935 resultados para Prices.
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Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.
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This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).
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A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.
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This paper addresses the impact of the CO2 opportunity cost on the wholesale electricity price in the context of the Iberian electricity market (MIBEL), namely on the Portuguese system, for the period corresponding to the Phase II of the European Union Emission Trading Scheme (EU ETS). In the econometric analysis a vector error correction model (VECM) is specified to estimate both long–run equilibrium relations and short–run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The model is estimated using daily spot market prices and the four commodities prices are jointly modelled as endogenous variables. Moreover, a set of exogenous variables is incorporated in order to account for the electricity demand conditions (temperature) and the electricity generation mix (quantity of electricity traded according the technology used). The outcomes for the Portuguese electricity system suggest that the dynamic pass–through of carbon prices into electricity prices is strongly significant and a long–run elasticity was estimated (equilibrium relation) that is aligned with studies that have been conducted for other markets.
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This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.
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List of prices totaling 7 pounds, 55 pence [no indication what this list refers to] Sept. 15, 1848.
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List of names and prices signed by Albert W. Sampson, n.d.
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List of prices paid to Dr. Richard King from Dilly Coleman in regard to items such as flour and a live hog which were sold to Dr. King by Mr. Coleman and medical treatment and medicines for Dilly and his family provided by Dr. King. Samuel Woodruff’s name appears on the outside of this list, n.d.
List of prices paid to Dilly Coleman by Doctor Richard .S. King for the board and feeding of a horse
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List (2 pages, handwritten) of prices paid to Dilly Coleman by Doctor Richard .S. King for the board and feeding of a horse. There is a handwritten note on the inner page regarding instructions for feeding the horse, Sept. 1850.
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Schedule of prices for Brown and McDonell, contractors, for sections 1, 2 and 3 of the Port Dalhousie Thorold Railway (1 page, handwritten), Sept. 24, 1856.
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Prices of John Brown’s contracts for Port Dalhousie and Thorold Railway from Geneva Street to Thorold Station (1 page, handwritten), n.d.
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Note from the Port Dalhousie and Thorold Railway to Mrs. E. Parnell with prices for digging a well, moving a hog pen and repairing a fence, n.d.
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Letter regarding prices for the excavation to S.D. Woodruff from Dexter Deverardo, Feb. 22, 1856.
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Estimate of dredging prices, July 14, 1854.