938 resultados para Generation from examples
Resumo:
The present work aims to study the feasibility of deploying a farm of sea current turbines for electricity generation in Portugal. An approach to the tides, which are they, how they are formed, its prediction, is held. It is also conducted a study about the energy of sea currents and it is presented some technology about ocean currents too. A model of tidal height and velocity of the currents it is also developed. The energy produced by a hypothetical park, built in Sines (Portugal), is calculated and afterwards, an economical assessment is performed for two possible scenarios and a sensitivity analysis of NVP (Net Present Value) and LCOE (Levelized Cost of Energy) is figured. The conclusions about the feasibility of the projects are also presented. Despite being desired due to its predictability, this energy source is not yet economically viable as it is in an initial state of development. To push investment in this technology a feed-in tariff of, at least €200/MWh, should be considered.
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We propose a low complexity technique to generate amplitude correlated time-series with Nakagami-m distribution and phase correlated Gaussian-distributed time-series, which is useful for the simulation of ionospheric scintillation effects in GNSS signals. To generate a complex scintillation process, the technique requires solely the knowledge of parameters Sa (scintillation index) and σφ (phase standard deviation) besides the definition of models for the amplitude and phase power spectra. The concatenation of two nonlinear memoryless transformations is used to produce a Nakagami-distributed amplitude signal from a Gaussian autoregressive process.
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This paper describes a modular solid-state switching cell derived from the Marx generator concept to be used in topologies for generating multilevel unipolar and bipolar high-voltage (HV) pulses into resistive loads. The switching modular cell comprises two ON/OFF semiconductors, a diode, and a capacitor. This cell can be stacked, being the capacitors charged in series and their voltages balanced in parallel. To balance each capacitor voltage without needing any parameter measurement, a vector decision diode algorithm is used in each cell to drive the two switches. Simulation and experimental results, for generating multilevel unipolar and bipolar HV pulses into resistive loads are presented.
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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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We show that a self-generated set of combinatorial games, S. may not be hereditarily closed but, strong self-generation and hereditary closure are equivalent in the universe of short games. In [13], the question "Is there a set which will give a non-distributive but modular lattice?" appears. A useful necessary condition for the existence of a finite non-distributive modular L(S) is proved. We show the existence of S such that L(S) is modular and not distributive, exhibiting the first known example. More, we prove a Representation Theorem with Games that allows the generation of all finite lattices in game context. Finally, a computational tool for drawing lattices of games is presented. (C) 2014 Elsevier B.V. All rights reserved.
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In the São Paulo State, Brazil, where the Biomphalaria tenagophila is the intermediate host, the Ribeira Valley is an important endemic schistosomiasis mansoni area. During last eleven years there has been intense control measures focusing on schistosomiasis. The efforts have been concentrated in the municipalities of Pedro de Toledo and Itariri. We determined the susceptibility of B. tenagophila to sympatric strain of S. mansoni, both recently isolated from Itariri field. In 1988, this strain was isolated and maintained in the experimental model: Swiss mice - sympatric B. tenagophila. The second generation of the worm was evaluated. The snail were divided in the three groups of 60 snails each. One group was exposed to 1 miracidium and other to 10. The third group was the control. The mortality and the shedding of cercariae were checked during 78 days. After that, the positive snails were observed until they ceased to shed cercariae. The exposed molluscs showed mortality rates of 23% and 31% and infection indexes were of 8% and 60% to 1 and 10 miracidia respectively. The mortality was of 22% in the control group. The periods of shedding cercariae in the two groups were 82 and 104 days. We can conclude that B. tenagophila is an effective intermediate host to the sympatric strain of S. mansoni sympatric strain
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This paper describes preliminary work on the generation of synthesis gas from water electrolysis using graphite electrodes without the separation of the generated gases. This is an innovative process, that has no similar work been done earlier. Preliminary tests allowed to establish correlations between the applied current to the electrolyser and flow rate and composition of the generated syngas, as well as a characterisation of generated carbon nanoparticles. The obtained syngas can further be used to produce synthetic liquid fuels, for example, methane, methanol or DME (dimethyl ether) in a catalytic reactor, in further stages of a present ongoing project, using the ELECTROFUEL® concept. The main competitive advantage of this project lies in the built-in of an innovative technology product, from RE (renewable energy) power in remote locations, for example, islands, villages in mountains as an alternative for energy storage for mobility constraints.
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Dissertação submetida à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Teatro e Comunidade.
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B. tenagophila snails from Ouro Branco, MG, showed positivity for S. mansoni, with infection rates of 5%, 10%, (SJ strain), and 1% (LE strain) using a pool of miracidia. The mollusks were found to be susceptive from the 3rd generation reared in laboratory onwards. The B. tenagophila (OB, MG) when individually exposed to 10 miracidia, showed infection rate of 2% for LE strain. B. glabrata snails from Gagé, MG, showed a positivity rate of 58% for S. mansoni (LE strain), under experimental conditions. The B. tenagophila from Cabo Frio, RJ and B. glabrata from Belo Horizonte, MG used as a control for SJ strain showed infection rates of 47% - 85% and 36% respectivily. For the LE strain, B. glabrata (BH, MG) used as control showed infection rate of 40% - 75%.
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The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.
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Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.
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This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.
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The electricity market restructuring, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in an rising complexity in power systems operation. Various power system simulators have been introduced in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex environment. This paper focuses on the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The restructuring of MASCEM (Multi-Agent System for Competitive Electricity Markets), and this system’s integration with MASGriP (Multi-Agent Smart Grid Platform), and ALBidS (Adaptive Learning Strategic Bidding System) provide the means for the exemplification of the usefulness of this ontology. A practical example is presented, showing how common simulation scenarios for different simulators, directed to very distinct environments, can be created departing from the proposed ontology.
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This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.
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As patients with chronic Chagas disease exhibit morphological and functional changes of the stomach (hypomotility and hypochlorhydria), malnutrition, immunological deficiency and high prevalence of peptic disease associated to Helicobater pylori infection, the purpose of this study was to evaluate if the prevalence of H. pylori infection in chronic chagasic is higher than in non-chagasic individuals in the urban and rural population from Uberlândia, MG, Brazil. Serological determination of IgG antibodies to H. pylori was performed using a second-generation ELISA. Thus, 598 people were evaluated: 128 chagasic (CG), 222 non-chagasic living in urban area (U-NCG) and 248 non-chagasic living in rural area (R-NCG). Regarding the age range from 21 to 50 years, the prevalence of H. pylori infection in the CG (85.1%) was significantly higher than in the U-NCG (56.3%, p < 0.01) and the R-NCG (67.4%, p < 0.05). In the patients over 50 years, the prevalence in the CG (86.4%) was similar to the U-NCG (78.8%) and R-NCG (86.1%). Similar results were also found between the U-NCG and R-NCG for all age ranges, with prevalence rates of 29.1% and 35.3% for the age range from 5 to 13 years, and 47.2% and 40% for that from 14 to 20 years, respectively. We conclude that chagasic patients showed a higher seroprevalence of H. pylori infection than non-chagasic individuals, in the age range from 21 to 50 years, and that the prevalence of this infection was similar in the studied urban and rural non-chagasic population.