813 resultados para Electricity customer clustering
Resumo:
Dependency on a small number of customer puts intense pressure on suppliers' profit margin and, in slow growing markets, limits their ability to grow. using stragtegic benchmarking information, a group of Northern Ireland consumer food producer are shown, depsite slow market growth and higher than averge customer dependency, to have increased market share while maintaining aboe vergate proitability. examination of the business strategic and develoment activites of the consumer food firms,and comparble information for other small food prodcuers in Ireland, suggests and emphasiss on cost-reduction and new prodcut development. A comparision of the productivity and prodcut range of the consuer food firms provides evidence of the success of these strategic. This suggests that even a relatively weak market situations, charactrised by dependency on a small number of customers, can be over come by effective and appropriate business strategy.
Resumo:
RNA polymerase I (Pol I) produces large ribosomal RNAs (rRNAs). In this study, we show that the Rpa49 and Rpa34 Pol I subunits, which do not have counterparts in Pol II and Pol III complexes, are functionally conserved using heterospecific complementation of the human and Schizosaccharomyces pombe orthologues in Saccharomyces cerevisiae. Deletion of RPA49 leads to the disappearance of nucleolar structure, but nucleolar assembly can be restored by decreasing ribosomal gene copy number from 190 to 25. Statistical analysis of Miller spreads in the absence of Rpa49 demonstrates a fourfold decrease in Pol I loading rate per gene and decreased contact between adjacent Pol I complexes. Therefore, the Rpa34 and Rpa49 Pol I–specific subunits are essential for nucleolar assembly and for the high polymerase loading rate associated with frequent contact between adjacent enzymes. Together our data suggest that localized rRNA production results in spatially constrained rRNA production, which is instrumental for nucleolar assembly.
Resumo:
Laying hens generally choose to aggregate, but the extent to which the environments in which we house them impact on social group dynamics is not known. In this paper the effect of pen environment on spatial clustering is considered. Twelve groups of four laying hens were studied under three environmental conditions: wire floor (W), shavings (Sh) and perches, peat, nestbox and shavings (PPN). Groups experienced each environment twice, for five weeks each time, in a systematic order that varied from group to group. Video recordings were made one day per week for 30 weeks. To determine level of clustering, we recorded positional data from a randomly selected 20-min excerpt per video (a total of 20 min x 360 videos analysed). On screen, pens were divided into six equal areas. In addition, PPN pens were divided into an additional four (sub) areas, to account for the use of perches (one area per half perch). Every 5 s, we recorded the location of each bird and calculated location use over time, feeding synchrony and cluster scores for each environment. Feeding synchrony and cluster scores were compared against unweighted and weighted (according to observed proportional location use) Poisson distributions to distinguish between resource and social attraction.
Resumo:
Recent cold winters and prolonged periods of low wind speeds have prompted concerns about the increasing penetration of wind generation in the Irish and other northern European power systems. On the combined Republic of Ireland and Northern Ireland system there was in excess of 1.5 GW of installed wind power in January 2010. As the penetration of these variable, non-dispatchable generators increases, power systems are becoming more sensitive to weather events on the supply side as well as on the demand side. In the temperate climate of Ireland, sensitivity of supply to weather is mainly due to wind variability while demand sensitivity is driven by space heating or cooling loads. The interplay of these two weather-driven effects is of particular concern if demand spikes driven by low temperatures coincide with periods of low winds. In December 2009 and January 2010 Ireland experienced a prolonged spell of unusually cold conditions. During much of this time, wind generation output was low due to low wind speeds. The impacts of this event are presented as a case study of the effects of weather extremes on power systems with high penetrations of variable renewable generation.
Resumo:
Electricity systems models are software tools used to manage electricity demand and the electricity systems, to trade electricity and for generation expansion planning purposes. Various portfolios and scenarios are modelled in order to compare the effects of decision making in policy and on business development plans in electricity systems so as to best advise governments and industry on the least cost economic and environmental approach to electricity supply, while maintaining a secure supply of sufficient quality electricity. The modelling techniques developed to study vertically integrated state monopolies are now applied in liberalised markets where the issues and constraints are more complex. This paper reviews the changing role of electricity systems modelling in a strategic manner, focussing on the modelling response to key developments, the move away from monopoly towards liberalised market regimes and the increasing complexity brought about by policy targets for renewable energy and emissions. The paper provides an overview of electricity systems modelling techniques, discusses a number of key proprietary electricity systems models used in the USA and Europe and provides an information resource to the electricity analyst not currently readily available in the literature on the choice of model to investigate different aspects of the electricity system.
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In late 2008, the Government of the Republic of Ireland set a specific target that 10% of all vehicles in its transport fleet be powered by electricity by 2020 in order to meet European Union renewable energy targets and greenhouse gas emissions reduction targets. International there are similar targets. This is a considerable challenge as in 2009, transport accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the impacts of 10% electric vehicle charging on the single wholesale electricity market for the Republic of Ireland and Northern Ireland is examined. The energy consumed and the total carbon dioxide emissions generated under different charging scenarios is quantified and the results of the charging scenarios are compared to identify the best implementation strategy.
Resumo:
To meet European Union renewable energy and greenhouse gas emissions reduction targets the Irish government set a target in 2008 that 10% of all vehicles in the transport fleet be powered by electricity by 2020. Similar electric vehicle targets have been introduced in other countries. However, reducing energy consumption and decreasing greenhouse gas emissions in transport is a considerable challenge due to heavy reliance on fossil fuels. In fact, transport in the Republic of Ireland in 2009 accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the effect of electric vehicle charging on the operation of the single wholesale electricity market for the Republic of Ireland and Northern Ireland is analysed. The energy consumed, greenhouse gas emissions generated and changes to the wholesale price of electricity under peak and off-peak charging scenarios are quantified and discussed. Results from the study show that off-peak charging is more beneficial than peak charging.
Resumo:
We study the residential demand for electricity and gas, working with nationwide household-level data that cover recent years, namely 1997-2007. Our dataset is a mixed panel/multi-year cross-sections of dwellings/households in the 50 largest metropolitan areas in the United States as of 2008. We estimate static and dynamic models of electricity and gas demand. We find strong household response to energy prices, both in the short and long term. From the static models, we get estimates of the own price elasticity of electricity demand in the -0.860 to -0.667 range, while the own price elasticity of gas demand is -0.693 to -0.566. These results are robust to a variety of checks. Contrary to earlier literature (Metcalf and Hassett, 1999; Reiss and White, 2005), we find no evidence of significantly different elasticities across households with electric and gas heat. The price elasticity of electricity demand declines with income, but the magnitude of this effect is small. These results are in sharp contrast to much of the literature on residential energy consumption in the United States, and with the figures used in current government agency practice. Our results suggest that there might be greater potential for policies which affect energy price than may have been previously appreciated. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured.