831 resultados para Buildings - Energy consumption
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To fully appreciate the environmental impact of a workplace the transport-related carbon dioxide (CO2) emissions resulting from its location should be considered in addition to the emissions that result from the occupation of the building itself. Since the first one was built in the early 1980s, business parks have become a significant workplace location for service-sector workers; a sector of the economy that grew rapidly at that time as the UK manufacturing output declined and the employment base shifted to retail services and de-regulated financial services. This paper examines the transport-related CO2 emissions associated with these workplace locations in comparison to town and city centre locations. Using 2001 Census Special Workplace Statistics which record people’s residence, usual workplace and mode of transport between them, distance travelled and mode of travel were calculated for a sample of city centre and out-of-town office locations. The results reveal the extent of the difference between transport-related CO2 emitted by commuters to out-of-town and city centre locations. The implications that these findings have for monitoring the environmental performance of workplaces are discussed.
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Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.
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Around 40% of total energy consumption in the UK is consumed by creating comfortable indoor environment for occupants. Occupants’ behaviour in terms of achieving thermal comfort could have a significant impact on a building’s energy consumption. Therefore, understanding the interactions of occupants with their buildings would be essential to provide a thermal comfort environment that is less reliance on energy-intensive heating, ventilation and air-conditioning systems, to meet energysaving and carbon emission targets. This paper presents the findings of a year-long field study conducted in non-air-conditioned office buildings in the UK. Occupants’ adaptive responses in terms of technological and personal dimensions are dynamic processes which could vary with both indoor and outdoor thermal conditions. The adaptive behaviours of occupants in the surveyed building show substantial seasonal and daily variations. Our study shows that non-physical factors such as habit could influence the adaptive responses of occupants. However, occupants sometimes displayed inappropriate adaptive behaviour, which could lead to a misuse of energy. This paper attempts to illustrate how occupants would adapt and interact with their built environment and consequently contribute to development of a guide for future design/refurbishment of buildings and to develop energy management systems for a comfortable built environment.
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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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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.