Matching Items (5)
Filtering by
- All Subjects: Renewable Energy
- Genre: Academic theses
- Creators: Phelan, Patrick
- Creators: Rittmann, Bruce E.
- Member of: Theses and Dissertations
- Resource Type: Text
Description
Many expect renewable energy technologies to play a leading role in a sustainable energy supply system and to aid the shift away from an over-reliance on traditional hydrocarbon resources in the next few decades. This dissertation develops environmental, policy and social models to help understand various aspects of photovoltaic (PV) technologies. The first part of this dissertation advances the life cycle assessment (LCA) of PV systems by expanding the boundary of included processes using hybrid LCA and accounting for the technology-driven dynamics of environmental impacts. Hybrid LCA extends the traditional method combining bottom-up process-sum and top-down economic input-output (EIO) approaches. The embodied energy and carbon of multi-crystalline silicon photovoltaic systems are assessed using hybrid LCA. From 2001 to 2010, the embodied energy and carbon fell substantially, indicating that technological progress is realizing reductions in environmental impacts in addition to lower module price. A variety of policies support renewable energy adoption, and it is critical to make them function cooperatively. To reveal the interrelationships among these policies, the second part of this dissertation proposes three tiers of policy architecture. This study develops a model to determine the specific subsidies required to support a Renewable Portfolio Standard (RPS) goal. The financial requirements are calculated (in two scenarios) and compared with predictable funds from public sources. A main result is that the expected investments to achieve the RPS goal far exceed the economic allocation for subsidy of distributed PV. Even with subsidies there are often challenges with social acceptance. The third part of this dissertation originally develops a fuzzy logic inference model to relate consumers' attitudes about the technology such as perceived cost, maintenance, and environmental concern to their adoption intention. Fuzzy logic inference model is a type of soft computing models. It has the advantage of dealing with imprecise and insufficient information and mimicking reasoning processes of human brains. This model is implemented in a case study of residential PV adoption using data through a survey of homeowners in Arizona. The output of this model is the purchasing probability of PV.
ContributorsZhai, Pei (Author) / Williams, Eric D. (Thesis advisor) / Allenby, Braden (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2010
Description
Concentrating solar thermal power systems gained a wide interest for a long time to serve as a renewable and sustainable alternate source of energy. While the optimization and modification are ongoing, focused generally on solar power systems to provide solar-electrical energy or solar-thermal energy, the production process of Ordinary Portland Cement (OPC) has not changed over the past century. A linear refractive Fresnel lens application in cement production process is investigated in this research to provide the thermal power required to raise the temperature of lime up to 623 K (350C) with zero carbon emissions for stage two in a new proposed two-stage production process. The location is considered to be Phoenix, Arizona, with a linear refractive Fresnel lens facing south, tilted 33.45 equaling the location latitude, and concentrating solar beam radiation on an evacuated tube collector with tracking system continuously rotating about the north-south axis. The mathematical analysis showed promising results based on averaged monthly values representing an average hourly useful thermal power and receiver temperature during day-light hours for each month throughout the year. The maximum average hourly useful thermal power throughout the year was obtained for June as 33 kWth m-2 with a maximum receiver temperature achieved of 786 K (513C), and the minimum useful thermal power obtained during the month of December with 27 kWth m-2 and a minimum receiver temperature of 701 K (428C).
ContributorsAlkhuwaiteem, Mohammad (Author) / Phelan, Patrick (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Neithalath, Narayanan (Committee member) / Arizona State University (Publisher)
Created2021
Description
The finite supply of current energy production materials has created opportunities for the investigation of alternative energy sources in many fields. One example is the use of microorganisms in bioenergy applications, such as microbial fuel cells. Present in many types of environments, microorganisms with the ability to respire solid electron acceptors have become of increasing relevance to alternative energy and wastewater treatment research. In this dissertation, several aspects of anode respiration are investigated, with the goal of increasing the limited understanding of the mechanisms of electron transport through the use of advanced electrochemical methods. Biofilms of Geobacter sulfurreducens, the model anode respiring organism, as well as its alkaliphilic relative, Geoalkalibacter ferrihydriticus, were investigated using chronoamperometry, electrochemical impedance spectroscopy, and cyclic voltammetry.
In G. sulfurreducens, two distinct pathways of electron transport were observed through the application of advanced electrochemical techniques on anode biofilms in microbial electrochemical cells. These pathways were found to be preferentially expressed, based on the poised anode potential (redox potential) of the electrode. In Glk. ferrihydriticus, four pathways for electron transport were found, showing an even greater diversity in electron transport pathway utilization as compared to G. sulfurreducens. These observations provide insights into the diversity of electron transport pathways present in anode-respiring bacteria and introduce the necessity of further characterization for pathway identification.
Essential to science today, communication of pressing scientific issues to the lay audience may present certain difficulties. This can be seen especially with the topics that are considered socio-scientific issues, those considered controversial in society but not for scientists. This dissertation explores the presentation of alternative and renewable energy technologies and climate change in undergraduate education. In introductory-level Biology, Chemistry, and Physics textbooks, the content and terminology presented were analyzed for individual textbooks and used to evaluate discipline-based trends. Additional extensions were made between teaching climate change with the active learning technique of citizen science using past research gains from studies of evolution. These observations reveal patterns in textbook content for energy technologies and climate change, as well as exploring new aspects of teaching techniques.
In G. sulfurreducens, two distinct pathways of electron transport were observed through the application of advanced electrochemical techniques on anode biofilms in microbial electrochemical cells. These pathways were found to be preferentially expressed, based on the poised anode potential (redox potential) of the electrode. In Glk. ferrihydriticus, four pathways for electron transport were found, showing an even greater diversity in electron transport pathway utilization as compared to G. sulfurreducens. These observations provide insights into the diversity of electron transport pathways present in anode-respiring bacteria and introduce the necessity of further characterization for pathway identification.
Essential to science today, communication of pressing scientific issues to the lay audience may present certain difficulties. This can be seen especially with the topics that are considered socio-scientific issues, those considered controversial in society but not for scientists. This dissertation explores the presentation of alternative and renewable energy technologies and climate change in undergraduate education. In introductory-level Biology, Chemistry, and Physics textbooks, the content and terminology presented were analyzed for individual textbooks and used to evaluate discipline-based trends. Additional extensions were made between teaching climate change with the active learning technique of citizen science using past research gains from studies of evolution. These observations reveal patterns in textbook content for energy technologies and climate change, as well as exploring new aspects of teaching techniques.
ContributorsYoho, Rachel Ann (Author) / Torres, César I (Thesis advisor) / Rittmann, Bruce E. (Committee member) / Popat, Sudeep C (Committee member) / Vanmali, Binaben H (Committee member) / Arizona State University (Publisher)
Created2016
Description
Microbial Electrochemical Cell (MXC) technology harnesses the power stored in wastewater by using anode respiring bacteria (ARB) as a biofilm catalyst to convert the energy stored in waste into hydrogen or electricity. ARB, or exoelectrogens, are able to convert the chemical energy stored in wastes into electrical energy by transporting electrons extracellularly and then transferring them to an electrode. If MXC technology is to be feasible for ‘real world’ applications, it is essential that diverse ARB are discovered and their unique physiologies elucidated- ones which are capable of consuming a broad spectrum of wastes from different contaminated water sources.
This dissertation examines the use of Gram-positive thermophilic (60 ◦C) ARB in MXCs since very little is known regarding the behavior of these microorganisms in this setting. Here, we begin with the draft sequence of the Thermincola ferriacetica genome and reveal the presence of 35 multiheme c-type cytochromes. In addition, we employ electrochemical techniques including cyclic voltammetry (CV) and chronoamperometry (CA) to gain insight into the presence of multiple pathways for extracellular electron transport (EET) and current production (j) limitations in T. ferriacetica biofilms.
Next, Thermoanaerobacter pseudethanolicus, a fermentative ARB, is investigated for its ability to ferment pentose and hexose sugars prior to using its fermentation products, including acetate and lactate, for current production in an MXC. Using CA, current production is tracked over time with the generation and consumption of fermentation products. Using CV, the midpoint potential (EKA) of the T. pseudethanolicus EET pathway is revealed.
Lastly, a cellulolytic microbial consortium was employed for the purpose ofassessing the feasibility of using thermophilic MXCs for the conversion of solid waste into current production. Here, a highly enriched consortium of bacteria, predominately from the Firmicutes phylum, is capable of generating current from solid cellulosic materials.
This dissertation examines the use of Gram-positive thermophilic (60 ◦C) ARB in MXCs since very little is known regarding the behavior of these microorganisms in this setting. Here, we begin with the draft sequence of the Thermincola ferriacetica genome and reveal the presence of 35 multiheme c-type cytochromes. In addition, we employ electrochemical techniques including cyclic voltammetry (CV) and chronoamperometry (CA) to gain insight into the presence of multiple pathways for extracellular electron transport (EET) and current production (j) limitations in T. ferriacetica biofilms.
Next, Thermoanaerobacter pseudethanolicus, a fermentative ARB, is investigated for its ability to ferment pentose and hexose sugars prior to using its fermentation products, including acetate and lactate, for current production in an MXC. Using CA, current production is tracked over time with the generation and consumption of fermentation products. Using CV, the midpoint potential (EKA) of the T. pseudethanolicus EET pathway is revealed.
Lastly, a cellulolytic microbial consortium was employed for the purpose ofassessing the feasibility of using thermophilic MXCs for the conversion of solid waste into current production. Here, a highly enriched consortium of bacteria, predominately from the Firmicutes phylum, is capable of generating current from solid cellulosic materials.
ContributorsLusk, Bradley (Author) / Torres, César I (Thesis advisor) / Rittmann, Bruce E. (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2015
Description
The operating temperature of photovoltaic (PV) modules has a strong impact on the expected performance of said modules in photovoltaic arrays. As the install capacity of PV arrays grows throughout the world, improved accuracy in modeling of the expected module temperature, particularly at finer time scales, requires improvements in the existing photovoltaic temperature models. This thesis work details the investigation, motivation, development, validation, and implementation of a transient photovoltaic module temperature model based on a weighted moving-average of steady-state temperature predictions.
This thesis work first details the literature review of steady-state and transient models that are commonly used by PV investigators in performance modeling. Attempts to develop models capable of accounting for the inherent transient thermal behavior of PV modules are shown to improve on the accuracy of the steady-state models while also significantly increasing the computational complexity and the number of input parameters needed to perform the model calculations.
The transient thermal model development presented in this thesis begins with an investigation of module thermal behavior performed through finite-element analysis (FEA) in a computer-aided design (CAD) software package. This FEA was used to discover trends in transient thermal behavior for a representative PV module in a timely manner. The FEA simulations were based on heat transfer principles and were validated against steady-state temperature model predictions. The dynamic thermal behavior of PV modules was determined to be exponential, with the shape of the exponential being dependent on the wind speed and mass per unit area of the module.
The results and subsequent discussion provided in this thesis link the thermal behavior observed in the FEA simulations to existing steady-state temperature models in order to create an exponential weighting function. This function can perform a weighted average of steady-state temperature predictions within 20 minutes of the time in question to generate a module temperature prediction that accounts for the inherent thermal mass of the module while requiring only simple input parameters. Validation of the modeling method presented here shows performance modeling accuracy improvement of 0.58%, or 1.45°C, over performance models relying on steady-state models at narrow data intervals.
This thesis work first details the literature review of steady-state and transient models that are commonly used by PV investigators in performance modeling. Attempts to develop models capable of accounting for the inherent transient thermal behavior of PV modules are shown to improve on the accuracy of the steady-state models while also significantly increasing the computational complexity and the number of input parameters needed to perform the model calculations.
The transient thermal model development presented in this thesis begins with an investigation of module thermal behavior performed through finite-element analysis (FEA) in a computer-aided design (CAD) software package. This FEA was used to discover trends in transient thermal behavior for a representative PV module in a timely manner. The FEA simulations were based on heat transfer principles and were validated against steady-state temperature model predictions. The dynamic thermal behavior of PV modules was determined to be exponential, with the shape of the exponential being dependent on the wind speed and mass per unit area of the module.
The results and subsequent discussion provided in this thesis link the thermal behavior observed in the FEA simulations to existing steady-state temperature models in order to create an exponential weighting function. This function can perform a weighted average of steady-state temperature predictions within 20 minutes of the time in question to generate a module temperature prediction that accounts for the inherent thermal mass of the module while requiring only simple input parameters. Validation of the modeling method presented here shows performance modeling accuracy improvement of 0.58%, or 1.45°C, over performance models relying on steady-state models at narrow data intervals.
ContributorsPrilliman, Matthew (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2020