O objetivo desse trabalho é verificar se os critérios e indicadores das certificações LEED New Construction, LEED Existing Building - Operations and Maintenance, LEED Comercial Interiors, AQUA Escritórios e Edifícios escolares e o regulamento brasileiro PROCEL, podem ser atendidos pelas tecnologias disponíveis no Brasil em termos de lâmpadas, luminárias, reatores (sistemas de iluminação), bem como avaliar se tais critérios e indicadores estão de acordo com as normas da ABNT e/ou normas internacionais. Para verificar os indicadores, foram realizadas simulações através do programa de cálculo Dialux 4.10/2012, utilizando os arquivos fotométricos fornecidos pelos fabricantes mais especificados no Brasil. Foram escolhidos dois estudos de caso para essa verificação, um escritório e uma escola que são ambientes comuns nas certificações e selos de sustentabilidade que serão analisados. Os resultados das simulações mostrarão se é possível obter as certificações e/ou selo de sustentabilidade utilizando a tecnologia disponível referente aos sistemas de iluminação comercializados nos dias de hoje. / The main goal of this dissertation is to verify if Brazilian available technology can meet some certification´s criteria and indicators. The chosen certifications are: LEED New Construction, LEED Existing Building - Operations and Maintenance, LEED Comercial Interiors, AQUA offices and educational buildings and the Brazilian standard PROCEL. Lamps, fixtures, ballasts (lighting systems), were analyzed to check whether these criteria and indicators are in line with the ABNT and / or international standards. To check the indicators, simulations were performed using DIALUX 4.10/2012, a professional light planning software. In these simulations the most specified photometric files provided by the manufacturers were used. To this research two cases were chosen for analysis, an regular office and a school, that are common environments in sustainability standards and certifications. Simulation results will show if it is possible to obtain a certification using the available technology in lighting systems.

Presently, there are concerns that buildings in the USA under-performs in terms of energy efficiency when compared with the original design specifications. A significant percentage of the energy loss in these buildings is associated with the building’s envelope. This study provides a qualitative and analytical understanding of the R-value, which indicates the thermal performance of the elements that make up a building envelope. Infrared thermography is used as a methodology to assess the thermal performance of envelopes of ten buildings on East Tennessee State University Campus. A Fluke Ti25 infrared hand-held camera and a DJI phantom-2 drone mounted with FLIR Vue Pro infrared camera were used for data collection. Data analyses were carried out using ‘Smartview’ and ‘FLIR Reporter Pro’ software. The data analyses revealed energy loss, insulation deficiencies, the associated energy costs of the inefficiencies and the potential savings that could result from correcting these deficiencies in the evaluated building’s envelopes.

Propelled by the explosive increases in mobile data traffic volume, existing wireless technologies are stretched to their capacity limits. There is a tremendous need for an expansion in system capacity and an improvement on energy efficiency. In addition, wireless network will support more and more multimedia services and applications, in which user experience has been always an important factor in evaluating the overall network performance. In order to keep pace with this explosion of data traffic and to meet the emerging quality of experience needs, wireless heterogeneous networks have been introduced as a promising network architecture evolution of the traditional cellular network. In this dissertation, we explore video quality-aware spectrum efficiency and energy efficiency in wireless heterogeneous networks|the potentials and the associated technical challenges. In particular, aiming to significantly enhance spectrum efficiency, we need to tackle the interference issue, which is exacerbated in heterogeneous network due to ultra dense node deployment as well as heterogeneity nature of various nodes. Specifically, werst study an optimal intra-cell inter-tier cooperation to mitigate interference between high power nodes and low power nodes. Together with cooperation, optimal mobile association and resource allocation schemes are also intensively investigated in heterogeneous network to achieve system load balancing so that bandwidth at high power and low power nodes can be utilized in the optimal way. The proposed scheme can greatly alleviate inter-tier interference and significantly increase overall system spectrum efficiency in a heterogeneous network. We then further apply advanced algorithms such as precoding, and non-orthogonal multiple access into intra-cell inter-tier cooperation so that the overall system spectrum efficiency and user experience are even more improved. When supporting a video type application in such a heterogeneous network, considering only spectrum efficiency is far from enough as video application is bandwidth consuming, battery consuming, and quality demanding. We develop a video quality-aware spectrum and energy efficiency resource allocation scheme in a wireless heterogeneous network and propose novel performance metrics to establish fundamental relationships among spectrum efficiency, energy efficiency, and quality of experience. Extensive simulations are conducted to evaluate the trade-o performance among three performance metrics.

This licentiate thesis presents a new way of understanding Electric Power. The new perspective on Electric Power highlights the similarities between our banking system and our power system. The two different systems share a common abstraction. In the case of the banking system this abstraction is fully accepted. In the case of the power system this abstraction is not yet fully accepted. This thesis aims to clarify this abstraction and show the parallelism between the two systems and the two abstractions. This thesis examines what the Product Electricity really is. What is it, in reality, we sign a power contract to buy and pay for, and how is this product transferred to us? This new understanding challenges the old, physical understanding of Electric Power. Understanding the similarity between our banking system and our power system becomes important when we examine our Power Markets, and it becomes absolutely vital to understand for those investing in new power generation. In no way does this new understanding of Electric Power question or challenge the physics behind power generation and power transfer. Maxwell’s equations holds true. The laws of Ohm and Kirchhoff are still the laws by which the electrical and power system engineers must abide. But when it comes to the Product Electricity, the product traded on our Power Markets, the product that we sign power contracts to buy and pay for, there is a major difference. The new understanding challenges the old quite dramatically. It does in fact show that the old, physical perspective on the Product Electricity is flawed and has been a misconception for over a century. My primary goal in this thesis is to thoroughly explain the new perspective and by so doing clarify and dissolve the old misconception of what the Product Electricity actually is. The scientific theory of the Greenhouse Effect now has over 195 years of published peer-reviewed science.[[i]] The threat of accelerating Climate Change is a scientifically solid fact. The Paris agreement must be met. My second goal with this thesis is to make credible that an electrification of our society is a possible and viable option. The possibility of a swift energy transition from fossil fuels to renewable electricity is made more likely, and more viable, thanks to the new understanding of what Electric Power really is, because now we have the de facto choice of not consuming any fossil power. © Per Ribbing, April 2019 [i] Joseph Fourier, Remarques générales sur les températures du globe terrestre et des espaces planétaires”, Annales de Chimie et de Physique, 27, 1824, p. 136-167

Energy efficient houses benefit communities not only to provide renewable energy shares and generating surplus electricity supporting local economic development. Also, residents in energy efficient houses have less energy usage that reduces household budget expenses. However, one of the obstacles of energy efficient technology installment of residential buildings is high investment cost, which can be solved with the usage of modular housing. In Europe, housing costs have a large share, especially for Sweden, housing expenses is a burden mostly for people who are at the risk of poverty. Also, high investment costs of energy efficient housing are combined with high construction prices leading a large share of budgets and effort to make houses affordable for low income groups. This study develops a scenario to find solutions for affordable housing problem in Sweden with a design proposal. The aim of this study is to investigate if there are ways of achieving socio-economic mix by the production of energy efficient affordable housing and urban gardening to develop a strategy for resource efficiency in Jakobsgårdarna. To achieve the aim, energy efficient affordable housing designed as modular units to achieve a local economic development. This study uses a design-based research method consisting of learning from background cases to transfer lesson learned in design phase of the sustainable neighborhood consisting of energy efficient technologies. Background cases were analyzed with literature review to define sustainable neighborhood, which was then used to develop a hypothesis. Findings of this thesis generates definition of sustainability tools consisting of a collaborative ownership; designing common kitchens; producing electricity and biogas from renewable energy sources; practicing urban agriculture; managing waste and storm and methods to cross subsidize energy efficient affordable housing production. The outcome of this research provides a sustainable neighborhood design proposal for Jacobsgårdarna, Borlänge.

Cellular network expansion in rural areas has been traditionally slower than in dense urban areas. Area coverage in rural areas is fundamentally limited by the deployment cost for the operator. The 5th generation new radio (5G NR) network is designed to deliver unprecedented levels of capacity, high data rates, low latency and high reliability anytime and anywhere. The focus of 5G NR development is on relatively short-range communication using high frequency bands (e.g. mmWave-length) where lots of spectrum is available. For extremely long-range communication (e.g. in rural areas) high frequency bands are less suitable due to the high signal attenuation. One way to increase coverage in rural areas is to allow end users to deploy their own personal local hot-spot nodes that connect to the cellular network. A personal rural hot-spot can make use of higher transmission power and have better antennas than what normal user terminals can be equipped with. This thesis work will study the impacts of ”user deployed rural hot-spots” on the network like how much the network energy consumption can be decreased, what is the effect of discontinuation transmission (DTX) on network sleep mode and how inter site distance (ISD) can be increased to increase the coverage. One way to increase rural coverage by using the user deployed hot-spot is to reduce the network energy consumption for network operators and results show that by using user deployed hot-spots (enhanced UE) decreased the network energy consumption and while enhancing the BS configuration will require additional capital expense (CAPEX) investment for the network operators. User deployed hot-spot provide better connectivity for the users that are lying in network edges and helps to increase the inter site distance (ISD) of wireless networks.

Sustainable development reduces construction waste by 43%, generating 50% cost savings. Residential construction executives lacking adequate knowledge regarding the benefits of sustainable development practices are at a competitive disadvantage. Drawing from the diffusion of innovation theory, the purpose of this qualitative case study was to explore knowledge acquisition within the bounds of sustainable residential construction. The purposive sample size of 11 executive decision makers fulfilled the sample size requirements and enabled the extraction of meaningful data. Participants were members of the National Home Builders Association and had experience of a minimum of 5 years in residential construction. The research question addressed how to improve knowledge acquisition relating to the cost benefits of building green homes and increase the adoption rate of sustainable development among residential builders. Data were collected via semistructured telephone interviews, field observation, and document analysis. Transcribed data were validated via respondent validation, coded into 5 initial categories aligned to the focus of the research, then reduced to 3 interlocking themes of environment, competitive advantage, and marketing. Recommendations include developing comprehensive public policies, horizontal and vertical communications networks, and green banks to capitalize sustainable development programs to improve the diffusion of green innovation as a competitive advantage strategy. Business leaders could benefit from this data by integrating sustainable development practices into their business processes. Sustainable development reduces operational costs, increases competitive advantage for builders, and reduces greenhouse gas emissions. Implications for social change increase energy independence through conservation and developing a legislative policy template for comprehensive energy strategies. A comprehensive energy strategy promotes economic development, technological gains in all business sectors within the energy industry, and reduces energy costs for consumers.

Dans un contexte où les ressources énergétiques sont moindres et la demande en termes de débit de communication est forte, il est intéressant de proposer des solutions techniques au niveau de la couche physique permettant d’optimiser la consommation énergétique de systèmes. Actuellement, pour une localisation précise et un transfert de données entre voie et trains efficace, la signalisation ferroviaire exploite des balises disposées entre les rails. La durée possible de la communication entre trains et balises s’avère très brève et n’est effective que lorsque le train passe juste au-dessus de la balise. Celle-ci reste en état de veille jusqu’à ce que le train la télé alimente lors de son passage. Le temps de communication utile entre le train et la balise s’établit à 3-4 ms pour un train roulant à 300 km/h. Par conséquent, plusieurs équipements consécutifs doivent être installés si l’on veut accroître la durée d’échange ou encore la quantité de données échangées. En outre, le fait d’émettre continument un puissant signal de télé alimentation radiofréquence non exploité depuis tous les trains en circulation, la difficulté de maintenance liée à la présence de cet équipement entre les rails, ainsi que la portée et donc la capacité de communication réduites des balises actuelles constituent autant de limitations que nous tentons de pallier avec ce nouvel équipement. Dès lors, nous développons une nouvelle génération de balise ferroviaire fondée sur un lien radiofréquence qui possède une portée atteignant quelques mètres, nettement plus importante que celle exploitable actuellement. Cette balise est également située en bord de voie et non entre les rails pour des questions de facilité de maintenance. Nous utilisons une technique de focalisation du signal émis depuis la balise vers l’antenne embarquée sur le train. Puisque la distance de communication balise au sol - interrogateur est portée à quelques mètres, la télé alimentation par couplage inductif actuelle n’est plus possible. Disposer d’une infrastructure centrale pour alimenter toutes les balises présentes sur le réseau n’est pas réaliste non plus. Une solution raisonnable et économe consiste à générer de l’énergie électrique basse tension localement en utilisant des énergies renouvelables (solaire, éolienne…), et en limitant le plus possible la consommation d’énergie de l’électronique de la balise. Dans cette optique, la contribution scientifique présentée consiste à développer et à optimiser, en termes d’énergie consommée, la couche physique de communication de cet équipement. / In railway signaling, accurate and safe localization of trains is of paramount importance for the safe exploitation of railway networks. Therefore, train odometry has received considerable interest. Usually, train odometers manage different embarked sensors including wheel counters and Doppler radars that compute the position and the speed of the trains. However, as trains move, these proprioceptive sensors accumulate drifts and, as a consequence, train localization accuracy is compromised after several kilometers. In order to fix this drift problem, railway signaling uses beacons installed at ground, on the track, between the rails. Installed every several kilometers, they transmit absolute localization information to trains passing over them thus, bringing back locally the drifts to zero. These beacons constitute major components of railway signaling and also one of the very last equipment installed between the rails. Existing railway beacons are placed on the rails for two main reasons. First of all, since in these conditions the radio link between the train and the beacons remains very short, in the order of a few tens of centimeters, placing the beacons on the rails is very helpful to deliver an accurate local absolute localization to the train. Moreover using this very short radio communication range, while passing over them, trains can supply electrical energy to the beacons by magnetically coupling radiofrequency energy from the train to the beacon. This radiofrequency energy is detected and converted in DC power supply to feed the beacon electronics. This very short range leads to a satisfactory transfer of energy between train and beacon. As indicated previously, beacons can just be position indicators; however, they can also handle communication between grounds and trains using a peer to peer radio link. In this case, communication is only active when the train passes over the beacons, thus, the effective communication time is very short. As another major drawback of this particular implementation between the rails, track maintenance requires disassembling the beacons and then repositioning them safely and accurately.

Mobile sensing applications (MSAs) are an emerging class of applications that process continuous sensor data streams to make time-sensitive inferences. Representative application domains range from environmental monitoring, context-aware services to recognition of physical activities and social interactions. Example applications involve city air quality assessment, indoor localization, pedometer and speaker identification. The common application workflow is to read data streams from the sensors (e.g, accelerometers, microphone, GPS), extract statistical features, and then present the inferred high-level events to the user. MSAs in the healthcare domain especially draw a significant amount of attention in recent years because sensor-based data collection and assessment offer finer-granularity, timeliness, and higher accuracy in greater quantity than traditional, labor-intensive, data gathering mechanisms in use today, e.g., surveys methods. The higher fidelity and accuracy of the collected data expose new research opportunities, improve the reliability and accuracy of medical decisions, and empower users to manage personal health more effectively. Nonetheless, a critical challenge to practical deployment of MSAs in real-world is to effectively manage limited resources of mobile platforms to meet stringent quality of service (QoS) requirements in terms of processing throughput and delay while ensuring long term robustness. To address the challenge, we model MSAs in dataflows as a graph of processing elements that are connected by communication channels. The processing elements may execute in parallel as long as they have sufficient data to process. A key feature of the dataflow model is that it explicitly capture parallelism and data dependencies between processing elements. Based on the graph composition, we first proposed CSense, a stream-processing toolkit for robust and high-rate MSAs. In this work, CSense provide a simple language for developers to describe their sensing flow without the need to deal with system intricacy, such as memory allocation, concurrency control and power management. The results show up to 19X performance difference may be achieved automatically compared with a baseline using the default runtime concurrency and memory management. Following this direction, we saw the opportunities that MSAs can be significantly improved from the perspective of memory performance and energy efficiency in view of the iterative execution. Therefore, we next focus on optimizing the runtime memory management through compile time analysis. The contribution is a stream compiler that captures the whole program memory behavior to generate an efficient memory layout for runtime access. Experiments show that our memory optimizations reduce memory footprint by as much as 96% while matching or improving the performance of the StreamIt compiler with cache optimizations enabled. On the other hand, while there is a significant body of work that has focused on optimizing the throughput or latency of processing sensor streams, little to no attention has been given to energy efficiency. We proposed an accurate offline energy prediction model for MSAs that leverages the pipeline structure and iterative execution nature to search for the most energy saving batching configuration w.r.t. a deadline constraint. The developers are expected to visualize the energy delay trade-off in the parameter space without runtime profiling. The evaluation shows the worst-case prediction errors are about 7% and 15% for energy and latency respectively despite variable application workloads.

Heating, ventilating and air-conditioning (HVAC) system is complex non-linear system with multi-variables simultaneously contributing to the system process. It poses challenges for both system modeling and performance optimization. Traditional modeling methods based on statistical or mathematical functions limit the characteristics of system operation and management. Data-driven models have shown powerful strength in non-linear system modeling and complex pattern recognition. Sufficient successful applications of data mining have proved its capability in extracting models accurately describing the relation of inner system. The heuristic techniques such as neural networks, support vector machine, and boosting tree have largely expanded to the modeling process of HVAC system. Evolutionary computation has rapidly merged to the center stage of solving the multi-objective optimization problem. Inspired from the biology behavior, it has shown the tremendous power in finding the optimal solution of complex problem. Different applications of evolutionary computation can be found in business, marketing, medical and manufacturing domains. The focus of this thesis is to apply the evolutionary computation approach in optimizing the performance of HVAC system. The energy saving can be achieved by implementing the optimal control setpoints with IAQ maintained at an acceptable level. A trade-off between energy saving and indoor air quality maintenance is also investigated by assigning different weights to the corresponding objective function. The major contribution of this research is to provide the optimal settings for the existing system to improve its efficiency and different preference-based operation methods to optimally utilize the resources.