Matching Items (36)
Description
The green building movement has been an effective catalyst in reducing energy demands of buildings and a large number of `green' certified buildings have been in operation for several years. Whether these buildings are actually performing as intended, and if not, identifying specific causes for this discrepancy falls into the general realm of post-occupancy evaluation (POE). POE involves evaluating building performance in terms of energy-use, indoor environmental quality, acoustics and water-use; the first aspect i.e. energy-use is addressed in this thesis. Normally, a full year or more of energy-use and weather data is required to determine the actual post-occupancy energy-use of buildings. In many cases, either measured building performance data is not available or the time and cost implications may not make it feasible to invest in monitoring the building for a whole year. Knowledge about the minimum amount of measured data needed to accurately capture the behavior of the building over the entire year can be immensely beneficial. This research identifies simple modeling techniques to determine best time of the year to begin in-situ monitoring of building energy-use, and the least amount of data required for generating acceptable long-term predictions. Four analysis procedures are studied. The short-term monitoring for long-term prediction (SMLP) approach and dry-bulb temperature analysis (DBTA) approach allow determining the best time and duration of the year for in-situ monitoring to be performed based only on the ambient temperature data of the location. Multivariate change-point (MCP) modeling uses simulated/monitored data to determine best monitoring period of the year. This is also used to validate the SMLP and DBTA approaches. The hybrid inverse modeling method-1 predicts energy-use by combining a short dataset of monitored internal loads with a year of utility-bills, and hybrid inverse method-2 predicts long term building performance using utility-bills only. The results obtained show that often less than three to four months of monitored data is adequate for estimating the annual building energy use, provided that the monitoring is initiated at the right time, and the seasonal as well as daily variations are adequately captured by the short dataset. The predictive accuracy of the short data-sets is found to be strongly influenced by the closeness of the dataset's mean temperature to the annual average temperature. The analysis methods studied would be very useful for energy professionals involved in POE.
ContributorsSingh, Vipul (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (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
The world is grappling with two serious issues related to energy and climate change. The use of solar energy is receiving much attention due to its potential as one of the solutions. Air conditioning is particularly attractive as a solar energy application because of the near coincidence of peak cooling loads with the available solar power. Recently, researchers have started serious discussions of using adsorptive processes for refrigeration and heat pumps. There is some success for the >100 ton adsorption systems but none exists in the <10 ton size range required for residential air conditioning. There are myriad reasons for the lack of small-scale systems such as low Coefficient of Performance (COP), high capital cost, scalability, and limited performance data. A numerical model to simulate an adsorption system was developed and its performance was compared with similar thermal-powered systems. Results showed that both the adsorption and absorption systems provide equal cooling capacity for a driving temperature range of 70-120 ºC, but the adsorption system is the only system to deliver cooling at temperatures below 65 ºC. Additionally, the absorption and desiccant systems provide better COP at low temperatures, but the COP's of the three systems converge at higher regeneration temperatures. To further investigate the viability of solar-powered heat pump systems, an hourly building load simulation was developed for a single-family house in the Phoenix metropolitan area. Thermal as well as economic performance comparison was conducted for adsorption, absorption, and solar photovoltaic (PV) powered vapor compression systems for a range of solar collector area and storage capacity. The results showed that for a small collector area, solar PV is more cost-effective whereas adsorption is better than absorption for larger collector area. The optimum solar collector area and the storage size were determined for each type of solar system. As part of this dissertation work, a small-scale proof-of-concept prototype of the adsorption system was assembled using some novel heat transfer enhancement strategies. Activated carbon and butane was chosen as the adsorbent-refrigerant pair. It was found that a COP of 0.12 and a cooling capacity of 89.6 W can be achieved.
ContributorsGupta, Yeshpal (Author) / Phelan, Patrick E (Thesis advisor) / Bryan, Harvey J. (Committee member) / Mikellidas, Pavlos G (Committee member) / Pacheco, Jose R (Committee member) / Trimble, Steven W (Committee member) / Arizona State University (Publisher)
Created2011
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
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
According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI pertinent to the building type. The ability to identify and rank the important variables is of great importance in practical implementation of the benchmarking tools which rely on query-based building and HVAC variable filters specified by the user.
ContributorsKaskhedikar, Apoorva Prakash (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Runger, George C. (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
The poor energy efficiency of buildings is a major barrier to alleviating the energy dilemma. Historically, monthly utility billing data was widely available and analytical methods for identifying building energy efficiency improvements, performing building Monitoring and Verification (M&V;) and continuous commissioning (CCx) were based on them. Although robust, these methods were not sensitive enough to detect a number of common causes for increased energy use. In recent years, prevalence of short-term building energy consumption data, also known as Energy Interval Data (EID), made available through the Smart Meters, along with data mining techniques presents the potential of knowledge discovery inherent in this data. This allows more sophisticated analytical tools to be developed resulting in greater sensitivities due to higher prediction accuracies; leading to deep energy savings and highly efficient building system operations. The research explores enhancements to Inverse Statistical Modeling techniques due to the availability of EID. Inverse statistical modeling is the process of identification of prediction model structure and estimates of model parameters. The methodology is based on several common statistical and data mining techniques: cluster analysis for day typing, outlier detection and removal, and generation of building scheduling. Inverse methods are simpler to develop and require fewer inputs for model identification. They can model changes in energy consumption based on changes in climatic variables and up to a certain extent, occupancy. This makes them easy-to-use and appealing to building managers for evaluating any general retrofits, building condition monitoring, continuous commissioning and short-term load forecasting (STLF). After evaluating several model structures, an elegant model form was derived which can be used to model daily energy consumption; which can be extended to model energy consumption for any specific hour by adding corrective terms. Additionally, adding AR terms to this model makes it usable for STLF. Two different buildings, one synthetic (ASHRAE medium-office prototype) building and another, an actual office building, were modeled using these techniques. The methodologies proposed have several novel features compared to the manner in which these models have been described earlier. Finally, this thesis investigates characteristic fault signature identification from detailed simulation models and subsequent inverse analysis.
ContributorsJalori, Saurabh (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT Leadership in Energy and Environmental Design (LEED) is a non-governmental organization of U.S. Green Building Council (USGBC) which promotes a sustainable built environment with its rating systems. One of the building segments which it considers is healthcare, where it is a challenge to identify the most cost-effective variety of complex equipments, to meet the demand for 24/7 health care and diagnosis, and implement various energy efficient strategies in inpatient hospitals. According to their “End Use Monitoring” study, Hospital Energy Alliances (HEA), an initiative of U.S. Department of Energy (DOE), reducing plug load reduces hospital energy consumption. The aim of this thesis is to investigate the extent to which realistic changes to the building envelope, together with HVAC and operation schedules would allow LEED credits to be earned in the DOE–hospital prototype. The scope of this research is to specifically investigate the inpatient block where patient stays longer. However, to obtain LEED credits the percentage cost saving should be considered along with the end use monitoring. Several steps have been taken to identify the optimal set of the end use results by adopting the Whole Building Energy Simulation option of the LEED Energy & Atmosphere (EA) pre– requisite 2: Minimum Energy Performance. The initial step includes evaluating certain LEED criteria consistent with ASHRAE Standard 90.1–2007 with the constraint that hospital prototype is to be upgraded from Standard 2004 to Standard 2007. The simulation method stipulates energy conservation measures as well as utility costing to enhance the LEED credits. A series of simulations with different values of Light Power Density, Sizing Factors, Chiller Coefficient of Performance, Boiler Efficiency, Plug Loads and utility cost were run for a variety of end uses with the extreme climatic condition of Phoenix. These assessments are then compared and used as a framework for a proposed interactive design decision approach. As a result, a total of 19.4% energy savings and 20% utility cost savings were achieved by the building simulation tool, which refer to 5 and 7 LEED credits respectively. The study develops a proper framework for future evaluations intended to achieve more LEED points.
ContributorsHaque, Sadia Khandaker (Author) / Reddy, T A (Thesis advisor) / Bryan, Harvey J. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2012
Description
In geographical locations with hot-arid climates, sun control in buildings is one primary problem to solve for the building envelope design. Today's technological advances in building science bring with them the opportunity to design dynamic façade systems for sun radiation control and daylighting. Although dynamic systems can become an attractive visual element, they can be costly and challenging to maintain for building owners. Alternatively, fixed solar-shading systems can be designed to create dynamism in the façade of the building, while providing similar functionalities for sun control. The work presented in this project focuses on the use of a visual scripting editor for modeling software, Grasshopper, to develop a Solar Control Visual Script that evaluates building envelope surfaces with planar and non-uniform rational basis-spline (NURBS) forms and provides projections for fixed sun control systems. The design platform of Grasshopper allows individuals with no experience or prior computer coding education to build up programming-like capabilities; this feature permits users to discover new design possibilities within flexible frames that can contribute to the overall design being pursued, while also having an environmental response. The Solar Control Visual Script provides minimum sizing geometries that achieve shading in openings at a particular date and time of the year. The model for this method of analysis makes use of three components to derive the appropriate values for the projections of shading geometries: typical meteorological year (TMY) data, irradiation isotropic equations and shading profile angles equations for vertical and tilted surfaces. Providing an automatic visual of generated geometries uncovers the opportunity to test several model forms and reiterates the analysis when modifying control parameters. By employing building science as a set of environmental parameters, the design outcome bears a dynamic form that responds to natural force conditions. The optimized results promote an efficient environmental design solution for sun control as an integral alternative into the building envelope.
ContributorsGrijalva, Karla (Author) / Bryan, Harvey J. (Thesis advisor) / Griffiths, Jason (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2012