959 resultados para Reactive power market


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Cover title: An evaluation of the economic potential for cogeneration in Illinois.

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Discoloration and mineralization of Reactive Red HE-3B were studied by using a laponite clay-based Fe nanocomposite (Fe-Lap-RD) as a heterogeneous catalyst in the presence of H2O2 and UV light. Our experimental results clearly indicate that Fe-Lap-RD mainly consists of Fe2O3 (meghemite) and Fe2Si4O10(OH)2 (iron silicate hydroxide) which have tetragonal and monoclinic structures, respectively, and has a high specific surface area (472m(2) / g) as well as a high total pore volume (0.547 cm(3)/g). It was observed that discoloration of HE-3B undergoes a much faster kinetics than mineralization of HE-3B. It was also found that initial HE-3B concentration, H2O2 concentration, UV light wavelength and power, and Fe-Lap-RD catalyst loading are the four main factors that can significantly influence the mineralization of HE-3B. At optimal conditions, complete discoloration of 100 mg/L HE-3B can be achieved in 30 min and the total organic carbon removal ratio can attain 76% in 120 min, illustrating that Fe-Lap-RD has a high photo-catalytic activity in the photo-assisted discoloration and mineralization of HE-3B in the presence of UV light (254nm) and H2O2. (C) 2003 Elsevier Science Ltd. All rights reserved.

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The present study adds to the sparse published Australian literature on the size effect, the book to market (BM) effect and the ability of the Fama French three factor model to account for these effects and to improve on the asset pricing ability of the Capital Asset Pricing Model (CAPM). The present study extends the 1981–1991 period examined by Halliwell, Heaney and Sawicki (1999) a further 10 years to 2000 and addresses several limitations and findings of that research. In contrast to Halliwell, Heaney and Sawicki the current study finds the three factor model provides significantly improved explanatory power over the CAPM, and evidence that the BM factor plays a role in asset pricing.

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Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses haw been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

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A hundred years ago the international craze for picture postcards distributed millions of images of popular stage actresses around the world. The cards were bought, sent, and collected by many whose contact with live theatre was sometimes minimal. Veronica Kelly's study of some of these cards sent in Australia indicates the increasing reach of theatrical images and celebrity brought about by the distribution mechanisms of industrial mass modernity. The specific social purposes and contexts of the senders are revealed by cross-reading the images themselves with the private messages on the backs, suggesting that, once outside the industrial framing of theatre or the dramatic one of specific roles, the actress operated as a multiply signifying icon within mass culture – with the desires and consumer power of women major factors in the consumption of the glamour actress card. A study of the typical visual rhetoric of these postcards indicates the authorized modes of femininity being constructed by the major postcard publishers whose products were distributed to theatre fans and non-theatregoers alike through the post. Veronica Kelly is working on a project dealing with commercial managements and stars in early twentieth-century Australian theatre. She teaches in the School of English, Media Studies, and Art History at the University of Queensland, is co-editor of Australasian Drama Studies, and author of databases and articles dealing with colonial and contemporary Australian theatre history and dramatic criticism. Her books include The Theatre of Louis Nowra (1998) and the collection Our Australian Theatre in the 1990s (1998).

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Vector error-correction models (VECMs) have become increasingly important in their application to financial markets. Standard full-order VECM models assume non-zero entries in all their coefficient matrices. However, applications of VECM models to financial market data have revealed that zero entries are often a necessary part of efficient modelling. In such cases, the use of full-order VECM models may lead to incorrect inferences. Specifically, if indirect causality or Granger non-causality exists among the variables, the use of over-parameterised full-order VECM models may weaken the power of statistical inference. In this paper, it is argued that the zero–non-zero (ZNZ) patterned VECM is a more straightforward and effective means of testing for both indirect causality and Granger non-causality. For a ZNZ patterned VECM framework for time series of integrated order two, we provide a new algorithm to select cointegrating and loading vectors that can contain zero entries. Two case studies are used to demonstrate the usefulness of the algorithm in tests of purchasing power parity and a three-variable system involving the stock market.

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The existence of undesirable electricity price spikes in a competitive electricity market requires an efficient auction mechanism. However, many of the existing auction mechanism have difficulties in suppressing such unreasonable price spikes effectively. A new auction mechanism is proposed to suppress effectively unreasonable price spikes in a competitive electricity market. It optimally combines system marginal price auction and pay as bid auction mechanisms. A threshold value is determined to activate the switching between the marginal price auction and the proposed composite auction. Basically when the system marginal price is higher than the threshold value, the composite auction for high price electricity market is activated. The winning electricity sellers will sell their electricity at the system marginal price or their own bid prices, depending on their rights of being paid at the system marginal price and their offers' impact on suppressing undesirable price spikes. Such economic stimuli discourage sellers from practising economic and physical withholdings. Multiple price caps are proposed to regulate strong market power. We also compare other auction mechanisms to highlight the characteristics of the proposed one. Numerical simulation using the proposed auction mechanism is given to illustrate the procedure of this new auction mechanism.

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Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

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Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

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We present a simulator of a hydropower company’s view of its scheme, and its broader market and network context, which has been developed to evaluate advanced displays for control room operations. Although simplified, the simulator captures all the main aspects of scheme operations. The simulator allows controlled studies to be performed that test the effectiveness of current vs advanced display concepts under normal vs unexpected operating conditions that can be scripted into the simulator.

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A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

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Bifurcation analysis is a very useful tool for power system stability assessment. In this paper, detailed investigation of power system bifurcation behaviour is presented. One and two parameter bifurcation analysis are conducted on a 3-bus power system. We also examined the impact of FACTS devices on power system stability through Hopf bifurcation analysis by taking static Var compensator (SVC) as an example. A simplified first-order model of the SVC device is included in the 3-bus sample system. Real and reactive powers are used as bifurcation parameter in the analysis to compare the system oscillatory properties with and without SVC. The simulation results indicate that the linearized system model with SVC enlarge the voltage stability boundary by moving Hopf bifurcation point to higher level of loading conditions. The installation of SVC increases the dynamic stability range of the system, however complicates the Hopf bifurcation behavior of the system

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The deregulation of power industry worldwide has delivered the efficiency gains to the society; meanwhile, the intensity of competition has increased uncertainty and risks to market participants. Consequently, market participants are keen to hedge the market risks and maintain a competitive edge in the market; and this is a good explanation to the flourish of electricity derivative market. In this paper, the authors gave a comprehensive review of derivative contract pricing methods and proposed a new framework for energy derivative pricing to suit the needs of a deregulated electricity market

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A deregulated electricity market is characterized with uncertainties, with both long and short terms. As one of the major long term planning issues, the transmission expansion planning (TEP) is aiming at implementing reliable and secure network support to the market participants. The TEP covers two major issues: technical assessment and financial evaluations. Traditionally, the net present value (NPV) method is the most accepted for financial evaluations, it is simple to conduct and easy to understand. Nevertheless, TEP in a deregulated market needs a more dynamic approach to incorporate a project's management flexibility, or the managerial ability to adapt in response to unpredictable market developments. The real options approach (ROA) is introduced here, which has clear advantage on counting the future course of actions that investors may take, with understandable results in monetary terms. In the case study, a Nordic test system has been testified and several scenarios are given for network expansion planning. Both the technical assessment and financial evaluation have been conducted in the case study.