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Mains electricity

About: Mains electricity is a(n) research topic. Over the lifetime, 7544 publication(s) have been published within this topic receiving 83102 citation(s). The topic is also known as: low voltage electrical grid & household wiring. more


Journal ArticleDOI: 10.1086/261846
Abstract: Most of the British electricity supply industry has been privatized. Two dominant generators supply bulk electricity to an unregulated "pool." They submit a supply schedule of prices for generation and receive the market-clearing price, which varies with demand. Despite claims that this should be highly competitive, we show that the Nash equilibrium in supply schedules implies a high markup on marginal cost and substantial deadweight losses. Further simulations, to show the effect of entry by 1994, produce somewhat lower prices, at the cost of excessive entry; subdividing the generators into five firms would produce better results. more

Topics: Supply (62%), Electricity market (61%), Electricity retailing (59%) more

1,373 Citations

Journal ArticleDOI: 10.1109/6.387140
N.G. Hingorani1Institutions (1)
01 Jun 1995-IEEE Spectrum
Abstract: Changes in customers' needs require improvements in the reliability and quality of the electricity supply This paper describes how the concept of custom power is now becoming familiar The term describes the value-added power that electric utilities and other service providers will offer their customers in the future The improved level of reliability of this power, in terms of reduced interruptions and less variation, will stem from an integrated solution to present problems, of which a prominent feature will be the application of power electronic controllers to utility distribution systems and/or at the supply end of many industrial and commercial customers and industrial parks > more

677 Citations

Open accessJournal ArticleDOI: 10.1126/SCIENCE.1208365
06 Jan 2012-Science
Abstract: The Technology Path to Deep Greenhouse Gas Emissions Cuts by 2050: The Pivotal Role of Electricity James H. Williams, 1,2 Andrew DeBenedictis, 1 Rebecca Ghanadan, 1,3 Amber Mahone, 1 Jack Moore, 1 William R. Morrow III, 4 Snuller Price, 1 Margaret S. Torn 3 * Several states and countries have adopted targets for deep reductions in greenhouse gas emissions by 2050, but there has been little physically realistic modeling of the energy and economic transformations required. We analyzed the infrastructure and technology path required to meet California’s goal of an 80% reduction below 1990 levels, using detailed modeling of infrastructure stocks, resource constraints, and electricity system operability. We found that technically feasible levels of energy efficiency and decarbonized energy supply alone are not sufficient; widespread electrification of transportation and other sectors is required. Decarbonized electricity would become the dominant form of energy supply, posing challenges and opportunities for economic growth and climate policy. This transformation demands technologies that are not yet commercialized, as well as coordination of investment, technology development, and infrastructure deployment. n 2004, Pacala and Socolow (1) proposed a way to stabilize climate using existing green- house gas (GHG) mitigation technologies, vi- sualized as interchangeable, global-scale “wedges” of equivalent emissions reductions. Subsequent work has produced more detailed analyses, but none combines the sectoral granularity, physical and resource constraints, and geographic scale needed for developing realistic technology and policy roadmaps (2–4). We addressed this gap by analyzing the specific changes in infrastructure, technology, cost, and governance required to de- carbonize a major economy, at the state level, that has primary jurisdiction over electricity supply, transportation planning, building standards, and other key components of an energy transition. California is the world’s sixth largest econ- omy and 12th largest emitter of GHGs. Its per capita GDP and GHG emissions are similar to those of Japan and western Europe, and its policy and technology choices have broad rele- vance nationally and globally (5, 6). California’s Assembly Bill 32 (AB32) requires the state to reduce GHG emissions to 1990 levels by 2020, a reduction of 30% relative to business-as-usual assumptions (7). Previous modeling work we per- formed for California’s state government formed the analytical foundation for the state’s AB32 implementation plan in the electricity and natural gas sectors (8, 9). California has also set a target of reducing 2050 emissions 80% below the 1990 level, con- I Energy and Environmental Economics, 101 Montgomery Street, Suite 1600, San Francisco, CA 94104, USA. 2 Monterey Institute of International Studies, 460 Pierce Street, Monterey, CA 93940, USA. 3 Energy and Resources Group, University of Cali- fornia,& Earth Sciences Division, Lawrence Berkeley National Laboratory (LBNL),, Berkeley, CA 94720, USA. 4 Environmental Energy Technologies Division, LBNL, Berkeley, CA 94720, USA. *To whom correspondence should be addressed. E-mail: sistent with an Intergovernmental Panel on Cli- mate Change (IPCC) emissions trajectory that would stabilize atmospheric GHG concentrations at 450 parts per million carbon dioxide equivalent (CO 2 e) and reduce the likelihood of dangerous an- thropogenic interference with climate (10). Work- ing at both time scales, we found a pressing need for methodologies that bridge the analytical gap between planning for shallower, near-term GHG reductions, based entirely on existing commercialized technology, and deeper, long-term GHG reduc- tions, which will depend substantially on technol- ogies that are not yet commercialized. We used a stock-rollover methodology that simulated physical infrastructure at an aggregate level, and built scenarios to explore mitigation options (11, 12). Our model divided California’s economy into six energy demand sectors and two energy supply sectors, plus cross-sectoral eco- nomic activities that produce non-energy and non-CO 2 GHG emissions. The model adjusted the infrastructure stock (e.g., vehicle fleets, build- ings, power plants, and industrial equipment) in each sector as new infrastructure was added and old infrastructure was retired, each year from 2008 to 2050. We constructed a baseline scenario from government forecasts of population and gross state product, combined with regression-based infra- structure characteristics and emissions intensities, producing a 2050 emissions baseline of 875 Mt CO 2 e (Fig. 1). In mitigation scenarios, we used backcasting, setting 2050 emissions at the state target of 85 Mt CO 2 e as a constrained outcome, and altered the emissions intensities of new in- frastructure over time as needed to meet the tar- get, employing 72 types of physical mitigation measures (13). In the short term, measure selec- tion was driven by implementation plans for AB32 and other state policies (table S1). In the long term, technological progress and rates of in- troduction were constrained by physical feasi- bility, resource availability, and historical uptake rates rather than relative prices of technology, en- ergy, or carbon as in general equilibrium models (14). Technology penetration levels in our model are within the range of technological feasibility for the United States suggested by recent assess- ments (table S20) (15, 16). We did not include technologies expected to be far from commercial- ization in the next few decades, such as fusion- based electricity. Mitigation cost was calculated as the difference between total fuel and measure costs in the mitigation and baseline scenarios. Our fuel and technology cost assumptions, including learning curves (tables S4, S5, S11, and S12, and fig. S29), are comparable to those in other recent studies (17). Clearly, future costs are very uncertain over such a long time horizon, especially for technologies that are not yet commercialized. We did not assume explicit life-style changes (e.g., vegetarianism, bicycle transportation), which could have a substantial effect on mitigation requirements and costs (18); behavior change in our model is subsumed within conservation measures and en- ergy efficiency (EE). To ensure that electricity supply scenarios met the technical requirements for maintaining reli- able service, we included an electricity system dispatch algorithm that tested grid operability. Without a dispatch model, it is difficult to de- termine whether a generation mix has infeasibly high levels of intermittent generation. We devel- oped an electricity demand curve bottom-up from sectoral demand, by season and time of day. On the basis of the demand curve, the model con- strained generation scenarios to satisfy in succes- sion the energy, capacity, and system-balancing requirements for reliable operation. The operabil- ity constraint set physical limits on the penetra- tion of different types of generation and specified the requirements for peaking generation, on-grid energy storage, transmission capacity, and out-of- state imports and exports for a given generation mix (table S13 and figs.S20 to S31). It was as- sumed that over the long run, California would not “go it alone” in pursuing deep GHG reduc- tions, and thus that neighboring states would de- carbonize their generation such that the carbon intensity of imports would be comparable to that of California in-state generation (19). Electrification required to meet 80% reduc- tion target. Three major energy system transfor- mations were necessary to meet the target (Fig. 2). First, EE had to improve by at least 1.3% year −1 over 40 years. Second, electricity supply had to be nearly decarbonized, with 2050 emissions in- tensity less than 0.025 kg CO 2 e/kWh. Third, most existing direct fuel uses had to be electrified, with electricity constituting 55% of end-use energy in 2050 versus 15% today. Results for a mitigation scenario, including these and other measures, are shown in Fig. 1. Of the emissions reductions relative to 2050 baseline emissions, 28% came from EE, 27% from decarbonization of electricity generation, 14% from a combination of energy more

Topics: Energy supply (54%), Greenhouse gas (53%), Energy transition (53%) more

618 Citations

Journal ArticleDOI: 10.1109/JSTARS.2009.2020300
Abstract: The contribution of power production by photovoltaic (PV) systems to the electricity supply is constantly increasing. An efficient use of the fluctuating solar power production will highly benefit from forecast information on the expected power production. This forecast information is necessary for the management of the electricity grids and for solar energy trading. This paper presents an approach to predict regional PV power output based on forecasts up to three days ahead provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Focus of the paper is the description and evaluation of the approach of irradiance forecasting, which is the basis for PV power prediction. One day-ahead irradiance forecasts for single stations in Germany show a rRMSE of 36%. For regional forecasts, forecast accuracy is increasing in dependency on the size of the region. For the complete area of Germany, the rRMSE amounts to 13%. Besides the forecast accuracy, also the specification of the forecast uncertainty is an important issue for an effective application. We present and evaluate an approach to derive weather specific prediction intervals for irradiance forecasts. The accuracy of PV power prediction is investigated in a case study. more

Topics: Solar power (58%), Photovoltaic system (56%), Weather forecasting (54%) more

573 Citations

Journal ArticleDOI: 10.1016/J.ENPOL.2006.10.001
01 Apr 2007-Energy Policy
Abstract: The purpose of this study is to estimate the relationships between GDP and electricity consumption in 10 newly industrializing and developing Asian countries using both single data sets and panel data procedures. The empirical results from single data set indicate that the causality directions in the 10 Asian countries are mixed while there is a uni-directional short-run causality running from economic growth to electricity consumption and a bi-directional long-run causality between electricity consumption and economic growth if the panel data procedure is implemented. These empirical findings imply that electricity conservation policies through both rationalizing the electricity supply efficiency improvement to avoid the wastage of electricity and managing demand side to reduce the electricity consumption without affecting the end-user benefits could be initiated without adverse effect on economic growth. The findings on the long-run relationship indicate that a sufficiently large supply of electricity can ensure that a higher level of economic growth. more

Topics: Electricity (54%), Mains electricity (53%), Consumption (economics) (53%) more

538 Citations

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Topic's top 5 most impactful authors

Chris Marnay

11 papers, 344 citations

Michael G. Pollitt

10 papers, 116 citations

Reinhard Madlener

9 papers, 145 citations

Meysam Qadrdan

6 papers, 67 citations

Gert Brunekreeft

6 papers, 94 citations

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