Due to various reasons data centers have become ubiquitous in our society. Energy costs are significant portion of data centers total lifetime costs which also makes financial sense to operators. This increases huge concern towards the energy costs and environmental impacts of data center. Power costs and energy efficiency are the major challenges front of us.From overall cyber energy used, 15% is used by networking portion ofa data center. Its estimated that the energy used by network infrastructure in a data center world wide is 15.6 billion kWh and is expected to increase to around 50%. Power costs and Energy Consumption plays a major role through out the life time of a data center, which also leads to the increase in financial costs for data center operators and increased usage of power resources. So, resource utilization has become a major issue in the data centers. The main aim of this thesis study is to find the efficient way for utilization of resources and decrease the energy costs to the operators in the data centers using virtualization. Virtualization technology is used to deploy virtual servers on physical servers which uses the same resources and helps to decrease the energy consumption of a data center.

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An electricity demand profile is a graph showing the amount of electricity used by customers over a unit of time. It shows the variation in electricity demand versus time. In the demand profiles, the shape of the graph is of utmost importance. The variations in demand profiles are caused by many factors, such as economic and en- vironmental factors. These variations may also be due to changes in the electricity use behaviours of electricity users. This study seeks to model daily profiles of energy demand in South Africa with a model which is a composition of two de Moivre type models. The model has seven parameters, each with a natural interpretation (one parameter representing minimum demand in a day, two parameters representing the time of morning and afternoon peaks, two parameters representing the shape of each peak, and two parameters representing the total energy per peak). With the help of this model, we trace change in the demand profile over a number of years. The proposed model will be helpful for short to long term electricity demand forecasting.

The economic boom in South Africa following the 1994 democratisation led to increased welfare of the citizens and their purchasing power. This further resulted in increase in electricity consumption. The electricity supply did not increase proportionally to the increase in electricity consumption leading to the 2008 shortage of electricity which nearly damaged the power generating circuit. The literature review has shown that electricity supply and consumption have a positive impact on economic growth. It further showed that employment enhances economic growth. Conversely, it showed that power outages negatively affect economic growth. The research serves to investigate the relationship between electricity supply and economic growth in South Africa and to examine the impact of power outages on economic growth. It also seeks to find the appropriate structure for electricity supply industry that will lead to increase in economic growth. The autoregressive distributed lag (ARDL) bounds approach was used to find the relationship between economic growth, electricity supply, power outages and employment using quarterly data from 2000 to 2012. The ARDL technique was chosen over the conventional models such as Johansen technique for the research because it uses a single reduced form of equation to examine the long run relationship of the variables as opposed to the conventional Johansen test that employs a system of equations. The ARDL technique is also suitable to use to test co-integration when a small sample data is used and does not require the underlying variables to be integrated of similar order. The Vector Error Correction Model (VECM) Granger causality was also employed in the study to establish the causality between economic growth and electricity supply. It was chosen for its ability to develop longer term forecasting, when dealing with an unconstrained model. The results from the ARDL bounds test showed that there is a long run relationship between economic growth, electricity supply, power outages and employment. Based on the causality tests, the findings showed a unidirectional causality flowing from electricity supply to economic growth. This implies that electricity supply affect economic growth in South Africa. The results further showed no causality flowing from economic growth to electricity supply which indicates that when economic growth is booming fewer funds are used for improvement of the electricity generation. Lastly, the results showed that power outages negatively affect economic growth in the long run. To sum up, electricity supply is an important factor for economic growth in South Africa. It is therefore necessary that South Africa must put in place measures aimed at stimulating electricity supply. One of the measures aimed at increasing output of electricity is to unbundle the electricity sector. This process involves allowing entry of the Independent Power Producers (IPPs), Independent System Operator (ISO) and Regional Electricity Distributors (REDs). This will lead to increased supply of electricity and competitively lower prices of electricity. The study further recommends that renewable energy sources should be used to produce electricity instead of coal and nuclear fuels as they failed to produce enough electricity for the nation.

Problem description: The buildings consume significant amounts of energy and are therefore major contributors to the overall CO2 emissions at the present time. The reduction of energy consumption in buildings is a major contribution to the overall control of global warming and to the improvement of sustainability. These reductions are essential as the world faces economic and energy crisis. An important key to the world’s energy problem is sustainable development. Taking the island of Cyprus as a case study, this thesis explores the different building categories and types, analyse building energy models and propose guidelines for the success development of Zero energy buildings in hot climates without compromising the comfort levels of the buildings. Purpose: The ultimate target is to be able to design and operate a building which requires no fossil fuel consumption – the so called “zero energy/carbon (emissions)” building. It is important for all countries to set a national goal in order to achieve zero energy consumption in the building sector and reduce the energy demands. Method: Through the theoretical research the project explored the causes of the problem of building energy, the different types of buildings, the definitions of zero energy buildings in various countries, regulations and standards concerning the buildings energy and all the available technology, methods and materials that can be used in the building sector. In this way the analysis presents the needs of the project and the point of focus during the practical part of the research with simulation of building models. The practical part of the project was the simulation of different building models in order to apply and check the theoretical findings and finally reach conclusions on the development of Zero energy buildings in hot climate countries. During the building simulation a variety of parameters such as the weather, the orientation, the shading methods, the insulation methods, the buildings materials, the glazing, the HVAC systems and building operation profiles were checked in order to find the appropriate combination of factors and achieve the zero energy building goals. Conclusions: This new approach to zero energy building, gives a new perspective to the energy consumption of the building and the indoor environment while also taking environmental impact from the building sector into account. This change in approach is a crucial part of the overall problem of how to achieve the ultimate goal of Zero Energy Buildings and how to convert buildings into “producers” of energy and help solve the world energy problem/crisis.

Orientador: Álvaro de Oliveira D'Antona / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Filosofia e Ciências Humanas / Made available in DSpace on 2018-08-27T22:00:34Z (GMT). No. of bitstreams: 1 DelGuercio_FaustoMartinsFontes_M.pdf: 9224993 bytes, checksum: 3ee5882b7862c19ccf4881a52cdd5fcd (MD5) Previous issue date: 2015 / Resumo: Este trabalho insere-se no campo de pesquisa de População e Ambiente e avalia a influência da composição do domicílio no consumo doméstico de energia, tanto total, quanto per capita. O aspecto priorizado é a heterogeneidade das características demográficas dos filhos ¿ idade e sexo - e o uso energético. A hipótese principal é a de que quanto mais diferirem estas características ¿ por exemplo, maior a diferença de idades e número de alternâncias de sexo nos nascimentos ¿ maior tende a ser o consumo de energia, via alocação em diferentes dormitórios e diminuição na utilização de bens de uso comum (luz elétrica, por exemplo). A fonte de dados utilizada foi o conjunto de 1499 questionários sociodemográficos aplicados em Lucas do Rio Verde-MT, Santarém-PA e Altamira-PA, parte do projeto Desflorestamento da Amazônia e Estrutura das Unidades Domésticas, uma parceria entre o Núcleo de Estudos de População Elza Berquó da Universidade de Campinas (NEPO/UNICAMP) e o Anthropological Center for Training and Research da Universidade de Indiana (ACT/IU). Para verificação das hipóteses foi utilizada regressão linear múltipla, relacionando média e desvio padrão da idade dos filhos, diferença de idade entre o filho mais novo e mais velho, número de alterações de sexo nos nascimentos, densidade de filhos por dormitório e índice de Shannon. Os resultados mostraram que há efeitos no consumo de energia dado o maior grau da heterogeneidade das características demográficas dos filhos, mas que este efeito se manifesta principalmente pelo aumento do número de dormitórios e consequente perda de economia de escala, não aparecendo de forma direta nos coeficientes das equações encontradas. O trabalho mostra, também, que é pertinente a realização de pesquisas na área de população e ambiente sem a ênfase no volume e no crescimento populacional, dando continuidade à análise da variável consumo, já verificada em parte da literatura na área / Abstract: This study is part of the Population and Environment field and evaluates the influence of household composition in the household energy consumption, both as a total and per capita. The highlighted focus is on the heterogeneity of the demographic characteristics of children - age and sex - and energy use. The main hypothesis is that the more these characteristics vary - for instance, the higher the age difference and number of changes in the sex of born children - the higher will be the energy consumption, considering that children are likely to be allocated in different rooms, yielding a lower share of common utilities (such as electricity). Data source was provided by a set of 1499 socio- demographic questionnaires applied in three Brazilian municipalities - Lucas do Rio Verde, MT, Santarém, PA, and Altamira PA - as part of the project Amazon Deforestation and Household Structure, a collaborative research between Núcleo de Estudos Elza Berquó, from the University of Campinas (NEPO/UNICAMP) and the Anthropological Center for Training and Research from the University of Indiana (ACT/IU). Hypothesis verification was made using multiple linear regression, relating mean and standard deviation of the age of children, the age difference between the youngest and the oldest child, number of sex alternations in births, child density per room, and the Shannon index. Results show that energy consumption is affected due to the higher grade of heterogeneity in the demographic characteristics of children, but such effect is mostly noticeable in the number of rooms and the consequent loss of economy scale. However, it is not directly observed in the coefficient of the resulting equations. This work also shows that it is possible to conduct research in the population and environment field without having to include population volume and growth, by keeping the analysis of the variable consumption, which has already been validated by other studies in the field / Mestrado / Demografia / Mestre em Demografia

Please read the abstract in the section 00front of this document / Dissertation (MSc (Electrical Engineering))--University of Pretoria, 2003. / Electrical, Electronic and Computer Engineering / unrestricted

The thesis is concerned with the theme of energy savings in the Building industry. It describes passive house development in detail with a focus on the construction part of buildings with low energy consumption. At first, there is an overview of the actual situation concerning the new European Union’s restrictions and a basic classification of energy efficient buildings is introduced. Further, construction compositions in two energy standards are designed for a few selected construction systems suitable for a passive house. They are evaluated from different points of view and compared to each other. Finally, an estimate of the passive house value is given as well as return of extra investments with regards to energy price increase. Key words The thesis is concerned with the theme of energy savings in the Building industry. It describes passive house development in detail with a focus on the construction part of buildings with low energy consumption. At first, there is an overview of the actual situation concerning the new European Union’s restrictions and a basic classification of energy efficient buildings is introduced. Further, construction compositions in two energy standards are designed for a few selected construction systems suitable for a passive house. They are evaluated from different points of view and compared to each other. Finally, an estimate of the passive house value is given as well as return of extra investments with regards to energy price increase. Key words The thesis is concerned with the theme of energy savings in the Building industry. It describes passive house development in detail with a focus on the construction part of buildings with low energy consumption. At first, there is an overview of the actual situation concerning the new European Union’s restrictions and a basic classification of energy efficient buildings is introduced. Further, construction compositions in two energy standards are designed for a few selected construction systems suitable for a passive house. They are evaluated from different points of view and compared to each other. Finally, an estimate of the passive house value is given as well as return of extra investments with regards to energy price increase.

Dense deployment of small base stations (SBSs) brings new challenges such as growing energy consumption, increased carbon footprint, higher inter-cell interference, and complications in handover management. These challenges can be dealt with by taking advantage of sleep/idle mode capabilities of SBSs, and exploiting the delay tolerance of data applications, as well as utilizing information derived from the statistical distributions of SBSs and user equipment (UE)-SBS associations. This dissertation focuses on the formulation of mathematical models and proposes energy efficient algorithms for small cell networks (SCN). It is shown that delay tolerance of some data applications can be taken advantage of to save energy in SCN. This dissertation introduces practical models to study the performance of delayed access to SCNs. Operational states of SBS are modeled as a Markov chain and their probability distributions are analyzed. Also, it argues that SCN can be operated to save energy during low traffic periods by taking advantage of user equipments' (UEs) delay tolerance in SCN while providing high access probability within bounded transmission range. Dense deployment of SCNs cause an increase in overlapping SBS coverage areas, allowing UEs to establish communication with multiple SBSs. A new load metric as a function of the number of SBSs in UE's communication range is defined, and its statistics are rigorously analyzed. Energy saving algorithms based on aforementioned load metric are developed and their efficiencies are compared. Besides, UE's delay tolerance allows establishing communication with close-by SBSs that are either in fully active mode or in sleeping mode. Improvements in coverage probability and bitrate are analyzed by considering different delay tolerance values for UEs. Key parameters such as UE's communication range are optimized with respect to SBS density and delay tolerance. The fundamental problem of local versus remote edge/fog computing and its inherent tradeoffs are studied from a queuing perspective taking into account user/SBS density, server capacity and latency constraints. The task offloading problem is cast as an M/M/1(c) queue in which CPU intensive tasks arrive according to Poisson process and receive service subject to a tolerable delay. The higher the proportion of locally computed tasks, the less traffic SCN handles between edge processor and UE. Therefore, low utilization of SCN can be interperted as increased spectral efficiency due to low interference and close UE-SBS distance. Tradeoff between delay dependent SCN utilization and spectral efficiency is evaluated at high and low traffic loads.

Indiana University-Purdue University Indianapolis (IUPUI) / Due to the increasing demand from mobile devices for the real-time response of cloud computing services, federated edge learning (FEL) emerges as a new computing paradigm, which utilizes edge devices to achieve efficient machine learning while protecting their data privacy. Implementing efficient FEL suffers from the challenges of devices' limited computing and communication resources, as well as unevenly distributed datasets, which inspires several existing research focusing on device selection to optimize time consumption and data diversity. However, these studies fail to consider the energy consumption of edge devices given their limited power supply, which can seriously affect the cost-efficiency of FEL with unexpected device dropouts. To fill this gap, we propose a device selection model capturing both energy consumption and data diversity optimization, under the constraints of time consumption and training data amount. Then we solve the optimization problem by reformulating the original model and designing a novel algorithm, named E2DS, to reduce the time complexity greatly. By comparing with two classical FEL schemes, we validate the superiority of our proposed device selection mechanism for FEL with extensive experimental results. Furthermore, for each device in a real FEL environment, it is the fact that multiple tasks will occupy the CPU at the same time, so the frequency of the CPU used for training fluctuates all the time, which may lead to large errors in computing energy consumption. To solve this problem, we deploy reinforcement learning to learn the frequency so as to approach real value. And compared to increasing data diversity, we consider a more direct way to improve the convergence speed using loss values. Then we formulate the optimization problem that minimizes the energy consumption and maximizes the loss values to select the appropriate set of devices. After reformulating the problem, we design a new algorithm FCE2DS as the solution to have better performance on convergence speed and accuracy. Finally, we compare the performance of this proposed scheme with the previous scheme and the traditional scheme to verify the improvement of the proposed scheme in multiple aspects.