819 resultados para Energy consumption data sets


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We study the residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price elasticity of electricity demand in the -0.860 to -0.667 range, while the own price elasticity of gas demand is -0.693 to -0.566. These results are robust to a variety of checks. Contrary to earlier literature (Metcalf and Hassett, 1999; Reiss and White, 2005), we find no evidence of significantly different elasticities across households with electric and gas heat. The price elasticity of electricity demand declines with income, but the magnitude of this effect is small. These results are in sharp contrast to much of the literature on residential energy consumption in the United States, and with the figures used in current government agency practice. Our results suggest that there might be greater potential for policies which affect energy price than may have been previously appreciated. (C) 2011 Elsevier B.V. All rights reserved.

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The power output from a wave energy converter is typically predicted using experimental and/or numerical modelling techniques. In order to yield meaningful results the relevant characteristics of the device, together with those of the wave climate must be modelled with sufficient accuracy.

The wave climate is commonly described using a scatter table of sea states defined according to parameters related to wave height and period. These sea states are traditionally modelled with the spectral distribution of energy defined according to some empirical formulation. Since the response of most wave energy converters vary at different frequencies of excitation, their performance in a particular sea state may be expected to depend on the choice of spectral shape employed rather than simply the spectral parameters. Estimates of energy production may therefore be affected if the spectral distribution of wave energy at the deployment site is not well modelled. Furthermore, validation of the model may be affected by differences between the observed full scale spectral energy distribution and the spectrum used to model it.

This paper investigates the sensitivity of the performance of a bottom hinged flap type wave energy converter to the spectral energy distribution of the incident waves. This is investigated experimentally using a 1:20 scale model of Aquamarine Power’s Oyster wave energy converter, a bottom hinged flap type device situated at the European Marine Energy Centre (EMEC) in approximately 13m water depth. The performance of the model is tested in sea states defined according to the same wave height and period parameters but adhering to different spectral energy distributions.

The results of these tests show that power capture is reduced with increasing spectral bandwidth. This result is explored with consideration of the spectral response of the device in irregular wave conditions. The implications of this result are discussed in the context of validation of the model against particular prototype data sets and estimation of annual energy production.

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We examine the effect of energy efficiency incentives on household energy efficiency home improvements. Starting in February 2007, Italian homeowners have been able to avail themselves of tax credits on the purchase and installation costs of certain types of energy efficiency renovations. We examine two such renovations—door/window replacements and heating system replacements—using multi-year cross-section data from the Italian Consumer Expenditure Survey and focusing on a narrow period around the introduction of the tax credits. Our regressions control for dwelling and household characteristics and economy-wide factors likely to influence the replacement rates. The effects of the policy are different for the two types of renovations. With window replacements, the policy is generally associated with a 30 % or stronger increase in the renovation rates and number of renovations. In the simplest econometric models, the effect is not statistically significant, but the results get stronger when we allow for heterogeneous effects across the country. With heating system replacements, simpler models suggest that the tax credits policy had no effect whatsoever or that free riding was rampant, i.e., people are now accepting subsidies for replacements that they would have done anyway. Further examination suggests a strong degree of heterogeneity in the effects across warmer and colder parts of the country, and effects in the colder areas that are even more pronounced than those for window replacements. These results should, however, be interpreted with caution due to the low rates of renovations, which imply that the effects are estimated relatively imprecisely.

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Bioenergy is a key component of the European Union long term energy strategy across all sectors, with a target contribution of up to 14% of the energy mix by 2020. It is estimated that there is the potential for 1TWh of primary energy from biogas per million persons in Europe, derived from agricultural by-products and waste. With an agricultural sector that accounts for 75% of land area and a large number of advanced engineering firms, Northern Ireland is a region with considerable potential for an integrated biogas industry. Northern Ireland is also heavily reliant on imported fossil fuels. Despite this, the industry is underdeveloped and there is a need for a collaborative approach from research, business and policy-makers across all sectors to optimise Northern Ireland’s abundant natural resources. ‘Developing Opportunities in Bio-Energy’ (i.e. Do Bioenergy) is a recently completed project that involved both academic and specialist industrial partners. The aim was to develop a biogas research action plan for 2020 to define priorities for intersectoral regional development, co-operation and knowledge transfer in the field of production and use of biogas. Consultations were held with regional stakeholders and working groups were established to compile supporting data, decide key objectives and implementation activities. Within the context of this study it was found that biogas from feedstocks including grass, agricultural slurry, household and industrial waste have the potential to contribute from 2.5% to 11% of Northern Ireland’s total energy consumption. The economics of on-farm production were assessed, along with potential markets and alternative uses for biogas in sectors such as transport, heat and electricity. Arising from this baseline data, a Do Bioenergy was developed. The plan sets out a strategic research agenda, and details priorities and targets for 2020. The challenge for Northern Ireland is how best to utilise the biogas – as electricity, heat or vehicle fuel and in what proportions. The research areas identified were: development of small scale solutions for biogas production and use; solutions for improved nutrient management; knowledge supporting and developing the integration of biogas into the rural economy; and future crops and bio-based products. The human resources and costs for the implementation were estimated as 80 person-years and £25 million respectively. It is also clear that the development of a robust bio-gas sector requires some reform of the regulatory regime, including a planning policy framework and a need to address social acceptance issues. The Action Plan was developed from a regional perspective but the results may be applicable to other regions in Europe and elsewhere. This paper presents the methodology, results and analysis, and discussion and key findings of the Do Bioenergy report for Northern Ireland.

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Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence,purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44%.

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Power, and consequently energy, has recently attained first-class system resource status, on par with conventional metrics such as CPU time. To reduce energy consumption, many hardware- and OS-level solutions have been investigated. However, application-level information - which can provide the system with valuable insights unattainable otherwise - was only considered in a handful of cases. We introduce OpenMPE, an extension to OpenMP designed for power management. OpenMP is the de-facto standard for programming parallel shared memory systems, but does not yet provide any support for power control. Our extension exposes (i) per-region multi-objective optimization hints and (ii) application-level adaptation parameters, in order to create energy-saving opportunities for the whole system stack. We have implemented OpenMPE support in a compiler and runtime system, and empirically evaluated its performance on two architectures, mobile and desktop. Our results demonstrate the effectiveness of OpenMPE with geometric mean energy savings across 9 use cases of 15 % while maintaining full quality of service.

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The ever-growing energy consumption in mobile networks stimulated by the expected growth in data tra ffic has provided the impetus for mobile operators to refocus network design, planning and deployment towards reducing the cost per bit, whilst at the same time providing a signifi cant step towards reducing their operational expenditure. As a step towards incorporating cost-eff ective mobile system, 3GPP LTE-Advanced has adopted the coordinated multi-point (CoMP) transmission technique due to its ability to mitigate and manage inter-cell interference (ICI). Using CoMP the cell average and cell edge throughput are boosted. However, there is room for reducing energy consumption further by exploiting the inherent exibility of dynamic resource allocation protocols. To this end packet scheduler plays the central role in determining the overall performance of the 3GPP longterm evolution (LTE) based on packet-switching operation and provide a potential research playground for optimizing energy consumption in future networks. In this thesis we investigate the baseline performance for down link CoMP using traditional scheduling approaches, and subsequently go beyond and propose novel energy e fficient scheduling (EES) strategies that can achieve power-e fficient transmission to the UEs whilst enabling both system energy effi ciency gain and fairness improvement. However, ICI can still be prominent when multiple nodes use common resources with di fferent power levels inside the cell, as in the so called heterogeneous networks (Het- Net) environment. HetNets are comprised of two or more tiers of cells. The rst, or higher tier, is a traditional deployment of cell sites, often referred to in this context as macrocells. The lower tiers are termed small cells, and can appear as microcell, picocells or femtocells. The HetNet has attracted signiffi cant interest by key manufacturers as one of the enablers for high speed data at low cost. Research until now has revealed several key hurdles that must be overcome before HetNets can achieve their full potential: bottlenecks in the backhaul must be alleviated, as well as their seamless interworking with CoMP. In this thesis we explore exactly the latter hurdle, and present innovative ideas on advancing CoMP to work in synergy with HetNet deployment, complemented by a novel resource allocation policy for HetNet tighter interference management. As system level simulator has been used to analyze the proposed algorithm/protocols, and results have concluded that up to 20% energy gain can be observed.

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In Mobile Ad hoc NETworks (MANETs), where cooperative behaviour is mandatory, there is a high probability for some nodes to become overloaded with packet forwarding operations in order to support neighbor data exchange. This altruistic behaviour leads to an unbalanced load in the network in terms of traffic and energy consumption. In such scenarios, mobile nodes can benefit from the use of energy efficient and traffic fitting routing protocol that better suits the limited battery capacity and throughput limitation of the network. This PhD work focuses on proposing energy efficient and load balanced routing protocols for ad hoc networks. Where most of the existing routing protocols simply consider the path length metric when choosing the best route between a source and a destination node, in our proposed mechanism, nodes are able to find several routes for each pair of source and destination nodes and select the best route according to energy and traffic parameters, effectively extending the lifespan of the network. Our results show that by applying this novel mechanism, current flat ad hoc routing protocols can achieve higher energy efficiency and load balancing. Also, due to the broadcast nature of the wireless channels in ad hoc networks, other technique such as Network Coding (NC) looks promising for energy efficiency. NC can reduce the number of transmissions, number of re-transmissions, and increase the data transfer rate that directly translates to energy efficiency. However, due to the need to access foreign nodes for coding and forwarding packets, NC needs a mitigation technique against unauthorized accesses and packet corruption. Therefore, we proposed different mechanisms for handling these security attacks by, in particular by serially concatenating codes to support reliability in ad hoc network. As a solution to this problem, we explored a new security framework that proposes an additional degree of protection against eavesdropping attackers based on using concatenated encoding. Therefore, malicious intermediate nodes will find it computationally intractable to decode the transitive packets. We also adopted another code that uses Luby Transform (LT) as a pre-coding code for NC. Primarily being designed for security applications, this code enables the sink nodes to recover corrupted packets even in the presence of byzantine attacks.

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Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Meteorologia), Universidade de Lisboa, Faculdade de Ciências, 2015

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Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and ‘fruits & vegetables’. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

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Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and fruits & vegetables. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included.

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Thesis (Master's)--University of Washington, 2015

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This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

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In this work a mixed integer optimization linear programming (MILP) model was applied to mixed line rate (MLR) IP over WDM and IP over OTN over WDM (with and without OTN grooming) networks, with aim to reduce network energy consumption. Energy-aware and energy-aware & short-path routing techniques were used. Simulations were made based on a real network topology as well as on forecasts of traffic matrix based on statistical data from 2005 up to 2017. Energy aware routing optimization model on IPoWDM network, showed the lowest energy consumption along all years, and once compared with energy-aware & short-path routing, has led to an overall reduction in energy consumption up to 29%, expecting to save even more than shortest-path routing. © 2014 IEEE.

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Thesis to obtain the Master Degree in Electronics and Telecommunications Engineering