984 resultados para Residential electricity simulation


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Num mercado de electricidade competitivo onde existe um ambiente de incerteza, as empresas de geração adoptam estratégias que visam a maximização do lucro, e a minimização do risco. Neste contexto, é de extrema importância para desenvolver uma estratégia adequada de gestão de risco ter em conta as diferentes opções de negociação de energia num mercado liberalizado, de forma a suportar a tomada de decisões na gestão de risco. O presente trabalho apresenta um modelo que avalia a melhor estratégia de um produtor de energia eléctrica que comercializa num mercado competitivo, onde existem dois mercados possíveis para a transacção de energia: o mercado organizado (bolsa) e o mercado de contratos bilaterais. O produtor tenta maximizar seus lucros e minimizar os riscos correspondentes, seleccionando o melhor equilíbrio entre os dois mercados possíveis (bolsa e bilateral). O mercado de contratos bilaterais visa gerir adequadamente os riscos inerentes à operação de mercados no curto prazo (mercado organizado) e dar o vendedor / comprador uma capacidade real de escolher o fornecedor com que quer negociar. O modelo apresentado neste trabalho faz uma caracterização explícita do risco no que diz respeito ao agente de mercado na questão da sua atitude face ao risco, medido pelo Value at Risk (VaR), descrito neste trabalho por Lucro-em-Risco (PAR). O preço e os factores de risco de volume são caracterizados por um valor médio e um desvio padrão, e são modelizados por distribuições normais. Os resultados numéricos são obtidos utilizando a simulação de Monte Carlo implementado em Matlab, e que é aplicado a um produtor que mantém uma carteira diversificada de tecnologias de geração, para um horizonte temporal de um ano. Esta dissertação está organizada da seguinte forma: o capítulo 1, 2 e 3 descrevem o estado-da-arte relacionado com a gestão de risco na comercialização de energia eléctrica. O capítulo 4 descreve o modelo desenvolvido e implementado, onde é também apresentado um estudo de caso com uma aplicação do modelo para avaliar o risco de negociação de um produtor. No capítulo 5 são apresentadas as principais conclusões.

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A energia eléctrica é um bem essencial para a maioria das sociedades. O seu fornecimento tem sido encarado como um serviço público, da responsabilidade dos governos, através de empresas monopolistas, públicas e privadas. O Mercado Ibérico de Electricidade (MIBEL) surge com o objectivo da integração e cooperação do sector eléctrico Português e Espanhol, no qual é possível negociar preços e volumes de energia. Actualmente, as entidades podem negociar através de um mercado bolsista ou num mercado de contratos bilaterais. Uma análise dos mercados de electricidade existentes mostra que estes estão longe de estarem liberalizados. As tarifas não reflectem o efeito da competitividade. Além disso, o recurso a contratos bilaterais limita frequentemente os clientes a um único fornecedor de energia eléctrica. Nos últimos anos, têm surgido uma série de ferramentas computacionais que permitem simular, parte ou a totalidade, dos mercados de electricidade. Contudo, apesar das suas potencialidades, muitos simuladores carecem de flexibilidade e generalidade. Nesta perspectiva, esta dissertação tem como principal objectivo o desenvolvimento de um simulador de mercados de energia eléctrica que possibilite lidar com as dificuldades inerentes a este novo modelo de mercado, recorrendo a agentes computacionais autónomos. A dissertação descreve o desenho e a implementação de um simulador simplificado para negociação de contratos bilaterais em mercados de energia, com particular incidência para o desenho das estratégias a utilizar pelas partes negociais. Além disso, efectua-se a descrição de um caso prático, com dados do MIBEL. Descrevem-se também várias simulações computacionais, envolvendo retalhistas e consumidores de energia eléctrica, que utilizam diferentes estratégias negociais. Efectua-se a análise detalhada dos resultados obtidos. De forma sucinta, os resultados permitem concluir que as melhores estratégias para cada entidade, no caso prático estudado, são: a estratégia de concessões fixas, para o retalhista, e a estratégia de concessões baseada no volume de energia, para o consumidor.

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This paper presents a new integrated model for the simulation of wind energy systems. The proposed model is more realistic and accurate, considering a variable-speed wind turbine, two-mass rotor, permanent magnet synchronous generator (PMSG), different power converter topologies, and filters. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with PMSG/full-power converter topology, based on fractional-order controllers. Comprehensive simulation studies are carried out with matrix and multilevel power converter topologies, in order to adequately assert the system performance in what regards the quality of the energy injected into the electric grid. Finally, conclusions are duly drawn.

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Topological defects in foam, either isolated (disclinations and dislocations) or in pairs, affect the energy and stress, and play an important role in foam deformation. Surface Evolver simulations were performed on large finite clusters of bubbles. These allow us to evaluate the effect of the topology of the defects, and the distance between defects, on the energy and pressure of foam clusters of different sizes. The energy of such defects follows trends similar to known analytical results for a continuous medium.

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Because of the adverse effect of CO2 from fossil fuel combustion on the earth's ecosystems, the most cost-effective method for CO2 capture is an important area of research. The predominant process for CO2 capture currently employed by industry is chemical absorption in amine solutions. A dynamic model for the de-absorption process was developed with monoethanolamine (MEA) solution. Henry's law was used for modelling the vapour phase equilibrium of the CO2, and fugacity ratios calculated by the Peng-Robinson equation of state (EOS) were used for H2O, MEA, N-2 and O-2. Chemical reactions between CO2 and MEA were included in the model along with the enhancement factor for chemical absorption. Liquid and vapour energy balances were developed to calculate the liquid and vapour temperature, respectively.

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This paper describes an assessment of the impact of the enforcement of the European carbon dioxide (CO2) emissions trading scheme on the Portuguese chemical industry, based on cost structure, CO2 emissions, electricity consumption and allocated allowances data from a survey to four Portuguese representative units of the chemical industry sector, and considering scenarios that allow the estimation of increases on both direct and indirect production costs. These estimated cost increases were also compared with similar data from other European Industries, found in the references and with conclusions from simulation studies. Thus, it was possible to ascertain the impact of buying extra CO2 emission permits, which could be considered as limited. It was also found that this impact is somewhat lower than the impacts for other industrial sectors.

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Microcrystalline silicon is a two-phase material. Its composition can be interpreted as a series of grains of crystalline silicon imbedded in an amorphous silicon tissue, with a high concentration of dangling bonds in the transition regions. In this paper, results for the transport properties of a mu c-Si:H p-i-n junction obtained by means of two-dimensional numerical simulation are reported. The role played by the boundary regions between the crystalline grains and the amorphous matrix is taken into account and these regions are treated similar to a heterojunction interface. The device is analysed under AM1.5 illumination and the paper outlines the influence of the local electric field at the grain boundary transition regions on the internal electric configuration of the device and on the transport mechanism within the mu c-Si:H intrinsic layer.

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The portfolio generating the iTraxx EUR index is modeled by coupled Markov chains. Each of the industries of the portfolio evolves according to its own Markov transition matrix. Using a variant of the method of moments, the model parameters are estimated from a data set of Standard and Poor's. Swap spreads are evaluated by Monte-Carlo simulations. Along with an actuarially fair spread, at least squares spread is considered.

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In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

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A survey was conducted among students of the Accounting and Administration undergraduate degree at ISCAP – IPP (School of Accounting and Administration of Polytechnic Institute of Porto) in order to understand their perception value of their course Business Simulation (BS). This course is provided in a business environment where students can learn by doing through the management of a company as they were in the real life, but risk-free. The learning tasks are provided in an action-oriented format to maximize the learning process. Students learn by doing a set of tasks every session and have also to produce reports and presentations during the course. BS is part of the undergraduate degree of Accounting and Administration at ISCAP – IPP since the beginning of 2003. The questionnaire we used captured the students’ perception about general and specific skills and competencies considered important for managers and accountants in the real life, about the methodology used in the course, which is totally different from the traditional form, and also about the adequacy of the course included as part of the undergraduate degree. The results showed that students’ perception is highly positive and almost all of them think they improve the skills needed for a job during the course. These results are consistent with [1] Adler and Milne’s research in which the authors found that students agree with the use of action-oriented learning tasks in order to provide them the needed attitudes, skills, and knowledge. The improvement of group skills is the most important issue for students, which can be understandable as BS is the only course from the degree in Accounting and Administration they really have to work in groups.

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With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

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In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

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This paper presents MASCEM - Multi-Agent Simulator for Electricity Markets improvement towards an enlarged model for Seller Agents coalitions. The simulator has been improved, both regarding its user interface and internal structure. The OOA, used as development platform, version was updated and the multi-agent model was adjusted for implementing and testing several negotiations regarding Seller agents’ coalitions. Seller coalitions are a very important subject regarding the increased relevance of Distributed Generation under liberalised electricity markets.

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A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

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In this work it is proposed the design of a mobile system to assist car drivers in a smart city environment oriented to the upcoming reality of Electric Vehicles (EV). Taking into account the new reality of smart cites, EV introduction, Smart Grids (SG), Electrical Markets (EM), with deregulation of electricity production and use, drivers will need more information for decision and mobility purposes. A mobile application to recommend useful related information will help drivers to deal with this new reality, giving guidance towards traffic, batteries charging process, and city mobility infrastructures (e. g. public transportation information, parking places availability and car & bike sharing systems). Since this is an upcoming reality with possible process changes, development must be based on agile process approaches (Web services).