29 resultados para market power

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This paper aims to offer new theoretical and empirical insights into power dynamics in an industrial supplier workshop setting. Theoretically, it advances an institutional perspective on supplier workshops as an important venue in managing, preserving and instituting industrial market power. Based on a detailed ethnographic analysis of an industrial workshop setting, this article investigates the institutional maintenance work of Retail Co. in preserving the power dynamics of market dominance in business exchanges and market structures. Our findings revealed three previously unreported insights into the subtle, but nonetheless pervasive power from institutional maintenance work in an industrial workshop setting. First, the institutional workshop work comprised a cultural performance; constituting socialization practice through a performance game, the power of numbers in field comprehension and an award ceremony. Second, the institutional workshop work mobilized projective agency, stipulating, directing and appealing for the instituting of distinct market rules and collective identities. Finally, the institutional workshop work increases supplier docility and utility via the regulative technologies-of-the-self to enhance business planning, operations and market decision-making practice, without necessarily being seen to be disciplinarian.

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Over the last decade there has been a rapid global increase in wind power stimulated by energy and climate policies. However, as wind power is inherently variable and stochastic over a range of time scales, additional system balancing is required to ensure system reliability and stability. This paper reviews the technical, policy and market challenges to achieving ambitious wind power penetration targets in Ireland’s All-Island Grid and examines a number of measures proposed to address these challenges. Current government policy in Ireland is to address these challenges with additional grid reinforcement, interconnection and open-cycle gas plant. More recently smart grid combined with demand side management and electric vehicles have also been presented as options to mitigate the variability of wind power. In addition, the transmission system operators have developed wind farm specific grid codes requiring improved turbine controls and wind power forecasting techniques.

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Wind energy has been identified as key to the European Union’s 2050 low carbon economy. However, as wind is a variable resource and stochastic by nature, it is difficult to plan and schedule the power system under varying wind power generation. This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact of the magnitude and variance of the offshore wind power forecast error on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price is analysed. The main findings of this research are that the magnitude of the offshore wind power forecast error has the largest impact on system generation costs and dispatch-down of wind, but the variance of the offshore wind power forecast error has the biggest impact on emissions costs and system marginal price. Overall offshore wind power forecast error variance results in a system marginal price increase of 9.6% in 2050.

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This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

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This paper tests a simple market fraction asset pricing model with heterogeneous
agents. By selecting a set of structural parameters of the model through a systematic procedure, we show that the autocorrelations (of returns, absolute returns and squared returns) of the market fraction model share the same pattern as those of the DAX 30. By conducting econometric analysis via Monte Carlo simulations, we characterize these power-law behaviours and find that estimates of the power-law decay indices, the (FI)GARCH parameters, and the tail index of the selected market fraction model closely match those of the DAX 30. The results strongly support the explanatory power of the heterogeneous agent models.

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The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

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Utilization of renewable energy sources and energy storage systems is increasing with fostering new policies on energy industries. However, the increase of distributed generation hinders the reliability of power systems. In order to stabilize them, a virtual power plant emerges as a novel power grid management system. The VPP has a role to make a participation of different distributed energy resources and energy storage systems. This paper defines core technology of the VPP which are demand response and ancillary service concerning about Korea, America and Europe cases. It also suggests application solutions of the VPP to V2G market for restructuring national power industries in Korea.

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The design, construction and subsequent operation of the 75 kW oscillating water column wave power plant on the Isle of Islay has provided a significant insight into the practicality of wave power conversion. The development of wave power plant poses a significant design and construction challenge for not only civil but also mechanical and electrical engineers. The plant must withstand the immense forces imposed during storms, yet efficiently convert the slow cyclic motion of waves into a useful energy source such as electricity and do so at a price competitive with other forms of generation. In addition, the hostile marine environment hampers the construction process and the variability of the wave resource poses problems for electrical control and grid integration. Many sceptics consider wave power conversion to be too difficult, too expensive and too variable to justify the effort and expense necessary to develop this technology. However, the authors contend that with modular wave power systems developed from the practical experience gained with the Islay plant, wave power is a viable technology with a considerable world market potential. However, this technology is still at the early stages of development and will require the construction of a number of different prototypes before there is extensive commercial exploitation.

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This paper examines the relation between technical possibilities, liberal logics, and the concrete reconfiguration of markets. It focuses on the enrolling of innovations in communication and information technologies into the markets traditionally dominated by stock exchanges. With the development of capacities to trade on-screen, the power of incumbent market makers has been challenged as a less stable array of competing quasi-public and private marketplaces emerges. Developing a case study of the Toronto Stock Exchange, I argue that narrative emphasis on the performative power of sociotechnical innovations, the deterritorialisation of financial relations, and the erosion of state capacities needs qualification. A case is made for the importance of developing an understanding of: the spaces of encounter between emerging social technologies and property rights, rules of exchange, and structures of governance; and the interplay of orderings of different institutional composition and spatial reach in the reconfiguration of market architectures. Only then can a better grasp be gained of the evolving dynamics between making markets, the regulatory powers of the state, and their delimitations.

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Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.

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This paper presents a new method for transmission loss allocation in a deregulated electrical power market. The proposed method is based on physical flow through transmission lines. The contributions of individual loads to the line flows are used as basis for allocating transmission losses to different loads. With minimum assumptions, that sound to be reasonable and cannot be rejected, a novel loss allocation formula is derived. The assumptions made are: a number of currents sharing a transmission line distribute themselves over the cross section in the same manner; that distribution causes the minimum possible power loss. Application of the proposed method is straightforward. It requires only a solved power flow and any simple algorithm for power flow tracing. Both active and reactive powers are considered in the loss allocation procedure. Results of application show the accuracy of the proposed method compared with the commonly used procedures.

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Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.

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Globally on-shore wind power has seen considerable growth in all grid systems. In the coming decade off-shore wind power is also expected to expand rapidly. Wind power is variable and intermittent over various time scales because it is weather dependent. Therefore wind power integration into traditional grids needs additional power system and electricity market planning and management for system balancing. This extra system balancing means that there is additional system costs associated with wind power assimilation. Wind power forecasting and prediction methods are used by system operators to plan unit commitment, scheduling and dispatch and by electricity traders and wind farm owners to maximize profit. Accurate wind power forecasting and prediction has numerous challenges. This paper presents a study of the existing and possible future methods used in wind power forecasting and prediction for both on-shore and off-shore wind farms.

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The growth of renewable power sources, distributed generation and the potential for alternative fuelled modes of transport such as electric vehicles has led to concerns over the ability of existing grid systems to facilitate such diverse portfolio mixes in already congested power systems. Internationally the growth in renewable energy sources is driven by government policy targets associated with the uncertainties of fossil fuel supplies, environmental issues and a move towards energy independence. Power grids were traditionally designed as vertically integrated centrally managed entities with fully dispatchable generating plant. Renewable power sources, distributed generation and alternative fuelled vehicles will place these power systems under additional stresses and strains due to their different operational characteristics. Energy storage and smart grid technologies are widely proposed as the tools to integrate these future diverse portfolio mixes within the more conventional power systems. The choice in these technologies is determined not only by their location on the grid system, but by the diversification in the power portfolio mix, the electricity market and the operational demands. This paper presents a high level technical and economic overview of the role and relevance of electrical energy storage and smart grid technologies in the next generation of renewable power systems.