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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
This paper describes the research done to quantify the relationship between external air temperature and energy consumption and internal air temperature and energy consumption. The study was conducted on a LEED Gold certified building, College Avenue Commons, located on Arizona State University's Tempe campus. It includes information on the background of previous studies in the area, some that agree with the research hypotheses and some that take a different path. Real-time data was collected hourly for energy consumption and external air temperature. Intermittent internal air temperature was collected by undergraduate researcher, Charles Banke. Regression analysis was used to prove two research hypotheses. The authors found no correlation between external air temperature and energy consumption, nor did they find a relationship between internal air temperature and energy consumption. This paper also includes recommendations for future work to improve the study.
ContributorsBanke, Charles Michael (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Building construction, design and maintenance is a sector of engineering where improved efficiency will have immense impacts on resource consumption and environmental health. This research closely examines the Leadership in Environment and Energy Design (LEED) rating system and the International Green Construction Code (IgCC). The IgCC is a model code, written with the same structure as many building codes. It is a standard that can be enforced if a city's government decides to adopt it. When IgCC is enforced, the buildings either meet all of the requirements set forth in the document or it fails to meet the code standards. The LEED Rating System, on the other hand, is not a building code. LEED certified buildings are built according to the standards of their local jurisdiction and in addition to that, building owners can chose to pursue a LEED certification. This is a rating system that awards points based on the sustainable measures achieved by a building. A comparison of these green building systems highlights their accomplishments in terms of reduced electricity usage, usage of low-impact materials, indoor environmental quality and other innovative features. It was determined that in general IgCC is more holistic, stringent approach to green building. At the same time the LEED rating system a wider variety of green building options. In addition, building data from LEED certified buildings was complied and analyzed to understand important trends. Both of these methods are progressing towards low-impact, efficient infrastructure and a side-by-side comparison, as done in this research, shed light on the strengths and weaknesses of each method, allowing for future improvements.
ContributorsCampbell, Kaleigh Ruth (Author) / Chong, Oswald (Thesis director) / Parrish, Kristen (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Building information modeling (BIM) has already sparked changes in design and construction practices, ranging from new methods to coordinate work during design to supporting paperless construction sites where crews use handheld devices in lieu of paper plans. It is seen as the starting point for the larger picture, virtual design and construction (VDC). While some research has explored the feasibility of using BIM for Facilities Management (FM) this practice is yet to become widely accepted and integrated. This paper explores how VDC could improve the operations of a Facilities Management department at a large state university. Specifically, the authors examine the degree to which institutional requirements foster BIM use during building operations, the ability of models to interface with existing FM software, and the willingness of FM executives to incorporate BIM into their processes. The authors also discuss the sorts of information contained in building models that FM could find most useful, and highlight those pieces of information required for FM that many building models do not contain. Finally, the paper closes with a set of recommendations about how to create building models that more seamlessly integrate into existing Facilities Management processes at the university studied, in order to draw a set of recommendations that may apply more broadly to state universities and similar institutions.
ContributorsHebel, Natasha Faith (Author) / Parrish, Kristen (Thesis director) / Ayer, Steven (Committee member) / Del E. Webb School of Construction (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Residential air conditioning systems represent a critical load for many electric
utilities, especially for those who serve customers in hot climates. In hot and dry
climates, in particular, the cooling load is usually relatively low during night hours and
early mornings and hits its maximum in the late afternoon. If electric loads could be
shifted from peak hours (e.g., late afternoon) to off-peak hours (e.g., late morning), not
only would building operation costs decrease, the need to run peaker plants, which
typically use more fossil fuels than non-peaker plants, would also decrease. Thus, shifting
electricity consumption from peak to off-peak hours promotes economic and
environmental savings. Operational and technological strategies can reduce the load
during peak hours by shifting cooling operation from on-peak hours to off-peak hours.
Although operational peak load shifting strategies such as precooling may require
mechanical cooling (e.g., in climates like Phoenix, Arizona), this cooling is less
expensive than on-peak cooling due to demand charges or time-based price plans.
Precooling is an operational shift, rather than a technological one, and is thus widely
accessible to utilities’ customer base. This dissertation compares the effects of different
precooling strategies in a Phoenix-based utility’s residential customer market and
assesses the impact of technological enhancements (e.g., energy efficiency measures and
solar photovoltaic system) on the performance of precooling. This dissertation focuses on
the operational and technological peak load shifting strategies that are feasible for
residential buildings and discusses the advantages of each in terms of peak energy
savings and residential electricity cost savings.
utilities, especially for those who serve customers in hot climates. In hot and dry
climates, in particular, the cooling load is usually relatively low during night hours and
early mornings and hits its maximum in the late afternoon. If electric loads could be
shifted from peak hours (e.g., late afternoon) to off-peak hours (e.g., late morning), not
only would building operation costs decrease, the need to run peaker plants, which
typically use more fossil fuels than non-peaker plants, would also decrease. Thus, shifting
electricity consumption from peak to off-peak hours promotes economic and
environmental savings. Operational and technological strategies can reduce the load
during peak hours by shifting cooling operation from on-peak hours to off-peak hours.
Although operational peak load shifting strategies such as precooling may require
mechanical cooling (e.g., in climates like Phoenix, Arizona), this cooling is less
expensive than on-peak cooling due to demand charges or time-based price plans.
Precooling is an operational shift, rather than a technological one, and is thus widely
accessible to utilities’ customer base. This dissertation compares the effects of different
precooling strategies in a Phoenix-based utility’s residential customer market and
assesses the impact of technological enhancements (e.g., energy efficiency measures and
solar photovoltaic system) on the performance of precooling. This dissertation focuses on
the operational and technological peak load shifting strategies that are feasible for
residential buildings and discusses the advantages of each in terms of peak energy
savings and residential electricity cost savings.
ContributorsArababadi, Reza (Author) / Parrish, Kristen (Thesis advisor) / Reddy, T A (Committee member) / Jackson, Roderick K (Committee member) / Arizona State University (Publisher)
Created2016
Description
Commercial buildings in the United States account for 19% of the total energy consumption annually. Commercial Building Energy Consumption Survey (CBECS), which serves as the benchmark for all the commercial buildings provides critical input for EnergyStar models. Smart energy management technologies, sensors, innovative demand response programs, and updated versions of certification programs elevate the opportunity to mitigate energy-related problems (blackouts and overproduction) and guides energy managers to optimize the consumption characteristics. With increasing advancements in technologies relying on the ‘Big Data,' codes and certification programs such as the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and the Leadership in Energy and Environmental Design (LEED) evaluates during the pre-construction phase. It is mostly carried out with the assumed quantitative and qualitative values calculated from energy models such as Energy Plus and E-quest. However, the energy consumption analysis through Knowledge Discovery in Databases (KDD) is not commonly used by energy managers to perform complete implementation, causing the need for better energy analytic framework.
The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to
1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.
2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.
3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.
With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.
The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to
1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.
2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.
3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.
With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.
ContributorsNaganathan, Hariharan (Author) / Chong, Oswald W (Thesis advisor) / Ariaratnam, Samuel T (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2017
Description
This is an applied research paper, where a micro campus was designed for the San Carlos Apache Community with a goal of meeting requirements for at least three petals of Living Building Challenge. The end goal was to submit recommendations for attaining the petal certifications. The process of design not only included following spatial requirements of designing the building, but also including a wider perspective of construction and energy management in it. The first step of the research was getting to know the community and their requirements and priorities. This was done in 1st semester as a part of an applied class Indigenous Project Delivery. The second part of the research was to design a micro campus for the community that is in sync with the main campus. The intent of design is to respect the community’s culture and help them pass it on to the next generation while abiding by the Living Building Challenge standards. The third step of this research was to back up the design with recommendations for petal certifications.
ContributorsSingaraju, Meghana (Author) / Costa, Wanda Dalla (Thesis advisor) / Coseo, Paul (Committee member) / Vekstein, Claudio (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2022
Description
This research is a comprehensive study of the sustainable modifiers for asphalt binder. It is a common practice to use modifiers to impart certain properties to asphalt binder; however, in order to facilitate the synthesis and design of highly effective sustainable modifiers, it is critical to thoroughly understand their underlying molecular level mechanisms in combination with micro and macro-level behavior. Therefore, this study incorporates a multi-scale approach using computational modeling and laboratory experiments to provide an in-depth understanding of the mechanisms of interaction between selected modifiers and the constituents of asphalt binder, at aged and unaged conditions. This study investigated the effect of paraffinic wax as a modifier for virgin binder in warm-mix asphalt that can reduce the environmental burden of asphalt pavements. The addition of wax was shown to reduce the viscosity of bitumen by reducing the self-interaction of asphaltene molecules and penetrating the existing nano agglomerates of asphaltenes. This study further examined how the interplay of various modifiers affects the modified binder’s thermomechanical properties. It was found that the presence of wax-based modifiers has a disrupting effect on the role of polyphosphoric acid that is another modifier of bitumen and its interactions with resin-type molecules.
This study was further extended to using nanozeolite as a mineral carrier for wax to better disperse wax in bitumen and reduce the wax's adverse effects such as physical hardening at low service temperatures and rutting at high service temperatures. This novel technique showed that using a different method of adding a modifier can help reduce the modifier's unwanted effects. It further showed that nanozeolite could carry wax-based modifiers and release them in bitumen, then acting as a scavenger for acidic compounds in the binder. This, in turn, could promote the resistance of asphalt binder to moisture damage by reducing the quantity of acidic compounds at the interface between the binder and the stone aggregates.
Furthermore, this study shows that iso-paraffin wax can reduce oxidized asphaltene molecules self-interaction and therefore, reduce the viscosity of aged bitumen while cause brittleness at low temperatures.
Additionally, a cradle to gate life-cycle assessment was performed for a new bio-modifier obtained from swine manure. This study showed that by partially replacing the bitumen with bio-binder from swine manure, the carbon footprint of the binder can be reduced by 10% in conjunction with reducing the cost and environmental impact of storing the manure in lagoons.
ContributorsSamieadel, Alireza (Author) / Fini, Elham H (Thesis advisor) / Kaloush, Kamil (Committee member) / Parrish, Kristen (Committee member) / Sharma, Brajendra Kumar (Committee member) / Parast, Mahour M (Committee member) / Arizona State University (Publisher)
Created2020