888 resultados para Electricity commercialization


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The atmosphere's fair weather electric field is a permanent feature, arising from the combination of distant thunderstorms, Earth's conducting surface, a charged ionosphere and cosmic ray ionization. Despite its ubiquity, no fair weather electricity effect on clouds has been hitherto demonstrated. Here we report surface measurements of radiation emitted and scattered by extensive thin continental cloud, which, after ~2 min delay, shows changes closely following the fair weather electric field. For typical fluctuations in the fair weather electric field, changes of about 10% are subsequently induced in the diffuse short-wave radiation. These observations are consistent with enhanced production of large cloud droplets from charging at layer cloud edges.

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This paper focuses upon the policy and institutional change that has taken place within the Argentine electricity market since the country’s economic and social crisis of 2001/2. As one of the first less developed countries (LDCs) to liberalise and privatise its electricity industry, Argentina has since moved away from the orthodox market model after consumer prices were frozen by the Government in early 2002 when the national currency was devalued by 70%. Although its reforms were widely praised during the 1990s, the electricity market has undergone a number of interventions, ostensibly to keep consumer prices low and to avert the much-discussed energy ‘crisis’ caused by a dearth of new investment combined with rising demand levels. This paper explores how the economic crisis and its consequences have both enabled and legitimised these policy and institutional amendments, while drawing upon the specifics of the post-neoliberal market ‘re-reforms’ to consider the extent to which the Government appears to be moving away from market-based prescriptions. In addition, this paper contributes to sector-specific understandings of how, despite these changes, neoliberal ideas and assumptions continue to dominate Argentine public policy well beyond the postcrisis era.

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In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

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We propose a mechanism to explain suggested links between seismic activity and ionospheric changes detected overhead. Specifically, we explain changes in the natural extremely low-frequency (ELF) radio noise recently observed in the topside ionosphere aboard the DEMETER satellite at night, before major earthquakes. Our mechanism utilises increased electrical conductivity of surface layer air before a major earthquake, which reduces the surface-ionosphere electrical resistance. This increases the vertical fair weather current, and (to maintain continuity of electron flow) lowers the ionosphere. Magnitudes of crucial parameters are estimated and found to be consistent with observations. Natural variability in ionospheric and atmospheric electrical properties is evaluated, and may be overcome using a hybrid detection approach. Suggested experiments to investigate the mechanism involve measuring the cut-off frequency of ELF “tweeks”, the amplitude and phase of very low frequency radio waves in the Earth–ionosphere waveguide, or medium frequency radar, incoherent scatter or rocket studies of the lower ionospheric electron density.

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The solar wind modulates the flux of galactic cosmic rays impinging on Earth inversely with solar activity. Cosmic ray ionisation is the major source of air’s electrical conductivity over the oceans and well above the continents. Differential solar modulation of the cosmic ray energy spectrum modifies the cosmic ray ionisation at different latitudes,varying the total atmospheric columnar conductance. This redistributes current flow in the global atmospheric electrical circuit, including the local vertical current density and the related surface potential gradient. Surface vertical current density and potential gradient measurements made independently at Lerwick Observatory,Shetland,from 1978 to 1985 are compared with modelled changes in cosmic ray ionisation arising from solar activity changes. Both the lower troposphere atmospheric electricity quantities are significantly increased at cosmic ray maximum(solar minimum),with a proportional change greater than that of the cosmic ray change.

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In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.