Matching Items (18)
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- All Subjects: Sustainability
- All Subjects: Energy Simulation
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
Through manipulation of adaptable opportunities available within a given environment, individuals become active participants in managing personal comfort requirements, by exercising control over their comfort without the assistance of mechanical heating and cooling systems. Similarly, continuous manipulation of a building skin's form, insulation, porosity, and transmissivity qualities exerts control over the energy exchanged between indoor and outdoor environments. This research uses four adaptive response variables in a modified software algorithm to explore an adaptive building skin's potential in reacting to environmental stimuli with the purpose of minimizing energy use without sacrificing occupant comfort. Results illustrate that significant energy savings can be realized with adaptive envelopes over static building envelopes even under extreme summer and winter climate conditions; that the magnitude of these savings are dependent on climate and orientation; and that occupant thermal comfort can be improved consistently over comfort levels achieved by optimized static building envelopes. The resulting adaptive envelope's unique climate-specific behavior could inform designers in creating an intelligent kinetic aesthetic that helps facilitate adaptability and resiliency in architecture.
ContributorsErickson, James (Author) / Bryan, Harvey (Thesis advisor) / Addison, Marlin (Committee member) / Kroelinger, Michael D. (Committee member) / Reddy, T. Agami (Committee member) / Arizona State University (Publisher)
Created2013
Description
The environmental and economic assessment of neighborhood-scale transit-oriented urban form changes should include initial construction impacts through long-term use to fully understand the benefits and costs of smart growth policies. The long-term impacts of moving people closer to transit require the coupling of behavioral forecasting with environmental assessment. Using new light rail and bus rapid transit in Los Angeles, California as a case study, a life-cycle environmental and economic assessment is developed to assess the potential range of impacts resulting from mixed-use infill development. An integrated transportation and land use life-cycle assessment framework is developed to estimate energy consumption, air emissions, and economic (public, developer, and user) costs. Residential and commercial buildings, automobile travel, and transit operation changes are included and a 60-year forecast is developed that compares transit-oriented growth against growth in areas without close access to high-capacity transit service. The results show that commercial developments create the greatest potential for impact reductions followed by residential commute shifts to transit, both of which may be effected by access to high-capacity transit, reduced parking requirements, and developer incentives. Greenhouse gas emission reductions up to 470 Gg CO2-equivalents per year can be achieved with potential costs savings for TOD users. The potential for respiratory impacts (PM10-equivalents) and smog formation can be reduced by 28-35%. The shift from business-as-usual growth to transit-oriented development can decrease user costs by $3,100 per household per year over the building lifetime, despite higher rental costs within the mixed-use development.
ContributorsNahlik, Matthew (Author) / Chester, Mikhail V (Thesis advisor) / Pendyala, Ram (Committee member) / Fraser, Matthew (Committee member) / Arizona State University (Publisher)
Created2014
Description
Comparative life cycle assessment (LCA) evaluates the relative performance of multiple products, services, or technologies with the purpose of selecting the least impactful alternative. Nevertheless, characterized results are seldom conclusive. When one alternative performs best in some aspects, it may also performs worse in others. These tradeoffs among different impact categories make it difficult to identify environmentally preferable alternatives. To help reconcile this dilemma, LCA analysts have the option to apply normalization and weighting to generate comparisons based upon a single score. However, these approaches can be misleading because they suffer from problems of reference dataset incompletion, linear and fully compensatory aggregation, masking of salient tradeoffs, weight insensitivity and difficulties incorporating uncertainty in performance assessment and weights. Consequently, most LCA studies truncate impacts assessment at characterization, which leaves decision-makers to confront highly uncertain multi-criteria problems without the aid of analytic guideposts. This study introduces Stochastic Multi attribute Analysis (SMAA), a novel approach to normalization and weighting of characterized life-cycle inventory data for use in comparative Life Cycle Assessment (LCA). The proposed method avoids the bias introduced by external normalization references, and is capable of exploring high uncertainty in both the input parameters and weights.
ContributorsPrado, Valentina (Author) / Seager, Thomas P (Thesis advisor) / Chester, Mikhail V (Committee member) / Kullapa Soratana (Committee member) / Tervonen, Tommi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Buildings in the United States, account for over 68 percent of electricity consumed, 39 percent of total energy use, and 38 percent of the carbon dioxide emissions. By the year 2035, about 75% of the U.S. building sector will be either new or renovated. The energy efficiency requirements of current building codes would have a significant impact on future energy use, hence, one of the most widely accepted solutions to slowing the growth rate of GHG emissions and then reversing it involves a stringent adoption of building energy codes. A large number of building energy codes exist and a large number of studies which state the energy savings possible through code compliance. However, most codes are difficult to comprehend and require an extensive understanding of the code, the compliance paths, all mandatory and prescriptive requirements as well as the strategy to convert the same to energy model inputs. This paper provides a simplified solution for the entire process by providing an easy to use interface for code compliance and energy simulation through a spreadsheet based tool, the ECCO or the Energy Code COmpliance Tool. This tool provides a platform for a more detailed analysis of building codes as applicable to each and every individual building in each climate zone. It also facilitates quick building energy simulation to determine energy savings achieved through code compliance. This process is highly beneficial not only for code compliance, but also for identifying parameters which can be improved for energy efficiency. Code compliance is simplified through a series of parametric runs which generates the minimally compliant baseline building and 30% beyond code building. This tool is seen as an effective solution for architects and engineers for an initial level analysis as well as for jurisdictions as a front-end diagnostic check for code compliance.
ContributorsGoel, Supriya (Author) / Bryan, Harvey J. (Thesis advisor) / Reddy, T. Agami (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011
Description
Arizona has an abundant solar resource and technologically mature systems are available to capture it, but solar energy systems are still considered to be an innovative technology. Adoption rates for solar and wind energy systems rise and fall with the political tides, and are relatively low in most rural areas in Arizona. This thesis tests the hypothesis that a consumer profile developed to characterize the adopters of renewable energy technology (RET) systems in rural Arizona is the same as the profile of other area residents who performed renovations, upgrades or additions to their homes. Residents of Santa Cruz and Cochise Counties who had obtained building permits to either install a solar or wind energy system or to perform a substantial renovation or upgrade to their home were surveyed to gather demographic, psychographic and behavioristic data. The data from 133 survey responses (76 from RET adopters and 57 from non-adopters) provided insights about their decisions regarding whether or not to adopt a RET system. The results, which are statistically significant at the 99% level of confidence, indicate that RET adopters had smaller households, were older and had higher education levels and greater income levels than the non-adopters. The research also provides answers to three related questions: First, are the energy conservation habits of RET adopters the same as those of non-adopters? Second, what were the sources of information consulted and the most important factors that motivated the decision to purchase a solar or wind energy system? And finally, are any of the factors which influenced the decision to live in a rural area in southeastern Arizona related to the decision to purchase a renewable energy system? The answers are provided, along with a series of recommendations that are designed to inform marketers and other promoters of RETs about how to utilize these results to help achieve their goals.
ContributorsPorter, Wayne Eliot (Author) / Reddy, T. Agami (Thesis advisor) / Pasqualetti, Martin (Committee member) / Larson, Kelli (Committee member) / Kennedy, Linda (Committee member) / Arizona State University (Publisher)
Created2011
Description
One of the key infrastructures of any community or facility is the energy system which consists of utility power plants, distributed generation technologies, and building heating and cooling systems. In general, there are two dimensions to “sustainability” as it applies to an engineered system. It needs to be designed, operated, and managed such that its environmental impacts and costs are minimal (energy efficient design and operation), and also be designed and configured in a way that it is resilient in confronting disruptions posed by natural, manmade, or random events. In this regard, development of quantitative sustainability metrics in support of decision-making relevant to design, future growth planning, and day-to-day operation of such systems would be of great value. In this study, a pragmatic performance-based sustainability assessment framework and quantitative indices are developed towards this end whereby sustainability goals and concepts can be translated and integrated into engineering practices.
New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components.
Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance.
A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
New quantitative sustainability indices are proposed to capture the energy system environmental impacts, economic performance, and resilience attributes, characterized by normalized environmental/health externalities, energy costs, and penalty costs respectively. A comprehensive Life Cycle Assessment is proposed which includes externalities due to emissions from different supply and demand-side energy systems specific to the regional power generation energy portfolio mix. An approach based on external costs, i.e. the monetized health and environmental impacts, was used to quantify adverse consequences associated with different energy system components.
Further, this thesis also proposes a new performance-based method for characterizing and assessing resilience of multi-functional demand-side engineered systems. Through modeling of system response to potential internal and external failures during different operational temporal periods reflective of diurnal variation in loads and services, the proposed methodology quantifies resilience of the system based on imposed penalty costs to the system stakeholders due to undelivered or interrupted services and/or non-optimal system performance.
A conceptual diagram called “Sustainability Compass” is also proposed which facilitates communicating the assessment results and allow better decision-analysis through illustration of different system attributes and trade-offs between different alternatives. The proposed methodologies have been illustrated using end-use monitored data for whole year operation of a university campus energy system.
ContributorsMoslehi, Salim (Author) / Reddy, T. Agami (Thesis advisor) / Lackner, Klaus S (Committee member) / Parrish, Kristen (Committee member) / Pendyala, Ram M. (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2018
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
This research is aimed at studying the impact of building design parameters in terms of their importance and mutual interaction, and how these aspects vary across climates and HVAC system types. A methodology is proposed for such a study, by examining the feasibility and use of two different statistical methods to derive all realistic ‘near-optimum’ solutions which might be lost using a simple optimization technique.
DOE prototype medium office building compliant with ASHRAE 90.1-2010 was selected for the analysis and four different HVAC systems in three US climates were simulated.
The interaction between building design parameters related to envelope characteristics and geometry (total of seven variables) has been studied using two different statistical methods, namely the ‘Morris method’ and ‘Predictive Learning via Rule Ensembles’.
Subsequently, a simple graphical tool based on sensitivity analysis has been developed and demonstrated to present the results from parametric simulations. This tool would be useful to better inform design decisions since it allows imposition of constraints on various parameters and visualize their interaction with other parameters.
It was observed that the Radiant system performed best in all three climates, followed by displacement ventilation system. However, it should be noted that this study did not deal with performance optimization of HVAC systems while there have been several studies which concluded that a VAV system with better controls can perform better than some of the newer HVAC technologies. In terms of building design parameters, it was observed that ‘Ceiling Height’, ‘Window-Wall Ratio’ and ‘Window Properties’ showed highest importance as well as interaction as compared to other parameters considered in this study, for all HVAC systems and climates.
Based on the results of this study, it is suggested to extend such analysis using statistical methods such as the ‘Morris method’, which require much fewer simulations to categorize parameters based on their importance and interaction strength. Usage of statistical methods like ‘Rule Ensembles’ or other simple visual tools to analyze simulation results for all combinations of parameters that show interaction would allow designers to make informed and superior design decisions while benefiting from large reduction in computational time.
DOE prototype medium office building compliant with ASHRAE 90.1-2010 was selected for the analysis and four different HVAC systems in three US climates were simulated.
The interaction between building design parameters related to envelope characteristics and geometry (total of seven variables) has been studied using two different statistical methods, namely the ‘Morris method’ and ‘Predictive Learning via Rule Ensembles’.
Subsequently, a simple graphical tool based on sensitivity analysis has been developed and demonstrated to present the results from parametric simulations. This tool would be useful to better inform design decisions since it allows imposition of constraints on various parameters and visualize their interaction with other parameters.
It was observed that the Radiant system performed best in all three climates, followed by displacement ventilation system. However, it should be noted that this study did not deal with performance optimization of HVAC systems while there have been several studies which concluded that a VAV system with better controls can perform better than some of the newer HVAC technologies. In terms of building design parameters, it was observed that ‘Ceiling Height’, ‘Window-Wall Ratio’ and ‘Window Properties’ showed highest importance as well as interaction as compared to other parameters considered in this study, for all HVAC systems and climates.
Based on the results of this study, it is suggested to extend such analysis using statistical methods such as the ‘Morris method’, which require much fewer simulations to categorize parameters based on their importance and interaction strength. Usage of statistical methods like ‘Rule Ensembles’ or other simple visual tools to analyze simulation results for all combinations of parameters that show interaction would allow designers to make informed and superior design decisions while benefiting from large reduction in computational time.
ContributorsDidwania, Srijan Kumar (Author) / Reddy, T. Agami (Thesis advisor) / Addison, Marlin S. (Thesis advisor) / Bryan, Harvey J. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Energy use within urban building stocks is continuing to increase globally as populations expand and access to electricity improves. This projected increase in demand could require deployment of new generation capacity, but there is potential to offset some of this demand through modification of the buildings themselves. Building stocks are quasi-permanent infrastructures which have enduring influence on urban energy consumption, and research is needed to understand: 1) how development patterns constrain energy use decisions and 2) how cities can achieve energy and environmental goals given the constraints of the stock. This requires a thorough evaluation of both the growth of the stock and as well as the spatial distribution of use throughout the city. In this dissertation, a case study in Los Angeles County, California (LAC) is used to quantify urban growth, forecast future energy use under climate change, and to make recommendations for mitigating energy consumption increases. A reproducible methodological framework is included for application to other urban areas.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
ContributorsReyna, Janet Lorel (Author) / Chester, Mikhail V (Thesis advisor) / Gurney, Kevin (Committee member) / Reddy, T. Agami (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2016