917 resultados para Household appliances, Electric.


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We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

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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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This chapter explores the politics around the role of agency in the UK climate change debate. Government interventions on the demand side of consumption have increasingly involved attempts to obtain greater traction with the values, attitudes and beliefs of citizens in relation to climate change and also in terms of influencing consumer behaviour at an individual level. With figures showing that approximately 40% of the UK’s carbon emissions are attributable to household and transport behaviour, policy initiatives have progressively focused on the facilitation of “sustainable behaviours”. Evidence suggests however, that mobilisation of pro-environmental attitudes in addressing the perceived “value-action gap” has so far had limited success. Research in this field suggests that there is a more significant and nuanced “gap” between context and behaviour; a relationship that perhaps provides a more adroit reflection of reasons why people do not necessarily react in the way that policy-makers anticipate. Tracing the development of the UK Government’s behaviour change agenda over the last decade, we posit that a core reason for the limitations of this programme relates to an excessively narrow focus on the individual. This has served to obscure some of the wider political and economic aspects of the debate in favour of a more simplified discussion. The second part of the chapter reports findings from a series of focus groups exploring some of the wider political views that people hold around household energy habits, purchase and use of domestic appliances, and transport behaviour-and discusses these insights in relation to the literature on the agenda’s apparent limitations. The chapter concludes by considering whether the aims of the Big Society approach (recently established by the UK’s Coalition Government) hold the potential to engage more directly with some of these issues or whether they merely constitute a “repackaging” of the individualism agenda.

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We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.

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We investigate electron acceleration due to shear Alfven waves in a collissionless plasma for plasma parameters typical of 4–5RE radial distance from the Earth along auroral field lines. Recent observational work has motivated this study, which explores the plasma regime where the thermal velocity of the electrons is similar to the Alfven speed of the plasma, encouraging Landau resonance for electrons in the wave fields. We use a self-consistent kinetic simulation model to follow the evolution of the electrons as they interact with a short-duration wave pulse, which allows us to determine the parallel electric field of the shear Alfven wave due to both electron inertia and electron pressure effects. The simulation demonstrates that electrons can be accelerated to keV energies in a modest amplitude sub-second period wave. We compare the parallel electric field obtained from the simulation with those provided by fluid approximations.

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We illustrate how coupling could occur between surface air and clouds via the global electric circuit – through Atmospheric Lithosphere–Ionosphere Charge Exchange (ALICE) processes – in an attempt to develop a physical understanding of the possible relationships between earthquakes and clouds

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Karen Aplin and Giles Harrison examine international records of the 1859 Carrington flare and consider what they mean for our understanding of space weather today. Space weather is increasingly recognized as a hazard to modern societies, and one way to assess the extent of its possible impact is through analysis of historic space weather events. One such event was the massive solar storm of late August and early September 1859. This is now widely known as the “Carrington flare” or “Carrington event” after the visual solar emissions on 1 September first reported by the Victorian astronomer Richard Carrington from his observatory in Redhill, Surrey (Carrington 1859). The related aurorae and subsequent effects on telegraph networks are well documented (e.g. Clark 2007, Boteler 2006), but use of modern techniques, such as analysis of nitrates produced by solar protons in ice cores to retrospectively assess the nature of the solar flare, has proved problematic (Wolff et al. 2012). This means that there is still very little quantitative information about the flare beyond magnetic observations (e.g. Viljanen et al. 2014).

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In this paper we present the capability of a new network of field mill sensors to monitor the atmospheric electric field at various locations in South America; we also show some early results. The main objective of the new network is to obtain the characteristic Universal Time diurnal curve of the atmospheric electric field in fair weather, known as the Carnegie curve. The Carnegie curve is closely related to the current sources flowing in the Global Atmospheric Electric Circuit so that another goal is the study of this relationship on various time scales (transient/monthly/seasonal/annual). Also, by operating this new network, we may also study departures of the Carnegie curve from its long term average value related to various solar, geophysical and atmospheric phenomena such as the solar cycle, solar flares and energetic charged particles, galactic cosmic rays, seismic activity and specific meteorological events. We then expect to have a better understanding of the influence of these phenomena on the Global Atmospheric Electric Circuit and its time-varying behavior.

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The effect of the direction of external electric field on the shear stress of an ER fluid has been studied by molecular-dynamics simulation. Due to the formation of inclined chains, the shear stress strongly depends on the direction of the field, and it may be very large under some special field direction. And theoretical model of ideal microstructure of ER fluids has proved this result. Thus the ER effect may be greatly enhanced just by choosing an optimum direction for the field without any additional requirement, suggesting a promising way to the practical application of ER fluids.

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The early twentieth century constituted the heyday of the ‘breadwinner–homemaker’ household, characterized by a high degree of intra-household functional specialization between paid and domestic work according to age, gender, and marital status. This article examines the links between formal workforce participation and access to resources for individualized discretionary spending in British working-class households during the late 1930s, via an analysis of household leisure expenditures. Leisure spending is particularly salient to intra-household resource allocation, as it constitutes one of the most highly prioritized areas of individualized expenditure, especially for young, single people. Using a database compiled from surviving returns to the Ministry of Labour's national 1937/8 working-class expenditure survey, we examine leisure participation rates for over 600 households, using a detailed set of commercial leisure activities together with other relevant variables. We find that the employment status of family members other than the male breadwinner was a key factor influencing their access to commercial leisure. Our analysis thus supports the view that the breadwinner–homemaker household was characterized by strong power imbalances that concentrated resources—especially for individualized expenditures—in the hands of those family members who engaged in paid labour.

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The weekly dependence of pollutant aerosols in the urban environment of Lisbon (Portugal) is inferred from the records of atmospheric electric field at Portela meteorological station (38°47′N,9°08′W). Measurements were made with a Bendorf electrograph. The data set exists from 1955 to 1990, but due to the contaminating effect of the radioactive fallout during 1960 and 1970s, only the period between 1980 and 1990 is considered here. Using a relative difference method a weekly dependence of the atmospheric electric field is found in these records, which shows an increasing trend between 1980 and 1990. This is consistent with a growth of population in the Lisbon metropolitan area and consequently urban activity, mainly traffic. Complementarily, using a Lomb–Scargle periodogram technique the presence of a daily and weekly cycle is also found. Moreover, to follow the evolution of theses cycles, in the period considered, a simple representation in a colour surface plot representation of the annual periodograms is presented. Further, a noise analysis of the periodograms is made, which validates the results found. Two datasets were considered: all days in the period, and fair-weather days only.

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More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences - that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at day-time, night-time, or a mix of both. The model is implemented on a neighbourhood in south-east England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.

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We investigated the plume structure of a piezo-electric sprayer system, set up to release ethanol in a wind tunnel, using a fast response mini-photoionizaton detector. We recorded the plume structure of four different piezo-sprayer configurations: the sprayer alone; with a 1.6-mm steel mesh shield; with a 3.2-mm steel mesh shield; and with a 5 cm circular upwind baffle. We measured a 12 × 12-mm core at the center of the plume, and both a horizontal and vertical cross-section of the plume, all at 100-, 200-, and 400-mm downwind of the odor source. Significant differences in plume structure were found among all configurations in terms of conditional relative mean concentration, intermittency, ratio of peak concentration to conditional mean concentration, and cross-sectional area of the plume. We then measured the flight responses of the almond moth, Cadra cautella, to odor plumes generated with the sprayer alone, and with the upwind baffle piezo-sprayer configuration, releasing a 13:1 ratio of (9Z,12E)-tetradecadienyl acetate and (Z)-9-tetradecenyl acetate diluted in ethanol at release rates of 1, 10, 100, and 1,000 pg/min. For each configuration, differences in pheromone release rate resulted in significant differences in the proportions of moths performing oriented flight and landing behaviors. Additionally, there were apparent differences in the moths’ behaviors between the two sprayer configurations, although this requires confirmation with further experiments. This study provides evidence that both pheromone concentration and plume structure affect moth orientation behavior and demonstrates that care is needed when setting up experiments that use a piezo-electric release system to ensure the optimal conditions for behavioral observations.