Evacuated tube solar thermal collector arrays have a wide range of applications. While most of these applications are limited in performance due to relatively low maximum operating temperatures, these collectors can still be useful in low grade thermal systems. An array of fifteen Apricus AP-30 evacuated tube collectors was designed, assembled, and tested on the Arizona State University campus in Tempe, AZ. An existing system model was reprogrammed and updated for increased flexibility and ease of use. The model predicts the outlet temperature of the collector array based on the specified environmental conditions. The model was verified through a comparative analysis to the data collected during a three-month test period. The accuracy of this model was then compared against data calculated from the Solar Rating and Certification Corporation (SRCC) efficiency curve to determine the relative performance. It was found that both the original and updated models were able to generate reasonable predictions of the performance of the collector array with overall average percentage errors of 1.0% and 1.8%, respectively.

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.

This study examines the applicability of high dynamic range (HDR) imagery as a diagnostic tool for studying lighting quality in interior environments. It originates from the limitations in lighting quality assessments, particularly from the problematic nature of measuring luminance contrast--a significant lighting quality definer. In this research, HDR imaging method is studied systematically and in detail via extensive camera calibration tests considering the effect of lens and light source geometry (i.e. vignetting, point spread and modulation transfer functions), in-camera variables (i.e. spectral response, sensor sensitivity, metering mode,), and environmental variables (i.e. ambient light level, surface color and reflectance, light source spectral power distribution) on the accuracy of HDR-image-derived luminance data. The calibration test findings are used to create camera setup and calibration guidelines for future research, especially to help minimize errors in image extracted lighting data. The findings are also utilized to demonstrate the viability of the tool in a real world setting--an office environment combining vertical and horizontal tasks. Via the quasi-experimental setup, the relationship between line of sight and perceived luminance contrast ratios are studied using HDR images. Future research can benefit from the calibration guidelines to minimize HDR-based luminance estimation errors. The proposed tool can be used and tested in different contexts and tasks with varying user groups for revising the former luminance-contrast guidelines as well as surface reflectance recommendations.

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.

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.

With the increasing interest in energy efficient building design, whole building energy simulation programs are increasingly employed in the design process to help architects and engineers determine which design alternatives save energy and are cost effective. DOE-2 is one of the most popular programs used by the building energy simulation community. eQUEST is a powerful graphic user interface for the DOE-2 engine. EnergyPlus is the newest generation simulation program under development by the U.S. Department of Energy which adds new modeling features beyond the DOE-2's capability. The new modeling capabilities of EnergyPlus make it possible to model new and complex building technologies which cannot be modeled by other whole building energy simulation programs. On the other hand, EnergyPlus models, especially with a large number of zones, run much slower than those of eQUEST. Both eQUEST and EnergyPlus offer their own set of advantages and disadvantages. The choice of which building simulation program should be used might vary in each case. The purpose of this thesis is to investigate the potential of both the programs to do the whole building energy analysis and compare the results with the actual building energy performance. For this purpose the energy simulation of a fully functional building is done in eQUEST and EnergyPlus and the results were compared with utility data of the building to identify the degree of closeness with which simulation results match with the actual heat and energy flows in building. It was observed in this study that eQUEST is easy to use and quick in producing results that would especially help in the taking critical decisions during the design phase. On the other hand EnergyPlus aids in modeling complex systems, producing more accurate results, but consumes more time. The choice of simulation program might change depending on the usability and applicability of the program to our need in different phases of a building's lifecycle. Therefore, it makes sense if a common front end is designed for both these simulation programs thereby allowing the user to select either the DOE-2.2 engine or the EnergyPlus engine based upon the need in each particular case.