Matching Items (17)
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- All Subjects: Architectural engineering
- Creators: Bryan, Harvey
Description
The intent of this research is to determine if cool roofs lead to increased energy use in the U.S. and if so, in what climates. Directed by the LEED environmental building rating system, cool roofs are increasingly specified in an attempt to mitigate urban heat island effect. A typical single story retail building was simulated using eQUEST energy software across seven different climatic zones in the U.S.. Two roof types are varied, one with a low solar reflectance index of 30 (typical bituminous roof), and a roof with SRI of 90 (high performing membrane roof). The model also varied the perimeter / core fraction, internal loads, and schedule of operations. The data suggests a certain point at which a high SRI roofing finish results in energy penalties over the course of the year in climate zones which are heating driven. Climate zones 5 and above appear to be the flipping point, beyond which the application of a high SRI roof creates sufficient heating penalties to outweigh the cooling energy benefits.
ContributorsLee, John (Author) / Bryan, Harvey (Thesis advisor) / Marlin, Marlin (Committee member) / Ramalingam, Muthukumar (Committee member) / Arizona State University (Publisher)
Created2011
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
With the desire of high standards of comfort, huge amount of energy is being consumed to maintain the indoor environment. In US building consumes 40% of the total primary energy while residential buildings consume about 21%. A large proportion of this consumption is due to cooling of buildings. Deteriorating environmental conditions due to excessive energy use suggest that we should look at passive designs and renewable energy opportunities to supply the required comfort. Phoenix gets about 300 days of clear sky every year. It also witnesses large temperature variations from night and day. The humidity ratio almost always stays below the 50% mark. With more than six months having outside temperatures more than 75 oF, night sky radiative cooling promise to be an attractive means to cool the buildings during summer. This technique can be useful for small commercial facilities or residential buildings. The roof ponds can be made more effective by covering them with Band Filters. These band filters block the solar heat gain and allow the water to cool down to lower temperatures. It also reduces the convection heat gain. This helps rood ponds maintain lower temperatures and provide more cooling then an exposed pond. 50 μm Polyethylene band filter is used in this study. Using this band filter, roof ponds can be made up to 10% more effective. About 45% of the energy required to cool a typical residential building in summer can be saved.
ContributorsSiddiqui, Mohd. Aqdus (Author) / Bryan, Harvey (Thesis advisor) / Reddy, T Agami (Committee member) / Kroelinger, Michael D. (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
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
The building sector is responsible for consuming the largest proportional share of global material and energy resources. Some observers assert that buildings are the problem and the solution to climate change. It appears that in the United States a coherent national energy policy to encourage rapid building performance improvements is not imminent. In this environment, where many climate and ecological scientists believe we are running out of time to reverse the effects of anthropogenic climate change, a local grass-roots effort to create demonstration net zero-energy buildings (ZEB) appears necessary. This paper documents the process of designing a ZEB in a community with no existing documented ZEB precedent. The project will establish a framework for collecting design, performance, and financial data for use by architects, building scientists, and the community at large. This type of information may prove critical in order to foster a near-term local demand for net zero-energy buildings.
ContributorsFrancis, Alan Merrill (Author) / Bryan, Harvey (Thesis advisor) / Addison, Marlin (Committee member) / Ramalingam, Muthukumar (Committee member) / Arizona State University (Publisher)
Created2014
Description
A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed.
ContributorsKhanolkar, Amruta (Author) / Reddy, T Agami (Thesis advisor) / Addison, Marlin (Committee member) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2012
Description
Among the various end-use sectors, the commercial sector is expected to have the second-largest increase in total primary energy consump¬tion from 2009 to 2035 (5.8 quadrillion Btu) with a growth rate of 1.1% per year, it is the fastest growing end-use sectors. In order to make major gains in reducing U.S. building energy use commercial sector buildings must be improved. Energy benchmarking of buildings gives the facility manager or the building owner a quick evaluation of energy use and the potential for energy savings. It is the process of comparing the energy performance of a building to standards and codes, to a set target performance or to a range of energy performance values of similar buildings in order to help assess opportunities for improvement. Commissioning of buildings is the process of ensuring that systems are designed, installed, functionally tested and capable of being operated and maintained according to the owner's operational needs. It is the first stage in the building upgrade process after it has been assessed using benchmarking tools. The staged approach accounts for the interactions among all the energy flows in a building and produces a systematic method for planning upgrades that increase energy savings. This research compares and analyzes selected benchmarking and retrocommissioning tools to validate their accuracy such that they could be used in the initial audit process of a building. The benchmarking study analyzes the Energy Use Intensities (EUIs) and Ratings assigned by Portfolio Manager and Oak Ridge National Laboratory (ORNL) Spreadsheets. The 90.1 Prototype models and Commercial Reference Building model for Large Office building type were used for this comparative analysis. A case-study building from the DOE - funded Energize Phoenix program was also benchmarked for its EUI and rating. The retrocommissioning study was conducted by modeling these prototype models and the case-study building in the Facility Energy Decision System (FEDS) tool to simulate their energy consumption and analyze the retrofits suggested by the tool. The results of the benchmarking study proved that a benchmarking tool could be used as a first step in the audit process, encouraging the building owner to conduct an energy audit and realize the energy savings potential. The retrocommissioning study established the validity of FEDS as an accurate tool to simulate a building for its energy performance using basic inputs and to accurately predict the energy savings achieved by the retrofits recommended on the basis of maximum LCC savings.
ContributorsAgnihotri, Shreya Prabodhkumar (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2011
Description
Building Envelope includes walls, roofs and openings, which react to the outdoor environmental condition. Today, with the increasing use of glass in building envelope, the energy usage of the buildings is increasing, especially in the offices and commercial buildings. Use of right glass type and control triggers helps to optimize the energy use, by tradeoff between optical and thermal properties. The part of the research looks at the different control triggers and its range that governs the use of electrochromic glass to regulate the energy usage in building. All different control trigger that can be possibly used for regulating the clear and tint state of glass were analyzed with most appropriate range. Its range was triggered such that 80% time of the glass is trigger between the ranges. The other building parameters like window wall ratio and orientations were also investigated. The other half of the research study looks into the feasibility of using the Electrochromic windows, as it is ought to be the main factor governing the market usage of Electrochromic windows and to investigate the possible ways to make it feasible. Different LCC parameters were studied to make it market feasible product. This study shows that installing this technology with most appropriate trigger range can reduce annual building energy consumption from 6-8% but still cost of the technology is 3 times the ASHRAE glass, which results in 70-90 years of payback. This study concludes that south orientation saves up to 3-5% of energy and 4-6% of cooling tons while north orientation gives negligible saving using EC glass. LCC parameters show that there is relative change in increasing the net saving for different parameters but none except 50% of the present glass cost is the possible option where significant change is observed.
ContributorsMunshi, Kavish Prakash (Author) / Bryan, Harvey (Thesis advisor) / Reddy, Agami (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2012
Description
The Urban Heat Island (UHI) has been known to have been around from as long as people have been urbanizing. The growth and conglomeration of cities in the past century has caused an increase in the intensity and impact of Urban Heat Island, causing significant changes to the micro-climate and causing imbalances in the temperature patterns of cities. The urban heat island (UHI) is a well established phenomenon and it has been attributed to the reduced heating loads and increased cooling loads, impacting the total energy consumption of affected buildings in all climatic regions. This thesis endeavors to understand the impact of the urban heat island on the typical buildings in the Phoenix Metropolitan region through an annual energy simulation process spanning through the years 1950 to 2005. Phoenix, as a representative city for the hot-arid cooling-dominated region, would be an interesting example to see how the reduction in heating energy consumption offsets the increased demand for cooling energy in the building. The commercial reference building models from the Department of Energy have been used to simulate commercial building stock, while for the residential stock a representative residential model prescribing to IECC 2006 standards will be used. The multiyear simulation process will bring forth the energy consumptions of various building typologies, thus highlighting differing impacts on the various building typologies. A vigorous analysis is performed to see the impact on the cooling loads annually, specifically during summer and summer nights, when the impact of the 'atmospheric canopy layer' - urban heat island (UHI) causes an increase in the summer night time minimum and night time average temperatures. This study also shows the disparity in results of annual simulations run utilizing a typical meteorological year (TMY) weather file, to that of the current recorded weather data. The under prediction due to the use of TMY would translate to higher or lower predicted energy savings in the future years, for changes made to the efficiencies of the cooling or heating systems and thermal performance of the built-forms. The change in energy usage patterns caused by higher cooling energy and lesser heating energy consumptions could influence future policies and energy conservation standards. This study could also be utilized to understand the impacts of the equipment sizing protocols currently adopted, equipment use and longevity and fuel swapping as heating cooling ratios change.
ContributorsDoddaballapur, Sandeep (Author) / Bryan, Harvey (Thesis advisor) / Reddy, Agami T (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2011