815 resultados para Electrical energy consumption


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Attempts were made to quantify the environmental impacts of the basement walls of two commercial buildings in London. Four different retaining wall options were designed based on steel and concrete systems for each of the sites. It was considered that excavation would take place with the aid of a one or two anchors system. Evaluation of embodied energy (EE) and CO2 emissions for each of the wall designs and anchoring systems were compared. Results show that there are notable differences in EE between different wall designs. Using the averaged set of Embodied Energy Intensity (EEI) values, the use of recycled steel over virgin steel would reduce the EE of the wall significantly. The difference in anchor designs is relatively insignificant, and therefore the practicality of the design for the specific site should be the deciding factor for anchor types. Generally, the scale of environmental impacts due to constructions is large compared to other aspects in life as demonstrated with the comparisons to car emissions and household energy consumption. Copyright ASCE 2008.

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A mathematical model is developed to predict the energy consumption of a heavy vehicle. It includes the important factors of heavy-vehicle energy consumption, namely engine and drivetrain performances, losses due to accessories, aerodynamic drag, rolling resistance, road gradients, and driver behaviour. Novel low-cost testing methods were developed to determine engine and drivetrain characteristics. A simple drive cycle was used to validate the model. The model is able to predict the fuel use for a 371 tractor-semitrailer vehicle over a 4 km drive cycle within 1 per cent. This paper demonstrates that accurate and reliable vehicle benchmarking and model parameter measurement can be achieved without expensive equipment overheads, e.g. engine and chassis dynamometers.

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Building integrated photovoltaics (BIPV) has potential of becoming the mainstream of renewable energy in the urban environment. BIPV has significant influence on the thermal performance of building envelope and changes radiation energy balance by adding or replacing conventional building elements in urban areas. PTEBU model was developed to evaluate the effect of photovoltaic (PV) system on the microclimate of urban canopy layer. PTEBU model consists of four sub-models: PV thermal model, PV electrical performance model, building energy consumption model, and urban canyon energy budget model. PTEBU model is forced with temperature, wind speed, and solar radiation above the roof level and incorporates detailed data of PV system and urban canyon in Tianjin, China. The simulation results show that PV roof and PV façade with ventilated air gap significantly change the building surface temperature and sensible heat flux density, but the air temperature of urban canyon with PV module varies little compared with the urban canyon of no PV. The PV module also changes the magnitude and pattern of diurnal variation of the storage heat flux and the net radiation for the urban canyon with PV increase slightly. The increase in the PV conversion efficiency not only improves the PV power output, but also reduces the urban canyon air temperature. © 2006.

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The embodied energy (EE) and gas emissions of four design alternatives for an embankment retaining wall system are analyzed for a hypothetical highway construction project. The airborne emissions considered are carbon dioxide (CO 2), methane (CH 4), nitrous oxide (N 2O), sulphur oxides (SO X), and nitrogen oxides (NO X). The process stages considered in this study are the initial materials production, transportation of construction machineries and materials, machinery operation during installation, and machinery depreciations. The objectives are (1) to determine whether there are statistically significant differences among the structural alternatives; (2) to understand the relative proportions of impacts for the process stages within each design; (3) to contextualize the impacts to other aspects in life by comparing the computed EE values to household energy consumption and car emission values; and (4) to examine the validity of the adopted EE as an environmental impact indicator through comparison with the amount of gas emissions. For the project considered in this study, the calculated results indicate that propped steel sheet pile wall and minipile wall systems have less embodied energy and gas emissions than cantilever steel tubular wall and secant concrete pile wall systems. The difference in CO 2 emission for the retaining wall of 100 m length between the most and least environmentally preferable wall design is equivalent to an average 2.0 L family car being driven for 6.2 million miles (or 62 cars with a mileage of 10,000 miles/year for 10 years). The impacts in construction are generally notable and careful consideration and optimization of designs will reduce such impacts. The use of recycled steel or steel pile as reinforcement bar is effective in reducing the environmental impact. The embodied energy value of a given design is correlated to the amount of gas emissions. © 2011 American Society of Civil Engineers.

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Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

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The increasing pressure on material availability, energy prices, as well as emerging environmental legislation is leading manufacturers to adopt solutions to reduce their material and energy consumption as well as their carbon footprint, thereby becoming more sustainable. Ultimately manufacturers could potentially become zero carbon by having zero net energy demand and zero waste across the supply chain. The literature on zero carbon manufacturing and the technologies that underpin it are growing, but there is little available on how a manufacturer undertakes the transition. Additionally, the work in this area is fragmented and clustered around technologies rather than around processes that link the technologies together. There is a need to better understand material, energy, and waste process flows in a manufacturing facility from a holistic viewpoint. With knowledge of the potential flows, design methodologies can be developed to enable zero carbon manufacturing facility creation. This paper explores the challenges faced when attempting to design a zero carbon manufacturing facility. A broad scope is adopted from legislation to technology and from low waste to consuming waste. A generic material, energy, and waste flow model is developed and presented to show the material, energy, and waste inputs and outputs for the manufacturing system and the supporting facility and, importantly, how they can potentially interact. Finally the application of the flow model in industrial applications is demonstrated to select appropriate technologies and configure them in an integrated way. © 2009 IMechE.

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Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

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Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in our existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

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Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

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The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop models for large scale analysis of the stock. This research proposes a probabilistic, engineering-based, bottom-up model to address these issues. In a recent study we classified London's non-domestic buildings based on the service they provide, such as offices, retail premise, and schools, and proposed the creation of one probabilistic representational model per building type. This paper investigates techniques for the development of such models. The representational model is a statistical surrogate of a dynamic energy simulation (ES) model. We first identify the main parameters affecting energy consumption in a particular building sector/type by using sampling-based global sensitivity analysis methods, and then generate statistical surrogate models of the dynamic ES model within the dominant model parameters. Given a sample of actual energy consumption for that sector, we use the surrogate model to infer the distribution of model parameters by inverse analysis. The inferred distributions of input parameters are able to quantify the relative benefits of alternative energy saving measures on an entire building sector with requisite quantification of uncertainties. Secondary school buildings are used for illustrating the application of this probabilistic method. © 2012 Elsevier B.V. All rights reserved.

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Over the past decade, electrical detection of chemical and biological species using novel nanostructure-based devices has attracted significant attention for chemical, genomics, biomedical diagnostics, and drug discovery applications. The use of nanostructured devices in chemical/biological sensors in place of conventional sensing technologies has advantages of high sensitivity, low decreased energy consumption and potentially highly miniaturized integration. Owing to their particular structure, excellent electrical properties and high chemical stability, carbon nanotube and graphene based electrical devices have been widely developed for high performance label-free chemical/biological sensors. Here, we review the latest developments of carbon nanostructure-based transistor sensors in ultrasensitive detection of chemical/biological entities, such as poisonous gases, nucleic acids, proteins and cells.

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This paper investigates 'future-proofing' as an unexplored yet all-important aspect in the design of low-energy dwellings. It refers particularly to adopting lifecycle thinking and accommodating risks and uncertainties in the selection of fabric energy efficiency measures and low or zero-carbon technologies. Based on a conceptual framework for future-proofed design, the paper first presents results from the analysis of two 'best practice' housing developments in England; i.e., North West Cambridge in Cambridge and West Carclaze and Baal in St. Austell, Cornwall. Second, it examines the 'Energy and CO2 Emissions' part of the Code for Sustainable Homes to reveal which design criteria and assessment methods can be practically integrated into this established building certification scheme so that it can become more dynamic and future-oriented.Practical application: Future-proofed construction is promoted implicitly within the increasingly stringent building regulations; however, there is no comprehensive method to readily incorporate futures thinking into the energy design of buildings. This study has a three-fold objective of relevance to the building industry:Illuminating the two key categories of long-term impacts in buildings, which are often erroneously treated interchangeably:- The environmental impact of buildings due to their long lifecycles.- The environment's impacts on buildings due to risks and uncertainties affecting the energy consumption by at least 2050. This refers to social, technological, economic, environmental and regulatory (predictable or unknown) trends and drivers of change, such as climate uncertainty, home-working, technology readiness etc.Encouraging future-proofing from an early planning stage to reduce the likelihood of a prematurely obsolete building design.Enhancing established building energy assessment methods (certification, modelling or audit tools) by integrating a set of future-oriented criteria into their methodologies. © 2012 The Chartered Institution of Building Services Engineers.

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This paper presents a review undertaken to understand the concept of 'future-proofing' the energy performance of buildings. The long lifecycles of the building stock, the impacts of climate change and the requirements for low carbon development underline the need for long-term thinking from the early design stages. 'Future-proofing' is an emerging research agenda with currently no widely accepted definition amongst scholars and building professionals. In this paper, it refers to design processes that accommodate explicitly full lifecycle perspectives and energy trends and drivers by at least 2050, when selecting energy efficient measures and low carbon technologies. A knowledge map is introduced, which explores the key axes (or attributes) for achieving a 'future-proofed' energy design; namely, coverage of sustainability issues, lifecycle thinking, and accommodating risks and uncertainties that affect the energy consumption. It is concluded that further research is needed so that established building energy assessment methods are refined to better incorporate future-proofing. The study follows an interdisciplinary approach and is targeted at design teams with aspirations to achieve resilient and flexible low-energy buildings over the long-term. © 2012 Elsevier Ltd.

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The ocean represents a huge energy reservoir since waves can be exploited to generate clean and renewable electricity; however, a hybrid energy storage system is needed to smooth the fluctuation. In this paper a hybrid energy storage system using a superconducting magnetic energy system (SMES) and Li-ion battery is proposed. The SMES is designed using Yttrium Barium Copper Oxide (YBCO) tapes, which store 60 kJ electrical energy. The magnet component of the SMES is designed using global optimization algorithm. Mechanical stress, coupled with electromagnetic field, is calculated using COMSOL and Matlab. A cooling system is presented and a suitable refrigerator is chosen to maintain a cold working temperature taking into account four heat sources. Then a microgrid system of direct drive linear wave energy converters is designed. The interface circuit connecting the generator and storage system is given. The result reveals that the fluctuated power from direct drive linear wave energy converters is smoothed by the hybrid energy storage system. The maximum power of the wave energy converter is 10 kW. © 2012 IEEE.

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Large digital chips use a significant amount of energy to broadcast a low-skew, multigigahertz clock to millions of latches located throughout the chip. Every clock cycle, the large aggregate capacitance of the clock network is charged from the supply and then discharged to ground. Instead of wasting this stored energy, it is possible to recycle the energy by controlling its delivery to another part of the chip using an on-chip dc-dc converter. The clock driver and switching converter circuits share many compatible characteristics that allow them to be merged into a single design and fully integrated on-chip. Our buck converter prototype, manufactured in 90-nm CMOS, provides a proof-of-concept that clock network energy can be recycled to other parts of the chip, thus lowering overall energy consumption. It also confirms that monolithic multigigahertz switching converters utilizing zero-voltage switching can be implemented in deep-submicrometer CMOS. With multigigahertz operation, fully integrated inductors and capacitors use a small amount of chip area with low losses. Combining the clock driver with the power converter can share the large MOSFET drivers necessary as well as being energy and space efficient. We present an analysis of the losses which we confirm by experimentally comparing the merged circuit with a conventional clock driver. © 2012 IEEE.