Master of Science (M.S.), University of Dayton, 2018, Mechanical Engineering

Prior research has shown that occupant behavior in residences accounts for nearly 50% of the energy consumption. It has also emphasized the need to strengthen the interdisciplinary focus on human dimensions of energy use in order to drive energy reduction. In this context, a behavior energy reduction study has been conducted on over 400 single-family, detached residences located in the Midwest of the US, all owned by a local university, and with a typical occupancy of 4-6 students. The housing set analyzed includes a diversity of houses, with construction years ranging from the early 1900s to current with wide variation in energy efficiency characteristics. For this study, historical energy data spanning the prior two academic years was used to construct predictive energy models for each residence. These models were used as baselines for the present study, offering a means to predict energy use for new weather conditions, thus providing a basis for comparison to actual use during any meter period. For this study, energy report cards were generated each month, including grades for electrical, gas, and overall energy consumption and delivered to each resident of all houses every month. The report cards also documented energy and carbon savings, both for individual residences and the totality of residences. It also identified the top performing residences and provided the most important behavioral energy reduction strategies for any months. Winning houses received Energy GPA champion T-shirts to advertise the initiative and engender competitive desire. Energy savings of 7.8% in natural gas and 5.2% electrical energy was achieved. Moreover, a statistical comparison of the best and worst performing residences enabled estimation of potential behavioral energy reduction throughout the entirety of the housing set.

Master of Sciences, Case Western Reserve University, 2022, Physics

The increasing adoption of renewable sources of electricity (i.e. wind and solar farms) is being driven by the demand for carbon neutral electricity production. Although zero carbon is emitted during electricity production, these renewable energy sources suffer from intermittency, which is a mismatch between the supply and demand of electricity of the grid. Renewable energy sources, such as wind and solar, produce their peak electricity at off-demand periods of the day. This strains the electrical grid as it risks over-generation in some locations as well as a need for quick ramping of the electrical load which is hard on electricity producing infrastructure. As a partial solution to intermittency, pumped storage hydropower (PSH) is the dominant form of grid-scale energy storage. PSH accounts for 95% of the U.S. grid-scale storage capacity, which amounts to 22.9 GW of capacity [1]. The EIA also estimates with all possible sites, the U.S. can double their PSH capacity [1]. However, much more than that is not feasible being constrained by the availability of locations suitable for PSH. As a result, other gridscale energy storage options are in development. The main options include batteries, thermal energy storage, compressed air energy storage (CAES) and flywheels. However, these storage options are plagued by high cost per kWh prices, location specificity (ex. PSH, CAES) and/or low energy density. With these concerns in mind, Cratus LLC is developing a molten salt thermal energy storage option known as ThermaBlox, which is location-independent, low-cost, and high-capacity (with the capability to scale). ThermaBlox will play a significant role in intermittency reduction while enabling increased adoption rates of renewable energy.

Master of Arts, Miami University, 2022, Economics

In 2011, Germany closed almost half of its nuclear nuclear plants and initiated a complete phaseout by 2022. This paper compares the trajectory of Germany's real GDP per capita, nitrous oxide pollution, carbon dioxide emissions, and particulate matter 2.5 before and after the nuclear energy shutdown with the trajectory of a weighted combination of similar countries, using weights determined endogenously by data. Synthetic Germany provides a counterfactual of what would have happened to the German economy and environment in the absence of the rapid nuclear plant closures. We find that the shutdown had positive effects on economic growth, contradicting previous literature. Each of our environmental outcomes have positive treatment effects, suggesting that pollution increased as a result of the nuclear energy shutdown and phaseout. Nitrous oxide pollution has particularly robust results.

Master of Arts (MA), Ohio University, 2022, Geography (Arts and Sciences)

Environmental issues such as habitat destruction, pollution, and climate change have spurred societies around the world to invest in new forms of alternative energy to reduce dependency on fossil fuels and the impacts that result from their extraction and use. The United States is the largest economy on Earth and consumes the most fossil fuels per capita. In this regard, the U.S. is lagging behind in terms of developing and utilizing alternative energy, but it is not the case that alternatives beyond fossil fuels are not being utilized at all. In fact, one of the biggest alternative energy booms in the U.S. has developed around wind energy. At the same time, the fossil fuel industry has undergone massive changes, shifting to natural gas while phasing out the use of coal. The state of Iowa has been a leader in developing and utilizing wind power for more than a decade, and in combination with utilizing more natural gas, has phased out using coal as a primary source for generating electricity. Like Iowa, Ohio has been replacing coal with natural gas in recent years, but unlike the Hawkeye State, has largely shunned wind power. Both states have gone in opposite directions in terms of electricity generation, but both have reduced their carbon footprint by very large amounts. In this thesis, I compare and contrast Iowa and Ohio

Doctor of Philosophy (Ph.D.), University of Dayton, 2021, Mechanical Engineering

The building sector has been identified as one of the biggest contributions to electricity and natural gas consumption in the U.S. These findings have necessitated the need for the development of energy saving initiatives in the sector, which will aid in reducing greenhouse gas emission needed to reduce the risk of climate change. However, despite several efforts by state agencies, such as the implementation of Property Assessed Clean Energy (PACE) and On-Bill Repayment or On-Bill Financing of energy efficiency investments, there are significant challenges to achieving energy efficiency in the building sector. Fundamentally the question is “How do we find the most cost effective energy efficiency measures present in the world?” Conventional energy audits, the typical way to discern, struggle from high cost, inconsistency in audit recommendations, and a lack of people trained to deliver. Thus, the approach just is not capable of “at-scale” identification of the measures to address first, then second, and so on. Additionally, it is essential that the savings from any investment and/or even behavioral changes be capable of being measured with accuracy in order to improve the ability to find the most effective energy reduction measures existing in the broader building sector and in order to communicate the relative economic benefits from upgrades to building owners. At this time, unless there are short-interval energy meters in buildings, the ability to measure savings with accuracy is just not there. As a solution, this dissertation investigates utilizing smart Wi-Fi thermostats data to conduct visual energy audits and predict energy savings with improved accuracy from any energy systems upgrade and any behavioral modification. The study leverages data from 101 residences owned by the University of Dayton. In 2015 prior University of Dayton researchers completed energy audits of these; documenting the geometric and energy characteristics and occupancy, as well as d (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2020, Environment and Natural Resources

The ongoing shale energy revolution has transformed global energy markets and positioned the United States as a leader in oil and natural gas production and exports for the first time in generations. However, little scholarly attention has been directed toward the downstream impacts of these developments on the people and places which experience energy export activity or host related infrastructure, particularly those in rail export corridors. This research presents a first-of-its kind, cross-regional comparative analysis of community risks, risk perceptions, energy and environmental attitudes, and related discourses in oil train export corridor communities. The mixed-methods design uses household-level survey data (N=571), interview data (N=58), and news media content analysis data (N=149), to address three key knowledge gaps regarding impacts of and attitudes toward crude oil by rail in examining: 1) the influences and distributions of support, opposition, and increased concern to oil by rail; 2) views toward hydrocarbon exports as well as broader energy preferences; and 3) dominant news media and stakeholder discourses and discursive channels concerning oil train activity. Results and related recommendations include the identification of community risk perceptions, vulnerabilities, and broader energy and export attitudes as well as predictors of their variation; discussion of implications for related community energy siting and planning, news media reporting, and communications; and the contribution of novel baseline data vis-a-vis predictors of risk perception and opposition concerning oil train activity and infrastructure to the risk perception and energy impacts fields.

Master of Science (M.S.), University of Dayton, 2017, Mechanical Engineering

The ability to forecast demand for large facilities will be increasingly important as real-time power pricing scenarios become increasingly present. Accurate prediction will inform data-driven power shedding to reduce energy costs most effectively with minimal sacrifice of comfort. A number of previous researchers have researched this topic, achieving results with varying amount of success. This study looks to forecast demand for a university complex of buildings, subject to the unique occupancy variation of such institutions. Specifically addressed is the use of academic institutional data associated with temporal enrollment and the academic calendar. As well, it addresses use of demand data in all buildings in an effort to more accurately predict this aggregate demand of the university. A data mining based approach based upon a Random Forest regression tree algorithm is used to develop the forecast model. The mean absolute percentage error (MAPE) value associated with the model applied to a validation set of data is on the order of 2.21 % based upon actual weather data. Using forecasted weather data, the MAPE increases to approximately 6.65 % in predicted day-ahead demand.

Master of Science, The Ohio State University, 2015, Allied Medical Professions

The female athlete triad and the recent introduction of the relative energy deficiency in sports (REDS) classifications define the negative consequences of the relationship between energy availability and overall physical health in athletes. The current triad paradigm considers the spectrum of energy availability of the athlete that can range between appropriate exercise with adequate fueling to more extreme weight loss methods such as restriction and over-exercising that may be associated with low energy availability (LEA) or a formal eating disorder. Eating disorders are typically characterized by restriction in dietary intake affecting total calories, macronutrients, and micronutrients consumed. In order to determine the diet composition, diet records and food frequency questionnaires are the two most common recording methods. However, their reliability and ability to be replicated in the female athlete population remains unclear. Furthermore, the macronutrient distribution of the female athlete's diet has been given little attention to establish if this distribution plays a role in the presence of LEA and skews total energy intake found in diet records. This study assessed the validity and reliability of diet records compared with an on-line food frequency questionnaire in recreational female runners. The two dietary tools used, three day food record analyzed by ESHA food processor and Vioscreen FFQ, produced similar intakes for calories, protein, and fat with correlations of .500, .59, .366, and .468 respectively, but ESHA consistently estimated calories and macronutrients higher compared to Vioscreen. In describing macronutrient contribution to the difference between the two tools, fat contributed 71.1% of the variability to the difference in caloric intake with carbohydrate contributing 22.1% and protein 2.1%. The macronutrient distribution from these two tools was then compared to current guidelines and assessed within the LEA framework. Of the (open full item for complete abstract)

BA, Oberlin College, 2013, Environmental Studies

This paper looks into the challenges to and opportunities in enabling residential energy efficiency, with a focus on Oberlin, OH. After laying out a basic framework, the paper has three main sections. First, it reviews and discusses financial barriers to residential energy. Next, it discusses social and psychological barriers, and discusses the Energy Advocate program that has successfully addressed these barriers. Finally, it discusses the physical barriers of old housing stock. It recommends developing a home repair cooperative to address the physical barriers to energy efficiency.

Master of Arts, The Ohio State University, 2010, East Asian Languages and Literatures

This thesis focuses on China's wind energy development, focusing on data pertaining to effects of wind energy development on economic, environmental, and social issues. It also reviews the Chinese government's Wind Energy development policy, laws that encourage the development of wind energy, as well as wind energy development problems and future development plans. I will also address current trends in China's wind energy development, as well as present the results of my field research.

Master of Science (MS), Ohio University, 2008, Mechanical Engineering (Engineering and Technology)

The use of alternative fuels addresses the issues of: reducing dependence on unstable petroleum supplies, reducing harmful emissions, and using renewable energy sources. This thesis focuses on a comparative energy balance on a four cylinder turbocharged diesel engine operating on diesel and biodiesel fuels. Steady-state tests were run to experimentally determine how input energy in the form of fuel was appropriated throughout the engine. The transfer of energy was measured for losses to the engine coolant and exhaust, usable power output, as well as minor and unaccounted losses. The results showed that input energy from biodiesel was distributed 37.4%, 31.1%, and 29.6% to the major areas of coolant, exhaust, and power output, respectively. Similarly the input energy from diesel was distributed 37.5%, 31.4%, and 29.2% to the major areas of coolant, exhaust, and power output, respectively. It was concluded from an uncertainty analysis that there was not a statistically significant difference in these results. Future improvements to obtain distinguishable results are outlined.

Doctor of Engineering, Cleveland State University, 2008, Fenn College of Engineering

We study the feasibility of a novel hybrid solar-wind hybrid system that shares most of its infrastructure and components. During periods of clear sunny days the system will generate electricity from the sun using a parabolic concentrator. The concentrator is formed by individual mirror elements and focuses the light onto high intensity vertical multi-junction (VMJ) cells. During periods of high wind speeds and at night, the same concentrator setup will be reconfigured to channel the wind into a wind turbine which will be used to harness wind energy. In this study we report on the feasibility of this type of solar/wind hybrid energy system. The key mechanisms; optics, cooling mechanism of VMJ cells and air flow through the system were investigated using simulation tools. The results from these simulations, along with a simple economic analysis giving the levelized cost of energy for such a system are presented. An iterative method of design refinement based on the simulation results was used to work towards a prototype design. T he levelized cost of the system achieved in the economic analysis shows the system to be a good alternative for a grid isolated site and could be used as a standalone system in regions of lower demand. The new approach to solar wind hybrid system reported herein will pave way for newer generation of hybrid systems that share common infrastructure in addition to the storage and distribution of energy.

Doctor of Philosophy, Case Western Reserve University, 2024, Management

In a world grappling with energy poverty, Africa, especially sub-Saharan Africa, faces profound challenges marked by extreme disparities in energy access. Study 1 advocates for the integration of environmental, social, and governance (ESG) principles as a linchpin for alleviating energy poverty by enhancing reliability and affordability and catalyzing low greenhouse gas (GHG) emissions. It emphasizes the urgent need for a shared language among diverse stakeholders to pursue sustainable energy solutions. Study 2 introduces "coopetition" as a groundbreaking strategy across 54 African nations, combining cooperation and competition to drive energy access while reducing greenhouse gas emissions. Challenging prevailing assumptions about the direct influence of financial development through official development assistance and foreign direct investment, the study highlights the pivotal role of transparent regulations and risk mitigation in fostering sustainable energy solutions. Study 3 further explores the interplay of coopetition and climate policy, introducing a model encompassing the Sustainable Development Index, GDP Growth Rate, and Corruption Perception Index. Coopetition emerges as an independent variable, moderated by climate policy, revealing a nuanced understanding of collaborative efforts' impact on energy poverty and emissions. The tripartite exploration underscores the call for a harmonious symphony of ESG principles, coopetition strategies, and tailored collaborations to illuminate the path toward a sustainable and equitable energy future for Africa.

Master of Science in Renewable and Clean Energy Engineering (MSRCE), Wright State University, 2023, Renewable and Clean Energy

In the past several years, the energy sector has experienced a rapid increase in renewable energy installations due to declining capital costs for wind turbines, solar panels, and batteries. Wind and solar electricity generation are intermittent in nature which must be considered in an economic analysis if a fair comparison is to be made between electricity supplied from renewables and electricity purchased from the grid. Energy storage reduces curtailment of wind and solar and minimizes electricity purchases from the grid by storing excess electricity and deploying the energy at times when demand exceeds the renewable energy supply. The objective of this work is to study the generation of electric power with wind turbines and solar panels coupled to either battery energy storage or hydrogen energy storage. So that logical conclusions can be drawn on the economic effectiveness of battery and hydrogen energy storage, four scenarios are analyzed: 1) purchasing all required electricity from the grid, 2) generating electricity with a combined wind and solar farm without energy storage, 3) generating electricity with a combined wind and solar farm with battery energy storage, and 4) generating electricity with a combined wind and solar farm with hydrogen energy storage. All four of these scenarios purchase electricity from the grid to meet demand that is not met by the renewable energy power plant. All scenarios are compared based on the lowest net present cost of supplying the specified electrical loads to serve 25,000 homes in Rio Vista, California over 25 years of operation. The detailed economics and electric power production of both wind and solar combined with energy storage for any size of wind facility, solar facility, battery facility, and hydrogen facility are analyzed with a MATLAB computer program developed for this work. The program contains technical and economic models of each of these systems working in different combinations. Current equipment c (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Electrical and Computer Engineering

Due to the increased penetration of inverter-based resources (IBRs) in bulk power system (BPS) networks, to conduct interconnection studies, generic dynamic mod- els of the second-generation renewable energy system models were developed by the Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force. The dynamic models have been extensively implemented in various power system simulation software packages, and the block diagram representation of the dynamic models is widely present in various technical reports and literature. However, there is a gap between the mathematical model and knowledge of key parameters for the second-generation renewable energy system dynamic models. The complex nonlinear nature of the dynamic models makes it highly challenging for the transmission planning engineers to identify the key parameters when the IBRs are subjected to large-scale voltage and frequency disturbances. This is needed to ensure grid stability under contingencies. For instance, the Type 3 wind turbine generator (WTG-3) model consists of 7 modules with 118 user-defined parameters, interfaced through 26 states and 9 control flags to facilitate the plant operation in different control modes. Thus, this work presents a methodology for the key parameter identification in non- linear models of power systems. The proposed methodology is applied to identify the key parameters of the transmission-scale IBRs (solar PV power plants, wind power plants, and battery energy storage system plants) dynamic models using proposed global sensitivity analysis techniques. It fills up the gap regarding the requirement of the mathematical model and knowledge of key parameters. In contrast to the state-of-the-art methods, the proposed modified Morris, modified Sobol', and modified eFAST sensitivity analysis techniques do not linearize the dynamic models of IBRs around an operating point, providing critical insights into the large-signal stability analysis. The (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Chemistry

Increasing concerns about carbon emissions has led to the global adoption of renewable energy initiatives. Direct integration of renewable energy sources, however, is difficult because of the intermittency of such sources. Furthermore, direct integration would overload the grid and lead to blackouts. Thus, grid-scale electrical energy storage is required to store and provide energy on-demand. Redox flow batteries have attracted attention as a scalable, inexpensive storage technology. Flow batteries store energy in solvated, redox-active electrolytes, as opposed to conductive, solid materials. These solutions are stored in separated reservoirs and are flowed to the electrochemical cell to cycle the redox-active compound. Energy stored in this fashion decouples energy and power, which allow for increased operational control. While many electrolytes exist, few electrolyte examples have achieved commercialization because of low solubility and low cell voltage. Redox-targeting flow batteries have emerged as an improvement to classic flow technology. Rather than storing energy in solution, redox -targeting flow batteries store energy in an insoluble solid while a solubilized electrolyte serves to shuttle electrons from the electrochemical cell to the solid. This strategy serves to combine the high energy density of solid-state batteries and scalability of flow batteries. Current redox targeting technology is mainly limited to the use of inorganic solid materials. These materials are cycle by an intercalation mechanism, which requires low current densities that lead to long cycle times. Furthermore, pairing shuttles with these materials are difficult because of distinct redox potentials and electron transfer rates of these solids. Our efforts focused on the development of an all-organic redox targeting flow battery. Organic materials generally do not operate based on intercalation mechanisms and the synthetic flexibility of organic compounds allow for the fin (open full item for complete abstract)

Master of Science (MS), Ohio University, 2021, Geography (Arts and Sciences)

Issues of greenhouse gas emissions and climate change are shaping the energy policies of various nations. Embracing low carbon technologies whiles incrementally reducing dependence on fossil fuel technologies seems to be the world's direction on energy at the moment. This study investigates how the energy policy of Ohio is promoting, if at all, this larger transition away from fossil fuels. The study made use of both primary and secondary data. The primary data was generated from responses through a semi-structured interview protocol from experienced professionals working within and outside the energy industry of Ohio. Secondary data was gotten from published academic and journalistic articles and then the use of document analysis was used to analyze them. There was a combined use of both textual and content analysis on secondary data obtained for this research. The study revealed that even though Ohio has a good ranking on its net metering policy, a holistic view of the energy policy thwarts Renewable Energy development. As it stands, the Renewable Wind Industry is stalled in development due to current policies. Also, various attempts by the legislature to introduce bills that do not promote renewables scare would-be investors. Ohio's current energy policy favors fossil fuels and nuclear plants. Lastly, stakeholders with an interest in Renewable Energy development have insufficient power to see it through the Ohio legislature. In light of this, the study proposes the way forward for a smooth transition from fossil fuel plants to renewables by calling for federal intervention in setting standards and providing the way forward for the cleaning of the electricity grid of Ohio.

Doctor of Philosophy (Ph.D.), University of Dayton, 2019, Electrical and Computer Engineering

Electric power grids are currently undergoing a major transition from large centralized power stations to distributed generation in which small and flexible facilities produce power closer to where it is needed. This move towards a decentralized delivery of energy is driven by a combination of economic, technological and environmental factors. In recent years, the cost of renewable energy in the form wind turbines and solar PV has dropped dramatically due to advances in manufacturing and material science, leading to their rapid deployment across the US. To supplement the intermittent nature of wind and solar energy, there is a growing need for small, highly controllable sources such as natural gas turbines. With the fracking boom in the US, there is currently abundant natural gas to use for this purpose. The resulting proliferation of many small energy producers creates technical problems such as voltage and frequency control that can be addressed with battery storage, whose cost is also dropping. These factors are leading to a move away from large energy production facilities that require too much initial investment. Also, a distributed supply is more efficient and reliable. The threat of global climate change is creating pressure to increase the integration of distributed generation and information technology is now capable of managing a greater number of energy producers, utilizing a vast supply of information to predict supplies and demand and to determine optimal dispatching of energy. The move towards a higher percentage of renewable energy creates many interesting technical issues, many of which are due to the lack of control over the renewable resources. Energy dispatching between multiple sources, some controllable and some not, and multiple loads leads to a need for dispatching strategies that maximize the percentage of the load that is met with renewable energy. A growing aspect of this energy dispatch is a stream of information about energy demand, w (open full item for complete abstract)

MS, University of Cincinnati, 2019, Engineering and Applied Science: Civil Engineering

The objectives of this thesis are to 1) Determine the extent to which commonly used building energy benchmarking metrics are correlated and 2) Establish if the added alternative metrics are valuable to the benchmarking scenario. If a high degree of correlation exists, then building performance under each metric would be similar and no new information is provided i.e. metrics are redundant. In this study, the results of dimension reduction analysis on commonly used building energy benchmarking metrics are examined. The thesis objective will be accomplished by applying a principal component analysis and factor analysis to a large database of buildings. The results of the analysis suggest that the most commonly used benchmarking metrics are correlated. Twelve selected metrics are reduced to three distinct factors, which are uncorrelated with each other. The first factor was related to the total energy consumption, the second factor was related to electricity, and the third factor was related to natural gas. Energy use intensity (EUI) and ENERGY STAR scores were captured together by the total energy consumption related factor. This implied that these vastly used metrics were redundant. The nine other metrics were loaded with the remaining two electricity and natural gas related factors and not the EUI and scores. It indicated that they are necessary for explaining the dataset and should be captured in the benchmarking discipline. New targets based on fuel types and end-uses are required for the complete building performance picture.

MS, University of Cincinnati, 2019, Engineering and Applied Science: Civil Engineering

Buildings account for almost 75% of total electricity consumption and nearly 40% of CO2 emissions in the US. Improving the energy-efficiency of buildings is one of the most effective and affordable ways to decrease greenhouse gas emissions on a large scale. Thus, Energy Modelling Software (EMS) are required to analyze a building for its energy use. These software are designed to evaluate energy performance of buildings during design phase, and not for buildings that already exist. For existing buildings, any attempt to evaluate energy-efficiency strategies should begin by understanding how it currently consumes energy by constructing its model in the software. The goal of this research is to better understand how Existing University Buildings (EUB)s use energy, to determine what factors impact the energy consumption and how changes in these factors affect its energy consumption. It also evaluates potential use of existing energy modelling software for simulating energy consumption of an existing building and provides recommendation on how to improve simulation results and reduce energy consumption. The methodology included analyzing architectural and HVAC equipment details of an existing building at University of Cincinnati, modeling the building in an EMS (eQUEST), comparing its utility consumption to actual data provided by the university, and performing a sensitivity analysis to determine factors affecting energy consumption. Recommendations on how to improve the energy simulation results and reduce the building's energy consumption were then developed.