55 resultados para Electricity tariff


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Abstract. Not long after Franklin’s iconic studies, an atmospheric electric field was discovered in “fair weather” regions, well away from thunderstorms. The origin of the fair weather field was sought by Lord Kelvin, through development of electrostatic instrumentation and early data logging techniques, but was ultimately explained through the global circuit model of C.T.R. Wilson. In Wilson’s model, charge exchanged by disturbed weather electrifies the ionosphere, and returns via a small vertical current density in fair weather regions. New insights into the relevance of fair weather atmospheric electricity to terrestrial and planetary atmospheres are now emerging. For example, there is a possible role of the global circuit current density in atmospheric processes, such as cloud formation. Beyond natural atmospheric processes, a novel practical application is the use of early atmospheric electrostatic investigations to provide quantitative information on past urban air pollution.

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In recent years, Germany has significantly increased its share of electricity produced from renewable sources, which is mainly due to the Renewable Energy Act (EEG). The EEG substantially impacts the dynamics of intra-day electricity prices by increasing the likelihood of negative prices. In this paper, we present a non-Gaussian process to model German intra-day electricity prices and propose an estimation procedure for this model. Most importantly, our model is able to generate extreme positive and negative spikes. A simulation study demonstrates the ability of our model to capture the characteristics of the data.

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Pacific ocean temperature anomalies associated with the El Niño–Southern Oscillation (ENSO) modulate atmospheric convection and hence thunderstorm electrification. The generated current flows globally via the atmospheric electric circuit, which can be monitored anywhere on Earth. Atmospheric electricity measurements made at Shetland (in Scotland) display a mean global circuit response to ENSO that is characterized by strengthening during 'El Niño' conditions, and weakening during 'La Niña' conditions. Examining the hourly varying response indicates that a potential gradient (PG) increase around noon UT is likely to be associated with a change in atmospheric convection and resultant lightning activity over equatorial Africa and Eastern Asia. A secondary increase in PG just after midnight UT can be attributed to more shower clouds in the central Pacific ocean during an 'El Niño'.

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The reform of previously state-owned and operated industries in many Less Developed Countries (LDCs) provide contrary experiences to those in the developed world, which have generally had more equitable distributional impacts. The economic reform policies proposed by the so-called 'Washington Consensus' state that privatisation provides governments with opportunities to raise revenues through the sale of under-performing and indebted state industries, thereby reducing significant fiscal burdens, and, at the same time, facilitating influxes of foreign capital, skills and technology, with the aim of improving operations and a "trickle-down" of benefits. However, experiences in many LDCs over the last 15-20 years suggest that reform has not solved the problem of chronic public-sector debt, and that poverty and socio-economic inequalities have increased during this period of 'neo-liberal' economics. This paper does not seek to challenge the policies themselves, but rather argues that the context in which reform has often taken place is of fundamental significance. The industry-centric policy advice provided by the IFIs typically causes a 'lock-in' of inequitably distributed 'efficiency gains', providing minimal, if any, benefits to impoverished groups. These arguments are made using case study analysis from the electricity and mining sectors.

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Wind generation’s contribution to meeting extreme peaks in electricity demand is a key concern for the integration of wind power. In Great Britain (GB), robustly assessing this contribution directly from power system data (i.e. metered wind-supply and electricity demand) is difficult as extreme peaks occur infrequently (by definition) and measurement records are both short and inhomogeneous. Atmospheric circulation-typing combined with meteorological reanalysis data is proposed as a means to address some of these difficulties, motivated by a case study of the extreme peak demand events in January 2010. A preliminary investigation of the physical and statistical properties of these circulation types suggests that they can be used to identify the conditions that are most likely to be associated with extreme peak demand events. Three broad cases are highlighted as requiring further investigation. The high-over-Britain anticyclone is found to be generally associated with very low winds but relatively moderate temperatures (and therefore moderate peak demands, somewhat in contrast to the classic low-wind cold snap that is sometimes apparent in the literature). In contrast, both longitudinally extended blocking over Scotland/Scandinavia and latitudinally extended troughs over western Europe appear to be more closely linked to the very cold GB temperatures (usually associated with extreme peak demands). In both of these latter situations, wind resource averaged across GB appears to be more moderate.

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Atmospheric aerosol acts to both reduce the background concentration of natural cluster ions, and to attenuate optical propagation. Hence, the presence of aerosol has two consequences, the reduction of the air’s electrical conductivity and the visual range. Ion-aerosol theory and Koschmieder’s visibility theory are combined here to derive the related non-linear variation of the atmospheric electric potential gradient with visual range. A substantial sensitivity is found under poor visual range conditions, but, for good visual range conditions the sensitivity diminishes and little influence of local aerosol on the fair weather potential gradient occurs. This allows visual range measurements, made simply and routinely at many meteorological sites, to provide inference about the local air’s electrical properties.

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This paper explores the possible evolution of UK electricity demand as we move along three potential transition pathways to a low carbon economy in 2050.The shift away from fossil fuels through the electrification of demand is discussed, particularly through the uptake of heat pumps and electric vehicles in the domestic and passenger transport sectors. Developments in the way people and institutions may use energy along each of the pathways are also considered and provide a rationale for the quantification of future annual electricity demands in various broad sectors. The paper then presents detailed modelling of hourly balancing of these demands in the context of potential low carbon generation mixes associated with the three pathways. In all cases, hourly balancing is shown to be a significant challenge. To minimise the need for conventional generation to operate with very low capacity factors, a variety of demand side participation measures are modelled and shown to provide significant benefits. Lastly, projections of greenhouse gas emissions from the UK and the imports of fossil fuels to the UK for each of the three pathways are presented.

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One of the most common Demand Side Management programs consists of Time-of-Use (TOU) tariffs, where consumers are charged differently depending on the time of the day when they make use of energy services. This paper assesses the impacts of TOU tariffs on a dataset of residential users from the Province of Trento in Northern Italy in terms of changes in electricity demand, price savings, peak load shifting and peak electricity demand at substation level. Findings highlight that TOU tariffs bring about higher average electricity consumption and lower payments by consumers. A significant level of load shifting takes place for morning peaks. However, issues with evening peaks are not resolved. Finally, TOU tariffs lead to increases in electricity demand for substations at peak time.

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For decades regulators in the energy sector have focused on facilitating the maximisation of energy supply in order to meet demand through liberalisation and removal of market barriers. The debate on climate change has emphasised a new type of risk in the balance between energy demand and supply: excessively high energy demand brings about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, energy suppliers have to activate dirty old power plants with higher greenhouse gas emissions and higher system costs. The creation of a Europe-wide electricity market requires a systematic investigation into the risk of aggregate peak demand. This paper draws on the e-Living Time-Use Survey database to assess the risk of aggregate peak residential electricity demand for European energy markets. Findings highlight in which countries and for what activities the risk of aggregate peak demand is greater. The discussion highlights which approaches energy regulators have started considering to convince users about the risks of consuming too much energy during peak times. These include ‘nudging’ approaches such as the roll-out of smart meters, incentives for shifting the timing of energy consumption, differentiated time-of-use tariffs, regulatory financial incentives and consumption data sharing at the community level.

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Lighting and small power will typically account for more than half of the total electricity consumption in an office building. Significant variations in electricity used by different tenants suggest that occupants can have a significant impact on the electricity demand for these end-uses. Yet current modelling techniques fail to represent the interaction between occupant and the building environment in a realistic manner. Understanding the impact of such behaviours is crucial to improve the methodology behind current energy modelling techniques, aiming to minimise the significant gap between predicted and in-use performance of buildings. A better understanding of the impact of occupant behaviour on electricity consumption can also inform appropriate energy saving strategies focused on behavioural change. This paper reports on a study aiming to assess the intent of occupants to switch off lighting and appliances when not in use in office buildings. Based on the Theory of Planned Behaviour, the assessment takes the form of a questionnaire and investigates three predictors to behaviour individually: 1) behavioural attitude; 2) subjective norms; 3) perceived behavioural control. The paper details the development of the assessment procedure and discusses preliminary findings from the study. The questionnaire results are compared against electricity consumption data for individual zones within a multi-tenanted office building. Initial results demonstrate a statistically significant correlation between perceived behavioural control and energy consumption for lighting and small power