Adaptable control for electrical generation at irregural wind speeds

The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

Construção de websites com ferramentas open-source: duas experiências de implementação em bibliotecas de ensino superior

As Tecnologias da Informação e da Comunicação (TIC) têm influenciado de forma inequívoca o desenvolvimento das bibliotecas à escala global. Nas últimas décadas, as TIC mudaram a dinâmica das bibliotecas permitindo a sua modernização (pelo desenvolvimento da eficiência das tarefas já realizadas), favorecendo a inovação (pela utilização das tecnologias como base para o desenvolvimento de novos serviços/técnicas) e promovendo a sua transformação (ao nível do paradigma funcional, da disponibilização de conteúdos, etc.) – criando, em suma, uma nova relação com os seus públicos

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Multilevel negotiation in smart grids for VPP management of distributed resources

A multilevel negotiation mechanism for operating smart grids and negotiating in electricity markets considers the advantages of virtual power player management.

Extended-spectrum β-lactamases from the North of Portugal in the boundaries to Spain: emergence of high resistance to 4th generation cephalosporins

During the past 15 years, emergence and dissemination of third-generation cephalosporins resistance in nosocomial Enterobacteriaceae became a serious problem worldwide, due to the production of extended-spectrum-β-lactamases (ESBLs). The aim of this study was to investigate among the presence of ESBL-producing enterobacteria among Portuguese clinical isolates nearby Spain, to investigate the antimicrobial susceptibility patterns and to compare the two countries. The β-lactamases genes, blaTEM, blaSHV and blaCTX-M were detected by molecular methods. Among the ESBL-producing isolates it was found extraordinary levels (98.9%) of resistance to the fourth-generation cephalosporin Cefepime. These findings point to the need of reevaluate the definition of ESBL.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Dual source/dual energy-renal applications

Development of Dual Source Computed Tomography (Definition, Siemens Medical Solutions, Erlanger, Germany) allowed advances in temporal resolution, with the addition of a second X-ray source and an array of detectors to the TCM 64 slices. The ability to run exams on Dual Energy, allows greater differentiation of tissues, showing differences between closer attenuation coefficients. In terms of renal applications, the distinction of kidney stones and masses become one of the main advantages of the use of dual-energy technology. This article pretends to demonstrate operating principles of this equipment, as its main renal applications.

Geoquímica de radionuclídeos naturais e biomonitoramento em área de mineração de carvão no sul do Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

VirtualECare: group decision supported by idea generation and argumentation

In the last years there has been a considerable increase in the number of people in need of intensive care, especially among the elderly, a phenomenon that is related to population ageing (Brown 2003). However, this is not exclusive of the elderly, as diseases as obesity, diabetes, and blood pressure have been increasing among young adults (Ford and Capewell 2007). As a new fact, it has to be dealt with by the healthcare sector, and particularly by the public one. Thus, the importance of finding new and cost effective ways for healthcare delivery are of particular importance, especially when the patients are not to be detached from their environments (WHO 2004). Following this line of thinking, a VirtualECare Multiagent System is presented in section 2, being our efforts centered on its Group Decision modules (Costa, Neves et al. 2007) (Camarinha-Matos and Afsarmanesh 2001).On the other hand, there has been a growing interest in combining the technological advances in the information society - computing, telecommunications and knowledge – in order to create new methodologies for problem solving, namely those that convey on Group Decision Support Systems (GDSS), based on agent perception. Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities, in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life cycle. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the GDSS referred to above to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This attainment is vital, regarding the incoming to the market of new drugs and medical practices, which compete in the use of limited resources.

AI in power systems and energy markets

In a world increasingly conscientious about environmental effects, power and energy systems are undergoing huge transformations. Electric energy produced from power plants is transmitted and distributed to end users through a power grid. The power industry performs the engineering design, installation, operation, and maintenance tasks to provide a high-quality, secure energy supply while accounting for its systems’ abilities to withstand uncertain events, such as weather-related outages. Competitive, deregulated electricity markets and new renewable energy sources, however, have further complicated this already complex infrastructure.Sustainable development has also been a challenge for power systems. Recently, there has been a signifi cant increase in the installation of distributed generations, mainly based on renewable resources such as wind and solar. Integrating these new generation systems leads to more complexity. Indeed, the number of generation sources greatly increases as the grid embraces numerous smaller and distributed resources. In addition, the inherent uncertainties of wind and solar energy lead to technical challenges such as forecasting, scheduling, operation, control, and risk management. In this special issue introductory article, we analyze the key areas in this field that can benefi t most from AI and intelligent systems now and in the future.We also identify new opportunities for cross-fertilization between power systems and energy markets and intelligent systems researchers.

Avaliação da rentabilidade económica dos sistemas de microgeração fotovoltaica em Portugal (1990-2010)

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica - ramo de Energia

Air pollution effects on myocardial infarction

OBJECTIVE: Myocardial infarction is an acute and severe cardiovascular disease that generally leads to patient admissions to intensive care units and few cases are initially admitted to infirmaries. The objective of the study was to assess whether estimates of air pollution effects on myocardial infarction morbidity are modified by the source of health information. METHODS: The study was carried out in hospitals of the Brazilian Health System in the city of São Paulo, Southern Brazil. A time series study (1998-1999) was performed using two outcomes: infarction admissions to infirmaries and to intensive care units, both for people older than 64 years of age. Generalized linear models controlling for seasonality (long and short-term trends) and weather were used. The eight-day cumulative effects of air pollutants were assessed using third degree polynomial distributed lag models. RESULTS: Almost 70% of daily hospital admissions due to myocardial infarction were to infirmaries. Despite that, the effects of air pollutants on infarction were higher for intensive care units admissions. All pollutants were positively associated with the study outcomes but SO2 presented the strongest statistically significant association. An interquartile range increase on SO2 concentration was associated with increases of 13% (95% CI: 6-19) and 8% (95% CI: 2-13) of intensive care units and infirmary infarction admissions, respectively. CONCLUSIONS: It may be assumed there is a misclassification of myocardial infarction admissions to infirmaries leading to overestimation. Also, despite the absolute number of events, admissions to intensive care units data provides a more adequate estimate of the magnitude of air pollution effects on infarction admissions.

Tsunamigenic earthquakes in the Gulf of Cadiz: fault model and recurrence

The Gulf of Cadiz, as part of the Azores-Gibraltar plate boundary, is recognized as a potential source of big earthquakes and tsunamis that may affect the bordering countries, as occurred on 1 November 1755. Preparing for the future, Portugal is establishing a national tsunami warning system in which the threat caused by any large-magnitude earthquake in the area is estimated from a comprehensive database of scenarios. In this paper we summarize the knowledge about the active tectonics in the Gulf of Cadiz and integrate the available seismological information in order to propose the generation model of destructive tsunamis to be applied in tsunami warnings. The fault model derived is then used to estimate the recurrence of large earthquakes using the fault slip rates obtained by Cunha et al. (2012) from thin-sheet neotectonic modelling. Finally we evaluate the consistency of seismicity rates derived from historical and instrumental catalogues with the convergence rates between Eurasia and Nubia given by plate kinematic models.

Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.