Matching Items (8)
Filtering by
- All Subjects: Renewable Energy
- Creators: Phelan, Patrick
- Member of: ASU Electronic Theses and Dissertations
Description
An eco-industrial park (EIP) is an industrial ecosystem in which a group of co-located firms are involved in collective resource optimization with each other and with the local community through physical exchanges of energy, water, materials, byproducts and services - referenced in the industrial ecology literature as "industrial symbiosis". EIPs, when compared with standard industrial resource sharing networks, prove to be of greater public advantage as they offer improved environmental and economic benefits, and higher operational efficiencies both upstream and downstream in their supply chain.
Although there have been many attempts to adapt EIP methodology to existing industrial sharing networks, most of them have failed for various factors: geographic restrictions by governmental organizations on use of technology, cost of technology, the inability of industries to effectively communicate their upstream and downstream resource usage, and to diminishing natural resources such as water, land and non-renewable energy (NRE) sources for energy production.
This paper presents a feasibility study conducted to evaluate the comparative environmental, economic, and geographic impacts arising from the use of renewable energy (RE) and NRE to power EIPs. Life Cycle Assessment (LCA) methodology, which is used in a variety of sectors to evaluate the environmental merits and demerits of different kinds of products and processes, was employed for comparison between these two energy production methods based on factors such as greenhouse gas emission, acidification potential, eutrophication potential, human toxicity potential, fresh water usage and land usage. To complement the environmental LCA analysis, levelized cost of electricity was used to evaluate the economic impact. This model was analyzed for two different geographic locations; United States and Europe, for 12 different energy production technologies.
The outcome of this study points out the environmental, economic and geographic superiority of one energy source over the other, including the total carbon dioxide equivalent emissions, which can then be related to the total number of carbon credits that can be earned or used to mitigate the overall carbon emission and move closer towards a net zero carbon footprint goal thus making the EIPs truly sustainable.
Although there have been many attempts to adapt EIP methodology to existing industrial sharing networks, most of them have failed for various factors: geographic restrictions by governmental organizations on use of technology, cost of technology, the inability of industries to effectively communicate their upstream and downstream resource usage, and to diminishing natural resources such as water, land and non-renewable energy (NRE) sources for energy production.
This paper presents a feasibility study conducted to evaluate the comparative environmental, economic, and geographic impacts arising from the use of renewable energy (RE) and NRE to power EIPs. Life Cycle Assessment (LCA) methodology, which is used in a variety of sectors to evaluate the environmental merits and demerits of different kinds of products and processes, was employed for comparison between these two energy production methods based on factors such as greenhouse gas emission, acidification potential, eutrophication potential, human toxicity potential, fresh water usage and land usage. To complement the environmental LCA analysis, levelized cost of electricity was used to evaluate the economic impact. This model was analyzed for two different geographic locations; United States and Europe, for 12 different energy production technologies.
The outcome of this study points out the environmental, economic and geographic superiority of one energy source over the other, including the total carbon dioxide equivalent emissions, which can then be related to the total number of carbon credits that can be earned or used to mitigate the overall carbon emission and move closer towards a net zero carbon footprint goal thus making the EIPs truly sustainable.
ContributorsGupta, Vaibhav (Author) / Calhoun, Ronald J (Thesis advisor) / Dooley, Kevin (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2014
Description
A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and their respective temperatures established simultaneously. Polystyrene and silica nanoparticles are synthesized with a variety of temperature-sensitive dyes such as BODIPY, rose Bengal, Rhodamine dyes 6G, 700, and 800, and Nile Blue A and Nile Red. Photographs are taken with a QImaging QM1 Questar EXi Retiga camera while particles are heated from 25 to 70 C and excited at 532 nm with a Coherent DPSS-532 laser. Photographs are converted to intensity images in MATLAB and analyzed for fluorescence intensity, and plots are generated in MATLAB to describe each dye's intensity vs temperature. Regression curves are created to describe change in fluorescence intensity over temperature. Dyes are compared as nanoparticle core material is varied. Large particles are also created to match the camera's optical resolution capabilities, and it is established that intensity values increase proportionally with nanoparticle size. Nile Red yielded the closest-fit model, with R2 values greater than 0.99 for a second-order polynomial fit. By contrast, Rhodamine 6G only yielded an R2 value of 0.88 for a third-order polynomial fit, making it the least reliable dye for temperature measurements using the polynomial model. Of particular interest in this work is Nile Blue A, whose fluorescence-temperature curve yielded a much different shape from the other dyes. It is recommended that future work describe a broader range of dyes and nanoparticle sizes, and use multiple excitation wavelengths to better quantify each dye's quantum efficiency. Further research into the effects of nanoparticle size on fluorescence intensity levels should be considered as the particles used here greatly exceed 2 ìm. In addition, Nile Blue A should be further investigated as to why its fluorescence-temperature curve did not take on a characteristic shape for a temperature-sensitive dye in these experiments.
ContributorsTomforde, Christine (Author) / Phelan, Patrick (Thesis advisor) / Dai, Lenore (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
Description
This is a two-part thesis.
Part 1 of this thesis investigates the influence of spatial temperature distribution on the accuracy of performance data of photovoltaic (PV) modules in outdoor conditions and provides physical approaches to improve the spatial temperature distribution of the test modules so an accurate performance data can be obtained in the field. Conventionally, during outdoor performance testing, a single thermocouple location is used on the backsheet or back glass of a test module. This study clearly indicates that there is a large spatial temperature difference between various thermocouple locations within a module. Two physical approaches or configurations were experimented to improve the spatial temperature uniformity: thermally insulating the inner and outer surface of the frame; backsheet and inner surface of the frame. All the data were compared with un-insulated conventional configuration. This study was performed in an array setup of six modules under two different preconditioning electrical configurations, Voc and MPPT over several clear sunny days. This investigation concludes that the best temperature uniformity and the most accurate I-V data can be obtained only by thermally insulating the inner and outer frame surfaces or by using the average of four thermocouple temperatures, as specified in IEC 61853-2, without any thermal insulation.
Part 2 of this thesis analyzes the field data obtained from old PV power plants using various statistical techniques to identify the most influential degradation modes on fielded PV modules in two different climates: hot-dry (Arizona); cold-dry (New York). Performance data and visual inspection data of 647 modules fielded in five different power plants were analyzed. Statistical tests including hypothesis testing were carried out to identify the I-V parameter(s) that are affected the most. The affected performance parameters (Isc, Voc, FF and Pmax) were then correlated with the defects to determine the most dominant defect affecting power degradation. Analysis indicates that the cell interconnect discoloration (or solder bond deterioration) is the dominant defect in hot-dry climate leading to series resistance increase and power loss, while encapsulant delamination is being the most dominant defect in cold-dry climate leading to cell mismatch and power loss.
Part 1 of this thesis investigates the influence of spatial temperature distribution on the accuracy of performance data of photovoltaic (PV) modules in outdoor conditions and provides physical approaches to improve the spatial temperature distribution of the test modules so an accurate performance data can be obtained in the field. Conventionally, during outdoor performance testing, a single thermocouple location is used on the backsheet or back glass of a test module. This study clearly indicates that there is a large spatial temperature difference between various thermocouple locations within a module. Two physical approaches or configurations were experimented to improve the spatial temperature uniformity: thermally insulating the inner and outer surface of the frame; backsheet and inner surface of the frame. All the data were compared with un-insulated conventional configuration. This study was performed in an array setup of six modules under two different preconditioning electrical configurations, Voc and MPPT over several clear sunny days. This investigation concludes that the best temperature uniformity and the most accurate I-V data can be obtained only by thermally insulating the inner and outer frame surfaces or by using the average of four thermocouple temperatures, as specified in IEC 61853-2, without any thermal insulation.
Part 2 of this thesis analyzes the field data obtained from old PV power plants using various statistical techniques to identify the most influential degradation modes on fielded PV modules in two different climates: hot-dry (Arizona); cold-dry (New York). Performance data and visual inspection data of 647 modules fielded in five different power plants were analyzed. Statistical tests including hypothesis testing were carried out to identify the I-V parameter(s) that are affected the most. The affected performance parameters (Isc, Voc, FF and Pmax) were then correlated with the defects to determine the most dominant defect affecting power degradation. Analysis indicates that the cell interconnect discoloration (or solder bond deterioration) is the dominant defect in hot-dry climate leading to series resistance increase and power loss, while encapsulant delamination is being the most dominant defect in cold-dry climate leading to cell mismatch and power loss.
ContributorsUmachandran, Neelesh (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Wang, Liping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2015
Description
The operating temperature of photovoltaic (PV) modules is affected by external factors such as irradiance, wind speed and ambient temperature as well as internal factors like material properties and design properties. These factors can make a difference in the operating temperatures between cells within a module and between modules within a plant. This is a three-part thesis.
Part 1 investigates the behavior of temperature distribution of PV cells within a module through outdoor temperature monitoring under various operating conditions (Pmax, Voc and Isc) and examines deviation in the temperature coefficient values pertaining to this temperature variation. ANOVA, a statistical tool, was used to study the influence of various factors on temperature variation. This study also investigated the thermal non-uniformity affecting I-V parameters and performance of four different PV technologies (crystalline silicon, CdTe, CIGS, a-Si). Two new approaches (black-colored frame and aluminum tape on back-sheet) were implemented in addition to the two previously-used approaches (thermally insulating the frame, and frame and back sheet) to study temperature uniformity improvements within c-Si PV modules on a fixed latitude-tilt array. This thesis concludes that frame thermal insulation and black frame help reducing thermal gradients and next best viable option to improve temperature uniformity measurements is by using average of four thermocouples as per IEC 61853-2 standard.
Part 2 analyzes the temperature data for two power plants (fixed-tilt and one-axis) to study the temperature variation across the cells in a module and across the modules in a power plant. The module placed in the center of one-axis power plant had higher temperature, whereas in fixed-tilt power plant, the module in north-west direction had higher temperatures. Higher average operating temperatures were observed in one-axis tracking as compared to the fixed-tilt PV power plant, thereby expected to lowering their lifetime.
Part 3 focuses on determination of a thermal model coefficients, using parameters similar to Uc and Uv thermal loss factors used in PVsyst, for modules of four different PV technologies experiencing hot-desert climate conditions by statistically correlating a year-long monitored data. Thermal models help to effectively quantity factors influencing module temperatures to estimate performance and energy models.
Part 1 investigates the behavior of temperature distribution of PV cells within a module through outdoor temperature monitoring under various operating conditions (Pmax, Voc and Isc) and examines deviation in the temperature coefficient values pertaining to this temperature variation. ANOVA, a statistical tool, was used to study the influence of various factors on temperature variation. This study also investigated the thermal non-uniformity affecting I-V parameters and performance of four different PV technologies (crystalline silicon, CdTe, CIGS, a-Si). Two new approaches (black-colored frame and aluminum tape on back-sheet) were implemented in addition to the two previously-used approaches (thermally insulating the frame, and frame and back sheet) to study temperature uniformity improvements within c-Si PV modules on a fixed latitude-tilt array. This thesis concludes that frame thermal insulation and black frame help reducing thermal gradients and next best viable option to improve temperature uniformity measurements is by using average of four thermocouples as per IEC 61853-2 standard.
Part 2 analyzes the temperature data for two power plants (fixed-tilt and one-axis) to study the temperature variation across the cells in a module and across the modules in a power plant. The module placed in the center of one-axis power plant had higher temperature, whereas in fixed-tilt power plant, the module in north-west direction had higher temperatures. Higher average operating temperatures were observed in one-axis tracking as compared to the fixed-tilt PV power plant, thereby expected to lowering their lifetime.
Part 3 focuses on determination of a thermal model coefficients, using parameters similar to Uc and Uv thermal loss factors used in PVsyst, for modules of four different PV technologies experiencing hot-desert climate conditions by statistically correlating a year-long monitored data. Thermal models help to effectively quantity factors influencing module temperatures to estimate performance and energy models.
ContributorsPavgi, Ashwini (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2016
Description
Solar photovoltaic (PV) industry is tipped to be one of the front-runners in the renewable industry. Typically, PV module manufacturers provide a linear or step warranty of 80% of original power over 25 years. This power loss during the field exposure is primarily attributed to the development of performance affecting defects in the PV modules. As many as 86 different defects can occur in a PV module. One of the major defects that can cause significant power loss is the interconnect metallization system (IMS) degradation which is the focus of this thesis. The IMS is composed of cell-interconnect (cell-ribbon interconnect) and string-interconnect (ribbon-ribbon interconnect). The cell interconnect is in turn composed of silver metallization (fingers and busbars) and solder bonds between silver busbar and copper ribbon. Weak solder bonding between copper ribbon and busbar of a cell results in increase of series resistance that in turn affects the fill factor causing a power drop. In this thesis work, the results obtained from various non-destructive and destructive experiments performed on modules exposed in three different climates (Arizona - Hot and Dry, Mexico - Warm and Humid, and California - Temperate) are presented. These experiments include light I-V measurements, dark I-V measurements, infrared imaging, extraction of test samples from the modules, peel strength measurements and four-point resistance measurements. The extraction of test samples was performed using a mechanical method and a chemical method. The merits and demerits of these two methods are presented. A drop of 10.33% in fill factor was observed for a 0.05Ω increase in the series resistance of the modules investigated in this work. Different combinations in a cell that can cause series resistance increase were considered and their effect on fill factor were observed using four-point probe experiments. Peel test experiments were conducted to correlate the effect of series resistance on the ribbon peel strength. Finally, climate specific thermal modelling was performed for 4 different sites over 20 years in order to calculate the accumulated thermal fatigue and also to evaluate its correlation, if any, with the increase of series resistance.
ContributorsTummala, Abhishiktha (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2016
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 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