988 resultados para electric arc simulation


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Nesta dissertação descreve-se uma metodologia de dimensionamento do sistema de tracção para equipar um veículo eléctrico ecológico (VEECO) com inclusão de um sistema de travagem regenerativa. Apresenta-se uma perspectiva geral de diversas topologias de sistemas de tracção utilizadas nos veículos eléctricos e realiza-se a sua comparação através do estudo e análise dos acionamentos electromecânicos que podem ser utilizados nesses sistemas de tracção eléctrica. Utilizando ferramentas de simulação numérica, estuda-se o modelo matemático de um veículo eléctrico com travagem regenerativa. A partir deste modelo matemático é adoptado uma possível configuração para o seu sistema de tracção eléctrica e são obtidas características teóricas de desempenho do veículo eléctrico, através da análise de testes padrão ao veículo. Em banco de ensaios, constrói-se um sistema de tracção eléctrica que permite a validação experimental do modelo matemático do veículo eléctrico. Para a construção deste banco de ensaios foram concebidos os sistemas de tracção eléctrica, de carga mecânica e de controlo e monitorização do banco de ensaios. A validação experimental realiza-se através dos mesmos testes padrão ao veículo eléctrico, como o teste NEDC (New European Driving Cycle), o teste de aceleração entre 0 e 100km/h e o teste de gradeabilidade. Desenvolve-se o dimensionamento do sistema de tracção eléctrica a equipar o VEECO, através da componente de modelação paramétrica do modelo matemático do veículo eléctrico. Com esta metodologia é adoptado um conjunto de variáveis paramétricas relacionadas com os elementos que constituem o sistema de tracção eléctrica do VEECO. Estuda-se a influência destas variáveis paramétricas nas características de desempenho pretendidas para o VEECO. Como resultado da análise de modelação paramétrica é apresentada uma solução para o sistema de tracção eléctrica do VEECO que cumpre a execução do NEDC, apresenta um tempo de aceleração entre 0 e 100km/h inferior a 10 segundos, supera uma gradeabilidade de 10% e uma autonomia de 200 km. O sistema de tracção do VEECO também permite realizar a travagem regenerativa com rendimento até 33%. Possui controlo de tracção e anti bloqueio da roda motora, através de uma unidade de controlo que permite reduzir a potência transmitida ao veio, quando a velocidade da roda de tracção difere do valor de referência da velocidade do veículo. Os conhecimentos adquiridos através do processo de investigação e desenvolvimento, para a realização da presente dissertação permitem apresentar perspectivas de desenvolvimento futuro com aplicação nos sistemas de tracção de veículos eléctricos rodoviários.

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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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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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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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The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

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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).

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The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

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Renewable based power generation has significantly increased over the last years. However, this process has evolved separately from electricity markets, leading to an inadequacy of the present market models to cope with huge quantities of renewable energy resources, and to take full advantage of the presently existing and the increasing envisaged renewable based and distributed energy resources. This paper proposes the modelling of electricity markets at several levels (continental, regional and micro), taking into account the specific characteristics of the players and resources involved in each level and ensuring that the proposed models accommodate adequate business models able to support the contribution of all the resources in the system, from the largest to the smaller ones. The proposed market models are integrated in MASCEM (Multi- Agent Simulator of Competitive Electricity Markets), using the multi agent approach advantages for overcoming the current inadequacy and significant limitations of the presently existing electricity market simulators to deal with the complex electricity market models that must be adopted.

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Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

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The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.

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In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.