This dissertation examines the employment impacts of investments in renewable energy and energy efficiency in the U.S. A broad expansion of the use of renewable energy in place of carbon-based energy, in addition to investments in energy efficiency, comprise a prominent strategy to slow or reverse the effects of anthropogenic climate change. This study first explores the literature on the employment impacts of these investments. This literature to date consists mainly of input-output (I-O) studies or case studies of renewable energy and energy efficiency (REEE). Researchers are constrained, however, by their ability to use the I-O model to study REEE, since currently industrial codes do not recognize this industry as such. I develop and present two methods to use the I-O framework to overcome this constraint: the synthetic and integrated approaches. In the former, I proxy the REEE industry by creating a vector of final demand based on the industrial spending patterns of REEE firms as found in the secondary literature. In the integrated approach, I collect primary data through a nationwide survey of REEE firms and integrate these data into the existing I-O tables to explicitly identify the REEE industry and estimate the employment impacts resulting from both upstream and downstream linkages with other industries. The size of the REEE employment multiplier is sensitive to the choice of method, and is higher using the synthetic approach than using the integrated approach. I find that using both methods, the employment level per $1 million demand is approximately three times greater for the REEE industry than for fossil fuel (FF) industries. This implies that a shift to clean energy will result in positive net employment impacts. The positive effects stem mainly from the higher labor intensity of REEE in relation to FF, as well as from higher domestic content and lower average wages. The findings suggest that as we transition away from a carbon-based energy system to more sustainable and low-carbon energy sources, approximately three jobs will be created in clean energy sectors for each job lost in the fossil fuel sector.

This thesis examines daylight utilization in Nordic home environments without artificial lighting. One of the aims is to save energy and create healthy living spaces that fully harness daylight benefits. The research question focuses on how to effectively use daylight as the sole illumination source for functional, comfortable, and aesthetically pleasing homes. Existing guidelines overlook the importance of daylight in homes and fail to consider human preferences, resulting in a research gap. To address this, this thesis conducts an analysis of three existing buildings and presents a design project that specifically focuses on building orientation, openings, and materials. Daylight calculations are conducted based on the proposed design. The key findings emphasize that a home without artificial light can be easily achieved during the summer months through strategic room placement, incorporation of skylight windows, and utilization of various window types. Material selection is crucial in creating a comfortable atmosphere while maximizing daylight transmission for optimal lighting. These findings highlight the importance of considering unique daylight conditions in Nordic countries and aligning designs with individual preferences. The study contributes by emphasizing the need for optimal daylight solutions that enhance energy efficiency, well-being, and user satisfaction in home environments.

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The houses which were built during the million programmes are now facing extensiverenovations and refurbishment, some have also been demolished. The houses that still standtoday have now reached their lifespan, this however, does not necessarily mean that theyshould be demolished. The construction industry has, during these last years, flourishedimmensely. Resources, methods, and construction techniques are constantly evolving and arenow being applied when working with renovations of old buildings. And it is now resulting inhouses that are durable and energy efficient, which enables them to endure even longer.Unlike new buildings, renovations are more complex and require wider knowledge in severaldifferent areas to address the problems in the best possible way. In addition to the technicalaspects, it also shows that the preservation of cultural-historical aspects, for the millionprogramme houses, must be considered when it comes to remodelling.In this study, it is investigated how a renovation is carried out and which measures are usedon these houses in terms of technology, sustainability, and the preservation of theenvironment. In addition, how such buildings are designed in regard to their culturalhistoricalvalue and influence.

Yes / Next-generation cellular systems like fth generation (5G) is are expected to experience tremendous tra c growth. To accommodate such tra c demand, there is a need to increase the network capacity that eventually requires the deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a signi cant amount of energy. As a result, cloud radio access networks (C-RAN) have been proposed as anenergy e cient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation technique model is to switch o idle baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low tra c periods and 12% during peak tra c periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.

With a nation-wide aim toward reducing operational energy costs in buildings, it is important to understand the dynamics of controlled heating, cooling, and air circulation of an individual room, the "One-Room Model Problem." By understanding how one most efficiently regulates a room's climate, one can use this knowledge to help develop overall best-practice power reduction strategies. A key toward effectively analyzing the "One-Room Model Problem" is to understand the capabilities and limitations of existing commercial tools designed for similar problems. In this thesis we develop methodology to link commercial Computational Fluid Dynamics (CFD) software COMSOL with standard computational mathematics software MATLAB, and design controllers that apply inlet airflow and heating or cooling to a room and investigate their effects. First, an appropriate continuum model, the Boussinesq System, is described within the framework of this problem. Next, abstract and weak formulations of the problem are described and tied to a Finite Element Method (FEM) approximation as implemented in the interface between COMSOL and MATLAB. A methodology is developed to design Linear Quadratic Regulator (LQR) controllers and associated functional gains in MATLAB which can be implemented in COMSOL. These "closed-loop" methods are then tested numerically in COMSOL and compared against "open-loop" and average state closed-loop controllers. / Ph. D.

Extraordinary improvements in computing performance, density, and capacity have driven rapid increases in system energy consumption, motivating the need for energy-efficient performance. Harnessing the collective computational capacity of thousands of these systems can consume megawatts of electrical power, even though many systems may be underutilized for extended periods of time. At scale, powering and cooling unused or lightly loaded systems can waste millions of dollars annually. To combat this inefficiency, we propose system software, control systems, and architectural techniques to improve the energy efficiency of high-capacity memory systems while preserving performance. We introduce and discuss several new application-transparent, memory management algorithms as well as a formal analytical model of a power-state control system rooted in classical control theory we developed to proportionally scale memory capacity with application demand. We present a prototype implementation of this control-theoretic runtime system that we evaluate on sequential memory systems. We also present and discuss why the traditional performance-motivated approach of maximizing interleaving within memory systems is problematic and should be revisited in terms of power and thermal efficiency. We then present power-aware control techniques for improving the energy efficiency of symmetrically interleaved memory systems. Given the limitations of traditional interleaved memory configurations, we propose and evaluate unorthodox, asymmetrically interleaved memory configurations. We show that when coupled with our control techniques, significant energy savings can be achieved without sacrificing application performance or memory bandwidth. / Ph. D.