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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

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
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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

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
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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

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
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Description
Improving the conditions of schools in many parts of the world is gradually acquiring importance. The Green School movement is an integral part of this effort since it aims at improving indoor environmental conditions. This would in turn, enhance student- learning while minimizing adverse environmental impact through energy efficiency of

Improving the conditions of schools in many parts of the world is gradually acquiring importance. The Green School movement is an integral part of this effort since it aims at improving indoor environmental conditions. This would in turn, enhance student- learning while minimizing adverse environmental impact through energy efficiency of comfort-related HVAC and lighting systems. This research, which is a part of a larger research project, aims at evaluating different school building designs in Albania in terms of energy use and indoor thermal comfort, and identify energy efficient options of existing schools. We start by identifying three different climate zones in Albania; Coastal (Durres), Hill/Pre-mountainous (Tirana), mountainous (Korca). Next, two prototypical school building designs are identified from the existing stock. Numerous scenarios are then identified for analysis which consists of combinations of climate zone, building type, building orientation, building upgrade levels, presence of renewable energy systems (solar photovoltaic and solar water heater). The existing building layouts, initially outlined in CAD software and then imported into a detailed building energy software program (eQuest) to perform annual simulations for all scenarios. The research also predicted indoor thermal comfort conditions of the various scenarios on the premise that windows could be opened to provide natural ventilation cooling when appropriate. This study also estimated the energy generated from solar photovoltaic systems and solar water heater systems when placed on the available roof area to determine the extent to which they are able to meet the required electric loads (plug and lights) and building heating loads respectively.

The results showed that there is adequate indoor comfort without the need for mechanical cooling for the three climate zones, and that only heating is needed during the winter months.
ContributorsDalvi, Ambalika Rajendra (Author) / Reddy, Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Due to extreme summer temperatures that regularly reach 122°F (50°C), cooling energy requirements have been responsible for 70% of peak demand and 45% of total electricity consumption in Kuwait. It is estimated that 50%-60% of electric power is consumed by the residential sector, mostly in detached villas. This study analyzes

Due to extreme summer temperatures that regularly reach 122°F (50°C), cooling energy requirements have been responsible for 70% of peak demand and 45% of total electricity consumption in Kuwait. It is estimated that 50%-60% of electric power is consumed by the residential sector, mostly in detached villas. This study analyzes the potential impact of energy efficiency measures (EEM) and renewable energy (RE) measures on the electric energy requirements of an existing villa built in 2004. Using architectural plans, interview data, and the eQUEST building energy simulation tool, a building energy model (BEM) was developed for a villa calibrated with hourly energy use data for the year 2014. Although the modeled villa consumed less energy than an average Kuwaiti villa of the same size, 26% energy reductions were still possible under compliance with 2018 building codes. Compliance with 2010 and 2014 building codes, however, would have increased energy use by 19% and 3% respectively. Furthermore, survey data of 150 villas was used to generate statistics on rooftop solar area availability. Accordingly, it was found that 78% of the survey sample’s average total rooftop area was not suitable for rooftop solar systems due to shading and other obstacles. The integration of a solar canopy circumvents this issue and also functions as a shading device for outdoor activities and as a protective cover for AC units and water tanks. Combining the highest modeled EEMs and RE measures on the villa, the energy use intensity (EUI) would be reduced to 15 kWh/m2/year from a baseline value of 127 kWh/m2/year, close to net zero. Finally, it was determined that EEMs were able to reduce the entire demand profile whereas RE measures were most effective at reducing demand around mid-day hours. In future studies, more effort should be spent on collecting hourly data from multiple villas to assist in the development of a detailed hourly bottom-up residential energy modeling methodology.
ContributorsAlyakoob, Ali (Author) / Reddy, Agami T (Thesis advisor) / Addison, Marlin (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2020