837 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.
The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions
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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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Electric propulsion is now a succeful method for primary propulsion of deep space long duration missions and for geosyncronous satellite attitude control. Closed Drift Thruster, so called Hall Thruster or SPT (Stationary Plasma Thruster), was primarily conceived in USSR (the ancient Soviet Union) and, since then, it has been developed by space agencies, space research institutes and industries in several countries such as France, USA, Israel, Russian Federation and Brazil. In this work we present the main features of the Permanent Magnet Hall Thruster (PMHT) developed at the Plasma Laboratory of the University of Brasilia. The idea of using an array of permanent magnets, instead of an electromagnet, to produce a radial magnetic field inside the plasma channel of the thruster is very significant. It allows the development of a Hall Thruster with power consumption low enough to be used in small and medium size satellites. Description of a new vacuum chamber used to test the second prototype of the PMHT (PHALL II) will be given. PHALL II has an aluminum plasma chamber and is smaller with 15 cm diameter and will contain rare earth magnets. We will show plasma density and temperature space profiles inside and outside the thruster channel. Ion temperature measurements based on Doppler broadening of spectral lines and ion energy measurements are also shown. Based on the measured plasma parameters we constructed an aptitude figure of the PMHT. It contains the specific impulse, total thrust, propellant flow rate and power consumption necessary for orbit raising of satellites. Based on previous studies of geosyncronous satellite orbit positioning we perform numerical simulations of satellite orbit raising from an altitude of 700 km to 36000 km using a PMHT operating in the 100 mN - 500 mN thrust range. In order to perform these calculations integration techniques were used. The main simulation paraters were orbit raising time, fuel mass, total satellite mass, thrust and exaust velocity. We conclude comparing our results with results obtainned with known space missions performed with Hall Thrusters. © 2008 by the American Institute of Aeronautics and Astronautics, Inc.
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This study proposes the development of thermal and energy consumption maps to generate useful planning information. A residential neighbourhood in a medium-sized city was selected as the study area. In this area, 40 points were taken as urban reference points where air temperatures at the pedestrian level were collected. At the same time, rural temperatures made available by the city meteorological station were registered. Data of electrical energy consumption of the building units (houses and apartments) were collected through a household survey that was also designed to identify the users' income levels. Then, maps were developed so that the configuration of urban heat islands and electrical energy consumption could be visualised, compared and analysed. The results showed that the income level was the most important variable influencing electrical energy consumption. However, a strong relationship of the consumption with the thermal environment was also observed.
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Incluye Bibliografía
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Includes bibliography
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Includes bibliography
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This issue of the FAL Bulletin discusses the relevance of energy consumption as a basis for identifying energy efficiency potential and calculating the carbon footprints of ports and terminals in Latin America and the Caribbean (LAC), focusing on the Southern Cone countries of Argentina, Chile, Paraguay and Uruguay.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.
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In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.