995 resultados para Electricity distribution
Resumo:
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.
Resumo:
Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Biomédica. A presente dissertação foi desenvolvida no Erasmus Medical Center em Roterdão, Holanda
Resumo:
Differences in cell charge between epimastigote and trypomastigote populations were compared in Y, Cl and Colombiana strains of T. cruzi. Trypomastigote populations were more homogenous in relation to cell charge than epimastigotes. This homogeneity of cell charge was not the result of the selection of trypomastigote sub-populations by the host immunosystem, but may be the result of a surface coat formed by host blood components.
Resumo:
Dissertação apresentada para obtenção do Grau de Mestre em Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
Resumo:
The prevalence of thermotolerant Campylobacters in mammals and birds from Southern Chile was determined. Campylobacters were isolated from 46.3% of the animals studied being C. jejuni biotipe 1 the most frequent (25.7%) followed by C. coli (17.4%) and C. jejuni biotipe 2 (3.2%).
Resumo:
Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia
Resumo:
Introduction: Standard Uptake Value (SUV) is a measurement of the uptake in a tumour normalized on the basis of a distribution volume and is used to quantify 18F-Fluorodeoxiglucose (FDG) uptake in tumors, such as primary lung tumor. Several sources of error can affect its accuracy. Normalization can be based on body weight, body surface area (BSA) and lean body mass (LBM). The aim of this study is to compare the influence of 3 normalization volumes in the calculation of SUV: body weight (SUVW), BSA (SUVBSA) and LBM (SUVLBM), with and without glucose correction, in patients with known primary lung tumor. The correlation between SUV and weight, height, blood glucose level, injected activity and time between injection and image acquisition is evaluated. Methods: Sample included 30 subjects (8 female and 22 male) with primary lung tumor, with clinical indication for 18F-FDG Positron Emission Tomography (PET). Images were acquired on a Siemens Biography according to the department’s protocol. Maximum pixel SUVW was obtained for abnormal uptake focus through semiautomatic VOI with Quantification 3D isocontour (threshold 2.5). The concentration of radioactivity (kBq/ml) was obtained from SUVW, SUVBSA, SUVLBM and the glucose corrected SUV were mathematically obtained. Results: Statistically significant differences between SUVW, SUVBSA and SUVLBM and between SUVWgluc, SUVBSAgluc and SUVLBMgluc were observed (p=0.000<0.05). The blood glucose level showed significant positive correlations with SUVW (r=0.371; p=0.043) and SUVLBM (r=0.389; p=0.034). SUVBSA showed independence of variations with the blood glucose level. Conclusion: The measurement of a radiopharmaceutical tumor uptake normalized on the basis of different distribution volumes is still variable. Further investigation on this subject is recommended.
Resumo:
The Mondunguara copper mines are situated in mountainous terrain in west-central Mozambique. The mineralization consists of chalcopyrite, pyrrhotite, common pcntlandite, cobaltpentlandite, pyrite and several minor oxides and sulphides in tabular ore bodies deeping steep to the north. Gold was known to occur in small quantities but no systematic sampling and analysis for precious clements was ever done. Mineralogical and geological evidence has shown that the ores are magmatic in origin and were derived from gabbro-peridotitic magma dykes saturated in sulphides when intruded. The ore bodies show a clear zonation. Platinum group elements as well as pure gold are associated with high temperature hexagonal pyrrhotite. This pyrrhotite being of no use is generally discarded to the tailing dumps. Late hydrothermal phases are enriched in native silver, silver tellurides as well as electrum.
Resumo:
The design of magnetic cores can be carried out by taking into account the optimization of different parameters in accordance with the application requirements. Considering the specifications of the fast field cycling nuclear magnetic resonance (FFC-NMR) technique, the magnetic flux density distribution, at the sample insertion volume, is one of the core parameters that needs to be evaluated. Recently, it has been shown that the FFC-NMR magnets can be built on the basis of solenoid coils with ferromagnetic cores. Since this type of apparatus requires magnets with high magnetic flux density uniformity, a new type of magnet using a ferromagnetic core, copper coils, and superconducting blocks was designed with improved magnetic flux density distribution. In this paper, the designing aspects of the magnet are described and discussed with emphasis on the improvement of the magnetic flux density homogeneity (Delta B/B-0) in the air gap. The magnetic flux density distribution is analyzed based on 3-D simulations and NMR experimental results.
Resumo:
Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.
Resumo:
Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.
Resumo:
Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.
Resumo:
This paper presents a coordination approach to maximize the total profit of wind power systems coordinated with concentrated solar power systems, having molten-salt thermal energy storage. Both systems are effectively handled by mixed-integer linear programming in the approach, allowing enhancement on the operational during non-insolation periods. Transmission grid constraints and technical operating constraints on both systems are modeled to enable a true management support for the integration of renewable energy sources in day-ahead electricity markets. A representative case study based on real systems is considered to demonstrate the effectiveness of the proposed approach. © IFIP International Federation for Information Processing 2015.
Resumo:
Abdominal angiostrongyliasis is a parasitic disease caused by Angiostrongylus costaricensis, a metastrongylid nematode with wide geographic distribution, occurring from the United States to Argentina. In Brazil, the disease has been reported from the States of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo, Federal District of Brasilia and Minas Gerais. We report here a case of abdominal angiostrongyliasis in a 9-year-old girl, from Itatiba, State of Espirito Santo, Brazil, submitted to exploratory laparotomy for acute abdomen. Extensive inflammatory lesions of terminal ileum and cecum, with perforations of the first, were present, and ileocecal resection was performed. The pathological picture was characterized by transmural inflammatory granulomatous reaction, extensive eosinophilic infiltration, eosinophilic vasculitis and the presence of worms within a mesenteric artery branch, with histological features of metastrongylid nematodes. This case report contributes to a better knowledge of the geographic distribution of this parasite in Brazil, suggesting that abdominal angiostrongyliasis may represent a disease of medical importance, more than a rarity of academic interest.