61 resultados para Java Virtual Machine
Resumo:
The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.
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Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.
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O cancro colo - rectal (CCR) é um problema de saúde mundial, estando associadas elevadas taxas de mortalidade e morbilidade. A maioria de CCR deriva de pólipos adenomatosos.. Um estudo retrospectivo, efectuado no serviço de Radiologia, dos achados imagiológicos típicos e atípicos, entre Janeiro de 2008 e Junho 2010. A Colonoscopia Virtual, apresenta uma sensibilidade elevada na detecção de lesões, com dimensão superior a 10mm, permitindo um diagnóstico precoce, é um exame rápido, pouco invasivo, não há necessidade de sedação e é efectuada em ambulatório.
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Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.
Resumo:
The development of renewable energy sources and Distributed Generation (DG) of electricity is of main importance in the way towards a sustainable development. However, the management, in large scale, of these technologies is complicated because of the intermittency of primary resources (wind, sunshine, etc.) and small scale of some plants. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. VPPs can ensure a secure, environmentally friendly generation and optimal management of heat, electricity and cold as well as optimal operation and maintenance of electrical equipment, including the sale of electricity in the energy market. For attaining these goals, there are important issues to deal with, such as reserve management strategies, strategies for bids formulation, the producers’ remuneration, and the producers’ characterization for coalition formation. This chapter presents the most important concepts related with renewable-based generation integration in electricity markets, using VPP paradigm. The presented case studies make use of two main computer applications:ViProd and MASCEM. ViProd simulates VPP operation, including the management of plants in operation. MASCEM is a multi-agent based electricity market simulator that supports the inclusion of VPPs in the players set.
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Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.
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This paper presents a new architecture for the MASCEM, a multi-agent electricity market simulator. This is implemented in a Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) provides a DLL interface between Win-Prolog and other applications. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets.
Resumo:
Nowadays, there is a growing environmental concern about were the energy that we use comes from, bringing the att ention on renewable energies. However, the use and trade of renewable e nergies in the market seem to be complicated because of the lack of guara ntees of generation, mainly in the wind farms. The lack of guarantees is usually addressed by using a reserve generation. The aggregation of DG p lants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of wind generation technologies, making them valuable in electricity markets. This paper presents some resul ts obtained with a simulation tool (ViProd) developed to support VPPs in the analysis of their operation and management methods and of their strat egies effects.
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The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.
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Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files
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Over time, XML markup language has acquired a considerable importance in applications development, standards definition and in the representation of large volumes of data, such as databases. Today, processing XML documents in a short period of time is a critical activity in a large range of applications, which imposes choosing the most appropriate mechanism to parse XML documents quickly and efficiently. When using a programming language for XML processing, such as Java, it becomes necessary to use effective mechanisms, e.g. APIs, which allow reading and processing of large documents in appropriated manners. This paper presents a performance study of the main existing Java APIs that deal with XML documents, in order to identify the most suitable one for processing large XML files.
Resumo:
Introduction: A major focus of data mining process - especially machine learning researches - is to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. Since imaging techniques like MPI – Myocardial Perfusion Imaging on Nuclear Cardiology, can implicate a huge part of the daily workflow and generate gigabytes of data, there could be advantages on Computerized Analysis of data over Human Analysis: shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc.Objectives: The aim of this study relates with the evaluation of the efficacy of this methodology on the evaluation of MPI Stress studies and the process of decision taking concerning the continuation – or not – of the evaluation of each patient. It has been pursued has an objective to automatically classify a patient test in one of three groups: “Positive”, “Negative” and “Indeterminate”. “Positive” would directly follow to the Rest test part of the exam, the “Negative” would be directly exempted from continuation and only the “Indeterminate” group would deserve the clinician analysis, so allowing economy of clinician’s effort, increasing workflow fluidity at the technologist’s level and probably sparing time to patients. Methods: WEKA v3.6.2 open source software was used to make a comparative analysis of three WEKA algorithms (“OneR”, “J48” and “Naïve Bayes”) - on a retrospective study using the comparison with correspondent clinical results as reference, signed by nuclear cardiologist experts - on “SPECT Heart Dataset”, available on University of California – Irvine, at the Machine Learning Repository. For evaluation purposes, criteria as “Precision”, “Incorrectly Classified Instances” and “Receiver Operating Characteristics (ROC) Areas” were considered. Results: The interpretation of the data suggests that the Naïve Bayes algorithm has the best performance among the three previously selected algorithms. Conclusions: It is believed - and apparently supported by the findings - that machine learning algorithms could significantly assist, at an intermediary level, on the analysis of scintigraphic data obtained on MPI, namely after Stress acquisition, so eventually increasing efficiency of the entire system and potentially easing both roles of Technologists and Nuclear Cardiologists. In the actual continuation of this study, it is planned to use more patient information and significantly increase the population under study, in order to allow improving system accuracy.
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O objectivo da Realidade Virtual é simples de entender mas muito difícil de implementar: criar ambientes completamente indiferenciáveis do mundo real com os quais se possa interagir de um modo natural. Desde a criação do Sensorama por Morton Heiling em 1962, passando pela difusão do conceito pelo público geral na década de 90 até os dias de hoje, a evolução da Realidade Virtual tem sido constante. Este conjunto de tecnologias tem estado envolvido por uma certa descrença por parte da sociedade, motivada pelas grandes expectativas que lhe foram atribuídas e pelo estado de desenvolvimento do hardware aquando do seu auge. No entanto, actualmente assiste-se a um ressurgimento do seu interesse no público geral com a introdução de imagem estereoscópica no cinema ou o sucesso dos controladores da consola Nintendo Wii. Hoje em dia as suas aplicações são muito variadas: desde o treino de pilotos de avião ao tratamento de fobias, passando pela industria do entretenimento e a visita virtual de locais com interesse histórico ou turístico. O objectivo desta tese de mestrado é explorar uma área que ainda não tem sido muito abrangida pela Realidade Virtual e que cobre também aspectos educacionais e lúdicos de modo a ser um factor de atracção para os estudantes do ensino secundário: a simulação de instrumentos musicais. Para tal foi implementado um sistema capaz de simular instrumentos musicais de percussão (uma bateria) utilizando imagem estereoscópica, som posicional e interfaces com o utilizador realistas. Os resultados obtidos nas sessões de avaliação efectuadas por alunos recentemente ingressados no ensino superior demonstram que o sistema desenvolvido, bem como a inovação em interfaces do utilizador com os dispositivos electrónicos de uma forma geral, constituem um meio efectivo na sua motivação para a escolha de um curso na área da engenharia.
Resumo:
Este trabalho é uma parte do tema global “Suporte à Computação Paralela e Distribuída em Java”, também tema da tese de Daniel Barciela no mestrado de Engenharia Informática do Instituto Superior de Engenharia do Porto. O seu objetivo principal consiste na definição/criação da interface com o programador, assim como também abrange a forma como os nós comunicam e cooperam entre si para a execução de determinadas tarefas, de modo a atingirem um único objetivo global. No âmbito desta dissertação foi realizado um estudo prévio relativamente aos modelos teóricos referentes à computação paralela, assim como também foram analisadas linguagens e frameworks que fornecem suporte a este mesmo tipo de computação. Este estudo teve como principal objetivo a análise da forma como estes modelos e linguagens permitem ao programador expressar o processamento paralelo no desenvolvimento das aplicações. Como resultado desta dissertação surgiu a framework denominada Distributed Parallel Framework for Java (DPF4j), cujo objetivo principal é fornecer aos programadores o suporte para o desenvolvimento de aplicações paralelas e distribuídas. Esta framework foi desenvolvida na linguagem Java. Esta dissertação contempla a parte referente à interface de programação e a toda a comunicação entre nós cooperantes da framework DPF4j. Por fim, foi demonstrado através dos testes realizados que a DPF4j, apesar de ser ainda um protótipo, já demonstra ter uma performance superior a outras frameworks e linguagens que possuem os mesmos objetivos.