930 resultados para Wholesale energy market


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The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

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The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

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In this paper we analyse the behaviour of the EU market for CO2 emission allowances; specifically, we focus on the contracts maturing in the Kyoto Protocol's second period of application (2008 to 2012). We calibrate the underlying parameters for the allowance price in the long run and we also calibrate those from the Spanish wholesale electricity market. This information is then used to assess the option to install a carbon capture and storage (CCS) unit in a coal-fired power plant. We use a two-dimensional binomial lattice where costs and profits are valued and the optimal investment time is determined. In other words, we study the trigger allowance prices above which it is optimal to install the capture unit immediately. We further analyse the impact of several variables on the critical prices, among them allowance price volatility and a hypothetical government subsidy. We conclude that, at current permit prices, from a financial point of view, immediate installation does not seem justified. This need not be the case, though, if carbon market parameters change dramatically and/or a specific policy to promote these units is adopted.

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Increasing installed capacities of wind power in an effort to achieve sustainable power systems for future generations pose problems for system operators. Volatility in generation volumes due to the adoption of stochastic wind power is increasing. Storage has been shown to act as a buffer for these stochastic energy sources, facilitating the integration of renewable energy into a historically inflexible power system. This paper examines peak and off peak benefits realised by installing a short term discharge storage unit in a system with a high penetration of wind power in 2020. A fully representative unit commitment and economic dispatch model is used to analyse two scenarios, one ‘with storage’ and one ‘without storage’. Key findings of this preliminary study show that wind curtailment can be reduced in the storage scenario, with a larger reduction in peak time ramping of gas generators is realised.

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica na Área de Especialização de Energia

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Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

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As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

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The integration of Plug-in electric vehicles in the transportation sector has a great potential to reduce oil dependency, the GHG emissions and to contribute for the integration of renewable sources into the electricity generation mix. Portugal has a high share of wind energy, and curtailment may occur, especially during the off-peak hours with high levels of hydro generation. In this context, the electric vehicles, seen as a distributed storage system, can help to reduce the potential wind curtailments and, therefore, increase the integration of wind power into the power system. In order to assess the energy and environmental benefits of this integration, a methodology based on a unit commitment and economic dispatch is adapted and implemented. From this methodology, the thermal generation costs, the CO2 emissions and the potential wind generation curtailment are computed. Simulation results show that a 10% penetration of electric vehicles in the Portuguese fleet would increase electrical load by 3% and reduce wind curtailment by only 26%. This results from the fact that the additional generation required to supply the electric vehicles is mostly thermal. The computed CO2 emissions of the EV are 92 g CO2/kWh which become closer to those of some new ICE engines.

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The liberalisation of the energy market goes back to the 1990s, when it was impelled by the European legislator. Since then, three legislative packages, temporarily successive, were approved. Those packages contained the measures to be implemented in order to deepen the internal energy market. Besides the opening up of several national markets to competition, the European legislator aimed the creation of a real internal energy market within the European Union. The unbundling regime was one of the most important steps with respect to the liberalisation process. The introduction of these rules ensured independence to the various market operators. A real and effective right of choice was granted to the consumers so they may choose their electricity and natural gas supplier. Therefore, the activity of comercialisation is subject to competition. However, some activities of the electricity’s and natural gas’ chain of value, namely the activities of transportation and distribution, were kept under regulation rules. Even though it may seem odd, the assignment of important competences and strong powers to a regulatory authority was essential in order to achieve the liberalisation process’ goals. Electricity and natural gas are essential public goods; therefore the market operators are legally bound to public service obligations, such as the security, the universality and the continuity of the supply. The performance of these obligations may become, in some cases, unprofitable for those operators. For such reason, the protection of the consumers’ rights shall only be properly defended if there is a regulatory authority that monitors the behaviour of the operators and sanctions the failure to comply with the public service obligations. Portugal, as a Member State of the European Union, transposed into the national legal order the European directives concerning the liberalisation process. This transposition has caused radical changes to the electricity and natural gas’ national markets. The Entidade Reguladora dos Serviços Energéticos also suffered various mutations in order to keep up with the regulatory demands regarding the liberalisation process.

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La investigación realizada, analiza las relaciones bilaterales comerciales que Brasil lleva a cabo con la Unión Europea y con China, basándose en la producción de biocombustibles. Lo que se busca demostrar con este estudio es que Brasil necesita y utiliza las relaciones que mantiene con los otros dos actores, que son grandes potencias a nivel internacional, como herramientas para promover la compra de los biocombustibles por parte de éstos y de potenciales socios comerciales que puedan surgir en el futuro. Tales relaciones deben incrementar el mercado de los biocombustibles en el cual Brasil lidera, y que significa sólo una mínima parte dentro del mercado energético mundial.

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En el año 2010 el gobierno de Canadá pública su estrategia de política exterior hacia el Ártico, en la cual manifiesta que esta región es una de las principales prioridades del Gobierno de Stephen Harper en materia de política exterior. Así las cosas, a partir de la perspectiva teórica del realismo neoclásico la investigación se enfoca en analizar por qué la seguridad nacional y la prosperidad económica son los principales intereses de este Gobierno en la zona.

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This paper provides an overview of the reduction targets that Ireland has set in the context of decarbonising their electricity generation through the use of renewables. The main challenges associated with integrating high levels (>20% of installed capacity) of non-dispatchable renewable generation are identified. The rising complexity of the challenge as renewable penetration levels increase is highlighted. A list of relevant research questions is then proposed, and an overview is given into the previous work that has gone into answering some of them. In particular, studies into the Irish energy market are identified, the current knowledge gap is described, and areas of necessary future research are suggested

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Policy makers are in broad agreement that demand response should play a major role in EU electricity systems and provide much needed future system flexibility. Yet, little demand response has been forthcoming in member states to date. This paper identifies some of the technical potential for demand response, based on empirical data from one UK demand aggregator. Half-hourly electricity readings of demand during normal operation and during response events have been analysed for different industry and service sectors. We review these findings in the context of ongoing EU policy developments with particular focus on the role appropriate arrangements to enhance the available resource. We conclude that in some sectors appropriate policy and regulation could triple the available response capacity and thereby lead to stronger commercial uptake of demand response.

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Despite the undisputed benefits associated with photovoltaic (PV) technology, the financial barrier acts as the major hurdle before it is seen as a commercial competitive form of renewable energy. Many studies have been performed outlining the life cycle energy benefits of PV technology. However, there has been limited number of studies dedicated to the life cycle cost impacts. The aim of this paper is to identify whether life cycle cost analysis is the best approach to determining the cost contributors or savings associated with this technology. This paper has been structured similarly to previous life cycle energy studies to consider the cost implications involved within each area of the products lifecycle. Amongst many new developments, traditional silicon based units have been challenged by the introduction of new organic systems; and recent studies highlight that these systems offer major cost reductions. Based on an analysis of current literature, this paper identifies that the recent growth and development of both organic and silicon based systems have had a considerable effect on the cost of PV cells. The competitive nature of the renewable energy market will also impact on a life cycle cost analysis; and any potential findings will valid for a limited timeframe.

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The aim of this research is to examine the efficiency of different aggregation algorithms to the forecasts obtained from individual neural network (NN) models in an ensemble. In this study an ensemble of 100 NN models are constructed with a heterogeneous architecture. The outputs from NN models are combined by three different aggregation algorithms. These aggregation algorithms comprise of a simple average, trimmed mean, and a Bayesian model averaging. These methods are utilized with certain modifications and are employed on the forecasts obtained from all individual NN models. The output of the aggregation algorithms is analyzed and compared with the individual NN models used in NN ensemble and with a Naive approach. Thirty-minutes interval electricity demand data from Australian Energy Market Operator (AEMO) and the New York Independent System Operator's web site (NYISO) are used in the empirical analysis. It is observed that the aggregation algorithm perform better than many of the individual NN models. In comparison with the Naive approach, the aggregation algorithms exhibit somewhat better forecasting performance.