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Description
Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.
ContributorsKrishnamurthy, Raghavendra (Author) / Calhoun, Ronald J (Thesis advisor) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Fraser, Matthew (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail V (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2013
Description
Shifting to renewable energy from fossil fuels is not occurring rapidly. Determining where to locate renewable power plants could help expedite development. The project discussed here uses a GIS ranking tool to determine potential locations for solar and wind power plants in Arizona. Criteria include renewable input (irradiance/wind class), topographic slope, and distance from transmission lines. These are ranked and summed to determine areas with the most potential. The resulting outputs show that there is much more potential land for solar development than wind development. Further analysis in this paper will focus solely on solar due to wind's lower potential. Land sensitivity and ownership are used to assess the feasibility of development. There are many groupings of highly ranked land across the state, but the largest stretch of land runs from outside of Marana (south-central Arizona) northwest to about 60 miles west of Wickenburg (central-west). This regions is mainly on BLM, state, and privately owned land. Some of this land is considered sensitive, but non-sensitive areas with high potential are frequent throughout. Renewable potential in other states could be determined using this tool as well. Variables could be weighted or added depending on each area's need.
ContributorsZeck, Kevin Michael (Author) / Fraser, Matthew (Thesis director) / Pasqualetti, Martin (Committee member) / Cowger, Lane (Committee member) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / School of Sustainability (Contributor)
Created2013-05
Description
Traditional infrastructure design approaches were born with industrialization. During this time the relatively stable environments allowed infrastructure systems to reliably provide service with networks designed to precise parameters and organizations fixated on maximizing efficiency. Now, infrastructure systems face the challenge of operating in the Anthropocene, an era of complexity. The environments in which infrastructure systems operate are changing more rapidly than the technologies and governance systems of infrastructure. Infrastructure systems will need to be resilient to navigate stability and instability and avoid obsolescence. This dissertation addresses how infrastructure systems could be designed for the Anthropocene, assessing technologies able to operate with uncertainty, rethinking the principles of technology design, and restructuring infrastructure governance. Resilience, in engineering, has often been defined as resistance to known disturbances with a focus on infrastructure assets. Resilience, more broadly reviewed, includes resistance, adaptation, and transformation across physical and governance domains. This dissertation constructs a foundation for resilient infrastructure through an assessment of resilience paradigms in engineering, complexity and deep uncertainty (Chapter 2), ecology (Chapter 3), and organizational change and leadership (Chapter 4). The second chapter reconciles frameworks of complexity and deep uncertainty to help infrastructure managers navigate the instability infrastructure systems face, with a focus on climate change. The third chapter identifies competencies of resilience in infrastructure theory and practice and compares those competencies with ‘Life’s Principles’ in ecology, presenting opportunities for growth and innovation in infrastructure resilience and highlighting the need for satisficed (to satisfy and suffice) solutions. The fourth chapter navigates pressures of exploitation and exploration that infrastructure institutions face during periods of stability and instability, proposing leadership capabilities to enhance institutional resilience. Finally, the dissertation is concluded with a chapter synthesizing the previous chapters, providing guidance for alternative design approaches for advancing resilient infrastructure. Combined, the work challenges the basic mental models used by engineers when approaching infrastructure design and recommends new ways of doing and thinking for the accelerating and increasingly uncertain conditions of the future.
ContributorsHelmrich, Alysha Marie (Author) / Chester, Mikhail V (Thesis advisor) / Grimm, Nancy B (Committee member) / Garcia, Margaret (Committee member) / Meerow, Sara (Committee member) / Arizona State University (Publisher)
Created2021
Description
Extreme weather events, such as hurricanes, continue to disrupt critical infrastructure like energy grids that provide lifeline services for urban systems, thus making resilience imperative for stakeholders, infrastructure managers, and community leaders to strategize in the face of 21st-century challenges. In Puerto Rico after Hurricane Maria, for example, the energy system took over nine months to recover in parts of the island, thousands of lives were lost, and livelihoods were severely impacted. Urban systems consist of interconnected human networks and physical infrastructure, and the subsequent complexity that is increasingly difficult to make sense of toward resilience enhancing efforts. While the resilience paradigm has continued to progress among and between several disciplinary fields, such as social science and engineering, an ongoing challenge is integrating social and technical approaches for resilience research. Misaligned or siloed perspectives can lead to misinformative and inadequate strategies that undercut inherent capacities or ultimately result in maladaptive infrastructure, social hardship, and sunken investments. This dissertation contributes toward integrating the social and technical resilience domains and transitioning established disaster resilience assessments into complexity perspectives by asking the overarching question: How can a multiplicity of resilience assessments be integrated by geographic and network mapping approaches to better capture the complexity of urban systems, using Hurricane Maria in Puerto Rico as a case study? The first chapter demonstrates how social metrics can be used in a socio-technical network modeling framework for a large-scale electrical system, presents a novel framing of social hardship due to disasters, and proposes a method for developing a social hardship metric using a treatment-effect approach. A second chapter presents a conceptual analysis of disaster resilience indicators from a complexity perspective and links socio-ecological systems resilience principles to tenets of complexity. A third chapter presents a novel methodology for integrating social complexity with performance-based metrics by leveraging distributed ethnographies and a thick mapping approach. Lastly, a concluding chapter synthesizes the previous chapters to discuss a broad framing for socio-technical resilience assessments, the role of space and place as anchors for multiple framings of a complex system, caveats given ongoing developments in Puerto Rico, and implications for collaborative resilience research.
ContributorsCarvalhaes, Thomaz (Author) / Chester, Mikhail V (Thesis advisor) / Reddy, Agami T (Thesis advisor) / Allenby, Braden R (Committee member) / Arizona State University (Publisher)
Created2021
Description
Infrastructure managers are continually challenged to reorient their organizations to mitigate disturbances. Disturbances to infrastructure constantly intensify, and the world and its intricate systems are becoming more connected and complex. This complexity often leads to disturbances and cascading failures. Some of these events unfold in extreme ways previously unimagined (i.e., Black Swan events). Infrastructure managers currently seek pathways through this complexity. To this end, reimagined – multifaceted – definitions of resilience must inform future decisions. Moreover, the hazardous environment of the Anthropocene demands flexibility and dynamic reprioritization of infrastructure and resources during disturbances. In this dissertation, the introduction will briefly explain foundational concepts, frameworks, and models that will inform the rest of this work. Chapter 2 investigates the concept of dynamic criticality: the skill to reprioritize amidst disturbances, repeating this process with each new disturbance. There is a dearth of insight requisite skillsets for infrastructure organizations to attain dynamic criticality. Therefore, this dissertation searches other industries and finds goals, structures, sensemaking, and strategic best practices to propose a contextualized framework for infrastructure. Chapters 3 and 4 seek insight into modeling infrastructure interdependencies and cascading failure to elucidate extreme outcomes such as Black Swans. Chapter 3 explores this concept through a theoretical analysis considering the use of realistic but fictional (i.e., synthetic) models to simulate interdependent behavior and cascading failures. This chapter also discusses potential uses of synthetic networks for infrastructure resilience research and barriers to future success. Chapter 4 tests the preceding theoretical analysis with an empirical study. Chapter 4 builds realistic networks with dependency between power and water models and simulates cascading failure. The discussion considers the future application of similar modeling efforts and how these techniques can help infrastructure managers scan the horizon for Black Swans. Finally, Chapter 5 concludes the dissertation with a synthesis of the findings from the previous chapters, discusses the boundaries and limitations, and proposes inspirations for future work.
ContributorsHoff, Ryan Michael (Author) / Chester, Mikhail V (Thesis advisor) / Allenby, Braden (Committee member) / Johnson, Nathan (Committee member) / McPhearson, Timon (Committee member) / Arizona State University (Publisher)
Created2023
Description
In order to develop a new approach to carbon capture using carbonate brines and solid acids, this research project begins the development of a theoretical basis for solid
acid based capture systems and experimental work to test the validity of the theory. It
appears that solid acids behave like weak acids and are able to increase the concentration
of carbon dioxide above a solution compared to what would be achievable without solid
acids. Experimental work aimed to show that solid acids behave as indicated by theory.
Experiments partially validated the theory through demonstrating desorption of carbon
dioxide from a carbonate brine. The regeneration of the solid acid with the help of a
strong acid was only partially successful due to instability of the solid acid in the
presence of a strong acid. The experimental work used activated.
ContributorsGrayson, Connor (Author) / Lackner, Klaus (Thesis advisor) / Fraser, Matthew (Thesis advisor) / Green, Matthew (Committee member) / Arizona State University (Publisher)
Created2024
Description
Electricity infrastructure vulnerabilities were assessed for future heat waves due to climate change. Critical processes and component relationships were identified and characterized with consideration for the terminal event of service outages, including cascading failures in transmission-level components that can result in blackouts. The most critical dependency identified was the increase in peak electricity demand with higher air temperatures. Historical and future air temperatures were characterized within and across Los Angeles County, California (LAC) and Maricopa County (Phoenix), Arizona. LAC was identified as more vulnerable to heat waves than Phoenix due to a wider distribution of historical temperatures. Two approaches were developed to estimate peak demand based on air temperatures, a top-down statistical model and bottom-up spatial building energy model. Both approaches yielded similar results, in that peak demand should increase sub-linearly at temperatures above 40°C (104 °F) due to saturation in the coincidence of air conditioning (AC) duty cycles. Spatial projections for peak demand were developed for LAC to 2060 considering potential changes in population, building type, building efficiency, AC penetration, appliance efficiency, and air temperatures due climate change. These projections were spatially allocated to delivery system components (generation, transmission lines, and substations) to consider their vulnerability in terms of thermal de-rated capacity and weather adjusted load factor (load divided by capacity). Peak hour electricity demand was projected to increase in residential and commercial sectors by 0.2–6.5 GW (2–51%) by 2060. All grid components, except those near Santa Monica Beach, were projected to experience 2–20% capacity loss due to air temperatures exceeding 40 °C (104 °F). Based on scenario projections, and substation load factors for Southern California Edison (SCE), SCE will require 848—6,724 MW (4-32%) of additional substation capacity or peak shaving in its LAC service territories by 2060 to meet additional demand associated with population growth projections.
ContributorsBurillo, Daniel (Author) / Chester, Mikhail V (Thesis advisor) / Ruddell, Benjamin (Committee member) / Johnson, Nathan (Committee member) / Arizona State University (Publisher)
Created2018
Description
'Attributional' Life Cycle Assessment (LCA) quantitatively tracks the potential environmental impacts of international value chains, in retrospective, while ensuring that burden shifting is avoided. Despite the growing popularity of LCA as a decision-support tool, there are numerous concerns relating to uncertainty and variability in LCA that affects its reliability and credibility. It is pertinent that some part of future research in LCA be guided towards increasing reliability and credibility for decision-making, while utilizing the LCA framework established by ISO 14040.
In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.
Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.
The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.
Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.
Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.
In this dissertation, I have synthesized the present state of knowledge and application of uncertainty and variability in ‘attributional’ LCA, and contribute to its quantitative assessment.
Firstly, the present state of addressment of uncertainty and variability in LCA is consolidated and reviewed. It is evident that sources of uncertainty and variability exist in the following areas: ISO standards, supplementary guides, software tools, life cycle inventory (LCI) databases, all four methodological phases of LCA, and use of LCA information. One source of uncertainty and variability, each, is identified, selected, quantified, and its implications discussed.
The use of surrogate LCI data in lieu of missing dataset(s) or data-gaps is a source of uncertainty. Despite the widespread use of surrogate data, there has been no effort to (1) establish any form of guidance for the appropriate selection of surrogate data and, (2) estimate the uncertainty associated with the choice and use of surrogate data. A formal expert elicitation-based methodology to select the most appropriate surrogates and to quantify the associated uncertainty was proposed and implemented.
Product-evolution in a non-uniform manner is a source of temporal variability that is presently not considered in LCA modeling. The resulting use of outdated LCA information will lead to misguided decisions affecting the issue at concern and eventually the environment. In order to demonstrate product-evolution within the scope of ISO 14044, and given that variability cannot be reduced, the sources of product-evolution were identified, generalized, analyzed and their implications (individual and coupled) on LCA results are quantified.
Finally, recommendations were provided for the advancement of robustness of 'attributional' LCA, with respect to uncertainty and variability.
ContributorsSubramanian, Vairavan (Author) / Golden, Jay S (Thesis advisor) / Chester, Mikhail V (Thesis advisor) / Allenby, Braden R. (Committee member) / Dooley, Kevin J (Committee member) / Arizona State University (Publisher)
Created2016
Description
This thesis examines using thermal energy storage as a demand side management tool for air-conditioning loads with the goal of increasing photovoltaic penetration. It uses Arizona State University (ASU) as a case study. The analysis is completed with a modeling approach using typical meteorological year (TMY) data, along with ASU’s historical load data. Sustainability, greenhouse gas emissions, carbon neutrality, and photovoltaic (PV) penetration are all considered along with potential economic impacts.
By extrapolating the air-conditioning load profile from the existing data sets, it can be ensured that cooling demands can be met at all times under the new management method. Using this cooling demand data, it is possible to determine how much energy is required to meet these needs. Then, modeling the PV arrays, the thermal energy storage (TES), and the chillers, the maximum PV penetration in the future state can be determined.
Using this approach, it has been determined that ASU can increase their solar PV resources by a factor of 3.460, which would amount to a PV penetration of approximately 48%.
By extrapolating the air-conditioning load profile from the existing data sets, it can be ensured that cooling demands can be met at all times under the new management method. Using this cooling demand data, it is possible to determine how much energy is required to meet these needs. Then, modeling the PV arrays, the thermal energy storage (TES), and the chillers, the maximum PV penetration in the future state can be determined.
Using this approach, it has been determined that ASU can increase their solar PV resources by a factor of 3.460, which would amount to a PV penetration of approximately 48%.
ContributorsRouthier, Alexander F (Author) / Honsberg, Christiana (Thesis advisor) / Fraser, Matthew (Committee member) / Bowden, Stuart (Committee member) / Arizona State University (Publisher)
Created2016