950 resultados para energy consumption


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The UK Government's Department for Energy and Climate Change has been investigating the feasibility of developing a national energy efficiency data framework covering both domestic and non-domestic buildings. Working closely with the Energy Saving Trust and energy suppliers, the aim is to develop a data framework to monitor changes in energy efficiency, develop and evaluate programmes and improve information available to consumers. Key applications of the framework are to understand trends in built stock energy use, identify drivers and evaluate the success of different policies. For energy suppliers, it could identify what energy uses are growing, in which sectors and why. This would help with market segmentation and the design of products. For building professionals, it could supplement energy audits and modelling of end-use consumption with real data and support the generation of accurate and comprehensive benchmarks. This paper critically examines the results of the first phase of work to construct a national energy efficiency data-framework for the domestic sector focusing on two specific issues: (a) drivers of domestic energy consumption in terms of the physical nature of the dwellings and socio-economic characteristics of occupants and (b) the impact of energy efficiency measures on energy consumption.

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As low carbon technologies become more pervasive, distribution network operators are looking to support the expected changes in the demands on the low voltage networks through the smarter control of storage devices. Accurate forecasts of demand at the single household-level, or of small aggregations of households, can improve the peak demand reduction brought about through such devices by helping to plan the appropriate charging and discharging cycles. However, before such methods can be developed, validation measures are required which can assess the accuracy and usefulness of forecasts of volatile and noisy household-level demand. In this paper we introduce a new forecast verification error measure that reduces the so called “double penalty” effect, incurred by forecasts whose features are displaced in space or time, compared to traditional point-wise metrics, such as Mean Absolute Error and p-norms in general. The measure that we propose is based on finding a restricted permutation of the original forecast that minimises the point wise error, according to a given metric. We illustrate the advantages of our error measure using half-hourly domestic household electrical energy usage data recorded by smart meters and discuss the effect of the permutation restriction.

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Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

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Taking a perspective from a whole building lifecycle, occupier's actions could account for about 50% of energy. However occupants' activities influence building energy performance is still a blind area. Building energy performance is thought to be the result of a combination of building fabrics, building services and occupants' activities, along with their interactions. In this sense, energy consumption in built environment is regarded as a socio-technical system. In order to understand how such a system works, a range of physical, technical and social information is involved that needs to be integrated and aligned. This paper has proposed a semiotic framework to add value for Building Information Modelling, incorporating energy-related occupancy factors in a context of office buildings. Further, building information has been addressed semantically to describe a building space from the facility management perspective. Finally, the framework guides to set up building information representation system, which can help facility managers to manage buildings efficiently by improving their understanding on how office buildings are operated and used.

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Building designs regularly fail to achieve the anticipated levels of in-use energy consumption. The interaction of occupants with building controls is often cited as a key factor behind this discrepancy. This paper examines whether one factor in inadvertent energy consumption might be the appearance of post-completion errors (when an intended action is not taken because a primary goal has already been accomplished) in occupants’ interactions with building controls. Post-completion errors have been widely studied in human-computer interaction but the concept has not previously been applied to the interaction of occupants with building controls. Two experiments were carried out to examine the effect of incorporating two different types of simple prompt to reduce post-completion error in the use of light switches in office meeting rooms. Results showed that the prompts were effective and that occupants switched off lights when leaving the room more often when presented with a normative prompt than with a standard injunction. Additionally, an over reliance on PIR sensors to turn off lights after meetings was observed, which reduced their intended energy savings. We conclude that achieving low carbon buildings in practice is not solely a technological issue and that application of user-models from human-computer interaction will encourage appropriate occupant interaction with building controls and help reduce inadvertent energy consumption.

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The effect of yarn hairiness on energy consumption when rotating a ring-spun yarn package is investigated theoretically and experimentally. A theoretical model is developed to calculate the energy required to rotate hair fibers, based on hair length and number as well as package speed and size. A single spindle test rig is used to verify the theoretical prediction. The experimental results confirm the theoretical prediction that the package power increases with increased yarn hairiness level and spindle speed.

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Ring spinning has been and will continue to be an important system for making staple yarns from different fibers in the textile industry. But high power consumption and low productivity remain the two outstanding problems with ring spinning. Based on an analysis of power distribution during yarn winding in ring spinning, models for the ratio of energy consumption to yarn production over a full yarn package are established. Spindle speed, yarn count, and package diameter are the three key parameters affecting this ratio. The effects on energy consumption of these parameters are discussed through a case study. The energy-to-production ratio increases with increased package diameter but decreases with increased spindle speed and/or yarn count (tex). The results will help guide spinners in minimizing energy consumption in ring spinning.

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High energy consumption remains a key challenge for the widely used ring spinning system. Tackling this challenge requires a full understanding of the various factors that contribute to yarn tension and energy consumption during ring spinning. In this paper, we report our recent experimental and theoretical research on air drag, yarn tension and energy consumption in ring spinning. A specially constructed rig was used to simulate the ring spinning process; and yarn tension at the guide-eye was measured for different yarns under different conditions. The effect of yarn hairiness on the air drag acting on a rotating yarn package and on a ballooning yarn was examined. Models of the power requirements for overcoming the air drag, increasing the kinetic energy of the yarn package (bobbin and wound yarn) and overcoming the yarn wind-on tension were developed. The ratio of energy-consumption to yarn-production over a full yarn package was discussed. A program to simulate yarn winding in ring spinning was implemented, which can generate the balloon shape and predict yarn tension under a given spinning condition. The simulation results were verified with experimental results obtained from spinning cotton and wool yarns.

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This paper examines the relationship between capital formation, energy consumption and real GDP in a panel of G7 countries using panel unit root, panel cointegration, Granger causality and long-run structural estimation. We find that capital formation, energy consumption and real GDP are cointegrated and that capital formation and energy consumption Granger cause real GDP positively in the long run. We find that a 1% increase in energy consumption increases real GDP by 0.12–0.39%, while a 1% increase in capital formation increases real GDP by 0.1–0.28%.

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Urban areas tend to have higher air temperatures than their surroundings as a result of man-made aiterations. This phenomenon is known as the urban heat island (UHI) effect. UHI is considered to he one of the major problems encountered by the human race this century. Solar radiation that is absorbed during the day by buildings is re~emitted after sunset creating high temperatures in urban areas. Also, anthropogenic heat sources such as air conditioners and road traffic add to the rise in temperatures, A number of
studies have indicated that UHI has a significant effect on the energy use of buildings. In mid- and low-latitude cities, heat islands contribute to urban dwellers' summer discomfort and significantly higher air-conditioning loads. This chapter summarizes and reviews the latest research methodologies and findings about the effect of increased temperatures on the energy consumption of buildings. The latest developments in the heat island mitigation strategies are remarkable, However, more attention needs to be
given to the implementation and testing of these strategies in full-scale buildings.

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This article applies univariate and panel data unit root tests to annual panel data for 182 countries over the period 1979–2000 to examine the stationarity properties of per capita energy consumption. The univariate unit root test can only reject the unit root null for 56 countries or 31% of the sample at the 10% level or better. However, univariate unit root tests have low power with short spans of data and therefore failure to reject the unit root null should be treated with caution. When we apply the panel data unit root test we find overwhelming evidence that energy consumption is stationary. We discuss the policy implications of these findings and offer suggestions for future research.

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The goal of this paper is to examine the long-run elasticities of the impacts of energy consumption on GDP and GDP on energy consumption. The energy consumption–GDP relationship is amongst the most popular relationships examined in the energy economics literature. The bulk of the extant literature has assumed a positive relationship between energy consumption and real GDP. Our analysis shows that in only around 60% of the countries considered the relationship is positive.

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This paper presents an energy management system to reduce the energy consumption of a vehicle when its air conditioning system is in use. The system controls the mass flow rate of the air by dynamically adjusting the blower speed and air-gates opening under various heat and loads circumstances. Simulations were conducted for a travelling vehicle operating the air conditioning system without and with the developed energy management system. The results show that the comfort temperature within the cabin room is achieved for reduced amount of energy consumption.