xusheng Xiao (Committee Chair); Koyuturk Mehmet (Committee Member) Subjects: Computer Science

Master of Sciences (Engineering), Case Western Reserve University, 2020, EECS - Computer Engineering

The world has never been more reliant on energy. With unsustainable fossil fuel powering a titanic 85 percent of the world's energy consumption, the demand for an alternative sustainable and renewable source of energy is growing. One of the best candidates is Solar Power, although that clean source comes along with the problem of unpredictability as it is heavily reliant on weather and not easy to tell if a solar panel is not optimally functioning or not. Thus comes the need to calculate PLR, or Performance Loss Rate of Photovoltaic Modules. Among other things, the Solar Durability and Lifetime Extension Center (SDLE) is responsible for calculating this by building models with a heavy emphasis on data-based time series analysis. This was previously done in R, a programming language made for Data Science. However, with scalability and resource efficiency in mind when processing enormous amounts of data, this language alone has severe inefficiencies. This thesis explores how a translation to Spark, a language made to solve the Big Data and the Big Compute problem through distributed computing, would improve efficiency while keeping the same functionality. It was found that neither the Spark solution or the original R solution was the optimal path; rather, a hybrid mix of the two proved to be the best in terms of time efficiency and performance.

Committee: Shuai Xu (Committee Chair); Roger French (Advisor); Ming-Chun Huang (Committee Member) Subjects: Computer Science

Doctor of Philosophy, University of Toledo, 2019, Electrical Engineering

The increasing complexity in the power grid, which is driven by distributed energy resources (DER) such as distributed generation, storage systems, and controllable loads, demands advanced control strategies for effective energy management. This dissertation demonstrates the development and implementation of two control strategies for managing DER. The first control objective is mitigating variability generated by PV output power using a battery energy storage system (BESS). The proposed method uses a novel adaptive moving average and adaptive state of charge (SoC) correction control method to achieve a better tradeoff between battery utilization and degree of PV power smoothness. The second control objective is achieving demand response, which refers to the mechanism that can shift the consumption of a load, such as the energy system in a building, to balance demand and supply of electricity, without harming the thermal comfort of the building's occupants and the free-will of the consumer. This is accomplished with PNNL's Intelligent Load Control (ILC), which manages the power consumption of loads based on priority criteria. ILC's unidirectional and bidirectional capability and their respective applications are demonstrated with the testbed. Additionally, this dissertation also explores the real-life implementation of these control strategies at the Scott Park campus (SPC) of the University of Toledo (UT). The SPC consists of eight buildings, a 1 MW solar array, and a 130-kWh BESS. For the dissertation work, a communication and control infrastructure has been created on the SPC electrical network by integrating an Internet of Things (IoT) system using Eclipse VOLTTRON. This infrastructure establishes communication and control between various devices on the SPC, which is used to validate and implement the proposed control strategies.

Committee: Raghav Khanna (Advisor); Mansoor Alam (Committee Member); Daniel Georgiev (Committee Member); Richard Molyet (Committee Member); Michael Heben (Committee Member) Subjects: Electrical Engineering; Energy

Master of Sciences, Case Western Reserve University, 2019, EMC - Mechanical Engineering

Solar panels installed on residential rooftops have gained popularity because of their economic efficiency as well as environmental friendliness. However, this type of installation affects the fire performance on the rooftop and introduces new fire concerns. To gain a fundamental understanding of this process, a gas burner fire over an inclined surface (90 cm wide and 440 cm long) with and without a parallel top panel is numerically simulated using FireFOAM. Cases with three different inter-panel distances (6.25 cm, 12.5 cm, and 25 cm) and a case without the top panel are simulated. The results show that the top panel has multiple effects on the fire behaviors. First, it reflects and increases the radiative heat input on the bottom panel. Second, it confines the flow between the two panels and forces the flame to stay close to the bottom panel, increasing the conductive heat flux onto the bottom panel. Third, the top panel reduces the fresh air (oxygen) that enters the fire domain. When the equivalence ratio drops below one, this effect impedes the gas-phase reaction and decreases the gas-phase temperature, and hence the heat flux on the lower panel. As a result of these effects, the flame temperature and heat flux on the lower panel first increases and then decreases when the inter-panel distance decreases. Physics-based mitigation strategies are proposed and shown effective to alleviate the adverse effects of the solar panels on the rooftop fire performance.

Committee: Ya-ting Liao (Committee Chair); James T'ien (Committee Member); Fumiaki Takahashi (Committee Member) Subjects: Mechanical Engineering

Doctor of Philosophy, University of Toledo, 2018, Civil Engineering

This dissertation explores the eco-design concepts for emerging PV cells. By conducting life cycle assessment (LCA) method, I addressed the following questions: (1) What is the environmental impact of a scalable perovskite PV cell? (2) How important are the metal emissions from the emerging thin film devices during the use phase? (3) What are the environmental impacts and costs of the materials used in emerging PVs? These questions are addressed in the analyses presented in the Chapters two, three and four, respectively. Chapter two assesses the environmental impacts of perovskites PVs that have device structures suitable for low cost manufacturing. A structure with an inorganic hole transport layer (HTL) was developed for both solution and vacuum based processes, and an HTL-free structure with printed back contact was modeled for solution-based deposition. The environmental impact of conventional Si PV technology was used as a reference point. The environmental impacts from manufacturing of perovskite solar cells were lower than that of mono-Si. However, environmental impacts from unit electricity generated were higher than all commercial PV technology mainly because of the shorter lifetime of perovskite solar cell. The HTL-free perovskite generally had the lowest environmental impacts among the three structures studied. Solution based methods used in perovskite deposition were observed to decrease the overall electricity consumption. Organic materials used for preparing the precursors for perovskite deposition were found to cause a high marine eutrophication impact. Surprisingly, the toxicity impacts of the lead used in the formation of the absorber layer were found to be negligible. Chapter three addresses the life cycle toxicity of metals (cadmium, copper, lead, nickel, tin and zinc) that are commonly used in emerging PVs. In estimating the potential metal release, a new model that incorporates field conditions (crack size, time, glass thickness) and phy (open full item for complete abstract)

Committee: Defne Apul (Committee Chair); Michael Heben (Committee Member); Randall Ellingson (Committee Member); Constance Schall (Committee Member); Cyndee Gruden (Committee Member); Kumar Ashok (Committee Member) Subjects: Energy; Environmental Engineering

Doctor of Philosophy (Ph.D.), University of Dayton, 2017, Mechanical Engineering

Solar energy, as an emerging renewable clean energy, has been rapidly growing for 15 years all over the world and is expected to grow 15% annually until 2020. In 2015, at least 40 GW of Photovoltaic (PV) systems were installed, achieving 178GW current solar power installation worldwide. In the next five years, 540 GW cumulative capacities are expected to be installed worldwide and US contributed 6.5 GW PV installations in 2015. US electricity demand is expected to be dominated by solar power by 2050 or even earlier. The widespread deployment of PV will not only contribute to a reduction in greenhouse gas emission, but can also mitigate the worldwide fossil fuel depletion. As the number of PV systems increases, the mass of PV waste will increase as well, adding a new source to the existing waste stream. The amount of End-of-Life (EoL) PV will approach 13.4 million ton worldwide, including approximately 5.5 million ton located in the US by 2025. PV contains high value, toxic, and energy-intensive materials. In addition, the market price of some materials utilized in the thin-film and crystalline PV technologies has drastically increased in the recent years. There is a strong need of coordinating the information to optimize the reverse logistics planning in a photovoltaic (PV) recycling network in the U.S. Two major tasks are included: 1) locating PV Recycling Centers (PVRC); 2) allocating Transportation Companies (TC) shipping PV installation sites (PVIS) to PVRC. One contribution of this dissertation is to decide the optimal number, as well as the location of PVRC by minimizing the overall cost. Another contribution is to determine the optimal distribution scheme to minimize the transportation cost among TC, PVIS, and PVRC. In order to accomplish the two tasks, a mathematical modeling framework was developed to facilitate PV recycling in an economically and environmentally feasible manner. The framework included two mathematical models: 1) Multi-Facility Opt (open full item for complete abstract)

Committee: Jun-Ki Choi (Advisor); Chuck Ebeling (Committee Member); Ron Deep (Committee Member); Shuang-ye Wu (Committee Member) Subjects: Energy; Mechanical Engineering

Master of Science (M.S.), University of Dayton, 2017, Renewable and Clean Energy

Photovoltaic-thermal (PVT) technology is a relatively new technology that comprises a photovoltaic (PV) panel coupled with a thermal collector to convert solar radiation into electricity and thermal energy simultaneously. Since cell temperature affects the electrical performance of PV panels, coupling a thermal collector with a PV panel contributes to extracting the heat from the latter to improve its performance. In order to ensure a sufficient temperature difference between the PV cells and the working fluid temperature entering the thermal collector, the circulated water has to reject the heat that has been removed from the PV cells into a relatively colder environment. Borehole thermal energy storage (BTES), which is located underground, often serves as this relatively colder environment due to the stability of underground temperatures, which are usually lower than the working cell temperature. Use of BTES is especially beneficial in summer, when the degradation in cells efficiency is highest. In this thesis, the electrical, thermal, and economic performances of a PVT system are evaluated for three types of buildings -- residential, small office, and secondary school -- in two different climates in the United States, one of which is hot and the other is cold. For each case, two different scenarios are considered. In the first, a PVT system is coupled with BTES, and a ground-coupled heat pump (GCHP) is in use. In the second, a PVT system is coupled with BTES and no GCHP is in use. Each scenarios' GCHP performance is assessed as well. Both the PVT collectors and GCHP performances are evaluated over short and long-term to study the effect of continued ground heat imbalance on both technologies.

Committee: Andrew Chiasson Ph.D. (Committee Chair); Youssef Raffoul Ph.D. (Committee Member); Robert Gilbert Ph.D. (Committee Member) Subjects: Energy; Engineering; Mechanical Engineering

Doctor of Philosophy, Case Western Reserve University, 2017, Materials Science and Engineering

Over 1000 photovaltaic (PV) systems' lifetime performance changes under real-world operation conditions were studied in pursuit of a better understanding of the impact of external variables on the durability of PV systems. These PV systems are part of the SDLE Research Center's global sunfarm network (GSFN), which has developed to include 787 PV power plants and outdoor test facilities. The analysis of this large PV data set was driven by a non-relational data warehouse for multiple heterogeneous energy data, referred to as Energy-CRADLE. The rate of power change was calculated using a month-by-month approach, explicitly, a linear regression model (the ß model) was fitted to each 30 day increment of data to train a predictive model for the output power of PV systems. The system's power output was then predicted under a selected environmental condition for each 30 day segment. A second linear or piecewise linear regression model (the ¿ model) was fitted to the monthly predicted power output values, with a weight on the inverse of the error of the prediction. For 655 PV systems where the monthly predicted values were well explained by a linear model, the annual rate of change were calculated from the slope of the linear regression fitting. These 655 systems were between two and eight years old, they were distributed in 9 different climate zones according to Koppen-Geiger Climate classification, the PV modules being used were from 20 different PV manufacturers, and the inverters being used were from 9 different manufacturers. A third multiple regression model (the ¿ model) was fitted to the 655 rate of change results. The variables being considered in the third model exhausted all external variables of the PV systems. Through a statistical variable selection method, stepwise Akaike information criterion (AIC), the variables that had statistically significant influence on the system change rate were selected and rank ordered by their contribution follows: K (open full item for complete abstract)

Committee: Roger French (Advisor); Timothy Peshek (Committee Member); David Matthiesen (Committee Member); Mehmet Koyuturk (Committee Member) Subjects: Energy; Engineering

Doctor of Philosophy, The Ohio State University, 2016, Biomedical Engineering

Volume overload (VO) induced heart failure results from an increase in blood volume (preload) to the heart. The heart responds to increases in hemodynamic load through compensative remodeling. VO has a distinct pattern of remodeling compared to pressure overload induced heart failure, which results in fibrosis. VO results in a net decrease in extracellular matrix (ECM). This loss of ECM contributes to the progression of the disease due to the loss of structural integrity. Since cardiac fibroblasts (CFs) are the main cells responsible for maintaining ECM in the heart, we characterized the in vitro phenotype of CFs isolated from a rat VO model, aortocaval fistula (ACF). Compared to sham operated animals, ACF fibroblasts displayed a phenotype that we described as “hypofibrotic”. ACF CFs secreted relatively less collagen and profibrotic molecules, such as a-smooth muscle actin (aSMA) and connective tissue growth factor (CTGF). Interestingly, ACFs produce approximately twice as much transforming growth factor-ß1 (TGF-ß), a key profibrotic stimulus, as their sham counterparts. However, there were no changes in the canonical TGF-ß pathway that could account for the hypofibrotic phenotype observed in ACF fibroblasts. Since others have shown that the cytoskeleton and the Rho/ROCK pathway play a role in fibroblast phenotype, we characterized the actin cytoskeleton in sham and ACF fibroblasts. We found that ACF CFs have significantly less F-actin than sham CFs. We were able to show that it is possible the actin cytoskeleton might account for phenotypic differences in CFs by chemically altering the amounts of F-actin and G-actin. When the cells were treated with a ROCK inhibitor, which allows F-actin to depolymerize into G-actin, CFs displayed a more hypofibrotic phenotype. Conversely, enhancement of F-actin with jasplakinolide treatment forced the CFs to have a profibrotic phenotype. Numerous studies have linked substrate modulus with effects on the cytoskeleton. S (open full item for complete abstract)

Committee: Keith Gooch PhD (Advisor); Jun Liu PhD (Committee Member); Pamela Lucchesi PhD (Committee Member); Aaron Trask PhD (Committee Member) Subjects: Biomedical Engineering

Doctor of Philosophy, Case Western Reserve University, 2017, Macromolecular Science and Engineering

The lifetime performance and degradation behavior of photovoltaic (PV) modules is of the utmost importance for the success and growth of solar energy as a major resource for fulfilling growing worldwide energy needs. While PV reliability has been a concern for some time, existing qualification testing methods do not reflect a cohesive picture of the science behind module degradation, and are not capable of accurately predicting module lifetime performance. Towards these goals, a statistical methodology, semi-gSEM, was developed and applied to investigate the response of full sized PV modules to accelerated stress conditions. The results of this initial study indicated that a correlation exists between system level power loss and the buildup of acetic acid resulting from the hydrolytic degradation of ethylene-vinyl acetate (EVA) polymer encapsulant. To further explore this proposed mechanistic pathway, a study was designed and conducted to characterize the degradation of mini-module samples under damp heat accelerated stress conditions. Mini-module samples featured two construction geometries that differed in the thicknesses of screen-printed silver conductive lines (SP-Ag) to assess the impact of gridline size on damp heat induced degradation. Samples were measured non-destructively at many points along their degradation pathway, using techniques that gathered both chemical and electrical information. The semi-gSEM analytical method was applied to this dataset to highlight degradation pathways and mechanisms observed in the experimental results. An EVA encapsulant spectroscopic degradation feature was found to be statistically related to quantified degradation features of simultaneously measured EL images. In turn, the EL image degradation was found to be statistically related to I-V curve parameters describing system level power loss. The degradation pathway observed was attributed to EVA encapsulant degradation leading to metallization corrosion and ultim (open full item for complete abstract)

Committee: Roger French (Advisor); Michael Hore (Committee Member); Timothy Peshek (Committee Member); Laura Bruckman (Committee Member); Ozan Akkus (Committee Member) Subjects: Materials Science; Plastics; Polymers

Doctor of Philosophy, University of Toledo, 2016, Electrical Engineering

Hybrid power generation system and distributed generation technology are attracting more investments due to the growing demand for energy nowadays and the increasing awareness regarding emissions and their environmental impacts such as global warming and pollution. The price fluctuation of crude oil is an additional reason for the leading oil producing countries to consider renewable resources as an alternative. Saudi Arabia as the top oil exporter country in the word announced the "Saudi Arabia Vision 2030" which is targeting to generate 9.5 GW of electricity from renewable resources. Two of the most promising renewable technologies are wind turbines (WT) and photovoltaic cells (PV). The integration or hybridization of photovoltaics and wind turbines with battery storage leads to higher adequacy and redundancy for both autonomous and grid connected systems. This study presents a method for optimal generation unit planning by installing a proper number of solar cells, wind turbines, and batteries in such a way that the net present value (NPV) is minimized while the overall system redundancy and adequacy is maximized. A new renewable fraction technique (RFT) is used to perform the generation unit planning. RFT was tested and validated with particle swarm optimization and HOMER Pro under the same conditions and environment. Renewable resources and load randomness and uncertainties are considered. Both autonomous and grid-connected system designs were adopted in the optimal generation units planning process. An uncertainty factor was designed and incorporated in both autonomous and grid connected system designs. In the autonomous hybrid system design model, the strategy including an additional amount of operation reserve as a percent of the hourly load was considered to deal with resource uncertainty since the battery storage system is the only backup. While in the grid-connected hybrid system design model, demand response was incorporated to overcome the impact o (open full item for complete abstract)

Committee: Lingfeng Wang (Committee Chair); Hong Wang (Committee Member); Jackson Carvalho (Committee Member); Richard Molyet (Committee Member); Weiqing Sun (Committee Member) Subjects: Electrical Engineering; Energy

Master of Science, The Ohio State University, 2016, Industrial and Systems Engineering

Evaluating the capacity value of solar PV plants can pose significant challenges due to their dependence on geographic and climatic conditions, which are highly variable and uncertain. Also, the way the data are recorded gives a significant variation in capacity value estimates. In this dissertation, different capacity value metrics are reviewed, several case studies are summarized and capacity value using the Effective Load Carrying Capability (ELCC) metric is estimated for 100 MW PV plants located across North America. ELCC estimates using hourly and minute-based solar data are compared, ELCCs are computed after shifting the load data ahead and behind by one hour to account for the sloppiness in reporting load data, and ELCC estimates using modeled and measured solar data are compared.

Committee: Ramteen Sioshansi Dr. (Advisor); Antonio Conejo Dr. (Committee Member) Subjects: Industrial Engineering