Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Includes bibliographical references (leaves 145-146). / Natural lighting serves several important functions in buildings. The visual power of a shaft of sunlight penetrating a dark space or the visual beauty of a stained window has long been recognized by architects and designers. The primary focus of this study is a more pragmatic one. Besides strong concern for the qualitative aspects of daylight design, methods of daylight and solar radiation modulation for commercial structures are explored and evaluated to offset electric lighting load or heat load requirements. An investigation into the energy use patterns of these building types - offices, schools, hospitals, warehouses and other "commercial" structures lead to the conclusion, that artificial lighting represents the most significant portion of total electrical energy consumption. This study considers daylight and solar design in several ways: First, it documents daylight and solar radiation fundamentals and their visual and thermal impact on human comfort. It reviews a series of traditional design tools and architectural elements to modulate and control daylight and solar radiation. Second, it proposes and evaluates an innovative daylight introduction system - a particular "lightshelf" configuration integrated as an architectural element - with careful consideration of the following criteria: - acceptance of the full range of seasonal sun altitude angles through a curved configuration of the reflecting lightshelf-surface to redirect incident radiation onto the same "reference-range" of the interior ceiling without and adjustments - modulation of daylight introduction and radiation diffusion for solar storage in distributed mass - penetration of daylight into a space beyond traditional limits of 15 to 20 feet for daylight utilization - design of the light introducing "component" as an architectural element and its integration into a modular window wall consisting of prefabricated lightweight concrete wall elements - evaluation of qualitative and quantitative performance of proposed system· - illumination and solar heat gain tradeoffs - integration of daylight design with dynamic artificial lighting system Third, analytical and experimental methods for daylight design are explored and an entensive daylight model experiment is executed to enable the qualitative and quantitative assessment of the proposed system. Finally, a number of case studies with innovative daylight introduction methods applied in praxis, are documented. / by Hans-Joachim Schlereth. / M.Arch.

With the commercial and institutional building sectors using approximately 29% and 34% of all electrical energy consumption in Canada and the United States, respectively, saving electrical energy in commercial and institutional buildings represents an important chal- lenge for both the environment and the energy consumer. Concurrently, a rapid decline in the cost of microprocessing and communication has enabled the profileration of smart me- ters, which allow a customer to monitor energy usage every hour, 15 minutes or even every minute. Algorithmic analysis of this stream of meter readings would allow 1) a building operator to predict the potential cost savings from implemented energy savings measures without engaging the services of an expensive energy expert; and 2) an energy expert to quickly obtain a high-level understanding of a building’s operating parameters without a time-consuming and expensive site visit. This thesis develops an algorithm that takes as input a stream of building meter data and outputs a building’s operating parameters. This output can be used directly by an energy expert to assess a building’s performance; it can also be used as input to other algorithms or systems, such as systems that 1) predict the cost savings from a change in these operating parameters; 2) benchmark a portfolio of building; 3) create baseline models for measurement and verification programs; 4) detect anomalous building behaviour; 5) provide novel data visualization methods; or 6) assess the applicability of demand response programs on a given building. To illustrate this, we show how operating parameters can be used to estimate potential energy savings from energy savings measures and predict building energy consumption. We validate our ap- proach on a range of commercial and institutional buildings in Canada and the United States; our dataset consists of 10 buildings across a variety of geographies and industries and comprises over 21 years of meter data. We use K-fold cross-validation and benchmark our work against a leading black-box prediction algorithm; our model offers comparable prediction accuracy while being far less complex.

Thesis (M. Phil.)--University of Hong Kong, 1987.

published_or_final_version / Surveying / Master / Master of Philosophy

With the commercial and institutional building sectors using approximately 29% and 34% of all electrical energy consumption in Canada and the United States, respectively, saving electrical energy in commercial and institutional buildings represents an important chal- lenge for both the environment and the energy consumer. Concurrently, a rapid decline in the cost of microprocessing and communication has enabled the profileration of smart me- ters, which allow a customer to monitor energy usage every hour, 15 minutes or even every minute. Algorithmic analysis of this stream of meter readings would allow 1) a building operator to predict the potential cost savings from implemented energy savings measures without engaging the services of an expensive energy expert; and 2) an energy expert to quickly obtain a high-level understanding of a building’s operating parameters without a time-consuming and expensive site visit. This thesis develops an algorithm that takes as input a stream of building meter data and outputs a building’s operating parameters. This output can be used directly by an energy expert to assess a building’s performance; it can also be used as input to other algorithms or systems, such as systems that 1) predict the cost savings from a change in these operating parameters; 2) benchmark a portfolio of building; 3) create baseline models for measurement and verification programs; 4) detect anomalous building behaviour; 5) provide novel data visualization methods; or 6) assess the applicability of demand response programs on a given building. To illustrate this, we show how operating parameters can be used to estimate potential energy savings from energy savings measures and predict building energy consumption. We validate our ap- proach on a range of commercial and institutional buildings in Canada and the United States; our dataset consists of 10 buildings across a variety of geographies and industries and comprises over 21 years of meter data. We use K-fold cross-validation and benchmark our work against a leading black-box prediction algorithm; our model offers comparable prediction accuracy while being far less complex.

Thesis (M.S.)--Florida State University, 2005. / Advisor: Dr. Nur Yazdani, Florida State University, College of Engineering, Dept. of Civil and Environmental Engineering. Title and description from dissertation home page (viewed June 28, 2005). Document formatted into pages; contains xv, 180 pages. Includes bibliographical references.

Thesis (M.Phil.) - University of Queensland, 2002. / Includes bibliographical references.

Thesis (M.Int.(Prof.))--University of Pretoria, 2005. / Includes summary. Includes bibliography. Available on the Internet via the World Wide Web.

Thesis (Ph.D. in Mechanical Engineering) -- University of Dayton. / Title from PDF t.p. (viewed 10/06/09). Advisor: Reza Kashani. Includes bibliographical references (p. 98-102).

Carbon emissions generated by the building sector have come under stricter limits with the amendments to Approved Document L: Conservation of Fuel and Power of the building regulations for England and Wales. Building designs are now checked to ensure that new constructions have the designed capabilities to operate with a higher standard of efficiency. However, there are currently no means of ensuring that the mandatory improvements in design and construction are actually translating into real life improvements during the actual operation of the building. Assessment methodologies such as the Display Energy Certificate are applied annually. The large interval between audits has the potential risk that poor performance may go unnoticed for prolonged periods of time. Real time assessment of energy performance that is linked to legislative requirements would aid the process of ensuring reductions in carbon emissions occur in reality. Evaluating the energy performance in real time is not a straight forward task; commercial buildings are complex nonlinear dynamic systems with a number of operating states, functions and features. These factors need to be taken into consideration for the fair appraisal of energy performance. Condition monitoring has been applied extensively to the field of machine health, in which the state of a system is determined through measuring the parameters that are indicative of its health. Within this thesis, a unique method of real time energy performance has been developed along with the implementation of two condition monitoring strategies for the purposes of state evaluation and fault detection and diagnosis. Kernel based dimensionality techniques have recently gained popularity as a means of modelling nonlinear systems. It was found that the application of nonlinear condition monitoring strategies for determination of building state was proficient in determining slow developing faults and abrupt changes in building state. However, the occurrences of non-acceptable incipient changes in state were harder to detect. Hence the state evaluation techniques were complemented with component level fault detection and diagnosis techniques. These techniques have the combined ability to address the requirement for assessing the state of operation within a building to allow for fair appraisal of the energy performance.