Virtual power players dealing with excessive wind power situations using real time pricing

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.

Modelling real solar cell using PSCAD/MATLAB

This paper presents the development of a solar photovoltaic (PV) model based on PSCAD/EMTDC - Power System Computer Aided Design – including a mathematical model study. An additional algorithm has been implemented in MATLAB software in order to calculate several parameters required by the PSCAD developed model. All the simulation study has been performed in PSCAD/MATLAB software simulation tool. A real data base concerning irradiance, cell temperature and PV power generation was used in order to support the evaluation of the implemented PV model.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Introduction to the special issue on real world applications of intelligent tutoring systems

The idea behind creating this special issue on real world applications of intelligent tutoring systems was to bring together in a single publication some of the most important examples of success in the use of ITS technology. This will serve as a reference to all researchers working in the area. It will also be an important resource for the industry, showing the maturity of ITS technology and creating an atmosphere for funding new ITS projects. Simultaneously, it will be valuable to academic groups, motivating students for new ideas of ITS and promoting new academic research work in the area.

Remoção hierárquica de geometria por oclusão em simulações em tempo real

Mestrado em Engenharia Electrotécnica e de Computadores

Real-time rheology of actively growing bacteria

The population growth of a Staphylococcus aureus culture, an active colloidal system of spherical cells, was followed by rheological measurements, under steady-state and oscillatory shear flows. We observed a rich viscoelastic behavior as a consequence of the bacteria activity, namely, of their multiplication and density-dependent aggregation properties. In the early stages of growth (lag and exponential phases), the viscosity increases by about a factor of 20, presenting several drops and full recoveries. This allows us to evoke the existence of a percolation phenomenon. Remarkably, as the bacteria reach their late phase of development, in which the population stabilizes, the viscosity returns close to its initial value. Most probably, this is caused by a change in the bacteria physiological activity and in particular, by the decrease of their adhesion properties. The viscous and elastic moduli exhibit power-law behaviors compatible with the "soft glassy materials" model, whose exponents are dependent on the bacteria growth stage. DOI: 10.1103/PhysRevE.87.030701.

Building the «true evolutionism»: Darwin's impact on Henri Bergson's thought

The paper focuses on the importance of Darwin’s work for the shaping of Henri Bergson’s philosophy, bearing on mind that the two authors first intercepted symbolically in 1859, when On the Origin of Species was published and Bergson was born. Bergson studied the biological sciences of his time, whose results were integrated in a metaphysical thought. He belonged to spiritualistic positivism, a philosophy that goes from the positive data of sciences and finds the ultimate explanation of reality in a spiritual principle. He was interested in the positive evolution of the natural world and in the works of naturalists such as Lamarck, De Vries or Eimer. Darwin was among these authors, being responsible for a vision of evolution that went from the scientific level to other domains. Bergson defends the “insufficiency of pure Darwinism” by pointing out the necessity to compensate scientific evolution with an internal metaphysical reading of the real, which he considered to be “true evolutionism”. This criticism is the most visible aspect of the relations between both works. However, an attentive look verifies that Darwin’s influence overcomes the divergence of positions concerning the extent of “evolution”. The French philosopher knew not only the 1859’s bestseller, but also studies by Darwin about ethology, entomology and botany, which contributed to the fact that the naturalist’s impact gained fundamental importance in Bergson’s philosophical perspective.

Optimization and validation of organochlorine compounds in adipose tissue by SPE-gas chromatography

Scientific evidence has shown an association between organochlorine compounds (OCC) exposure and human health hazards. Concerning this, OCC detection in human adipose samples has to be considered a public health priority. This study evaluated the efficacy of various solid-phase extraction (SPE) and cleanup methods for OCC determination in human adipose tissue. Octadecylsilyl endcapped (C18-E), benzenesulfonic acid modified silica cation exchanger (SA), poly (styrene-divinylbenzene (EN) and EN/RP18 SPE sorbents were evaluated. The relative sample cleanup provided by these SPE columns was evaluated using gas chromatography with electron capture detection (GC–ECD). The C18-E columns with strong homogenization were found to provide the most effective cleanup, removing the greatest amount of interfering substance, and simultaneously ensuring good analyte recoveries higher than 70%. Recoveries>70% with standard deviations (SD)<15% were obtained for all compounds under the selected conditions. Method detection limits were in the 0.003–0.009 mg/kg range. The positive samples were confirmed by gas chromatography coupled with tandem mass spectrometry (GC-MS/MS). The highest percentage found of the OCC in real samples corresponded to HCB, o,p′-DDT and methoxychlor, which were detected in 80 and 95% of samples analyzed respectively. Copyright © 2012 John Wiley & Sons, Ltd.

Estrutura da boa vida em pessoas com doença crónica

Doenças crónicas (DC) são doenças que têm de ser geridas em vez de curadas. Giovannini, Bitti, Sarchielli e Speltini (1986) caracterizam as doenças crónicas como: a) doenças de longa duração, b) que tendem a prolongar-se por toda a vida do doente, c) que provocam invalidez em graus variáveis, d) são devidas a causas não reversíveis, e) que exigem formas particulares de reeducação, f) que obrigam o doente a seguir determinadas prescrições terapêuticas, g) que normalmente exigem a aprendizagem de um novo estilo de vida, h) que necessitam de controlo periódico, de observação e de tratamento regulares. As DC não se definem pela sua aparente ou real gravidade. As pessoas que têm DC podem fazer a vida do dia-a-dia como qualquer outro cidadão, e grande parte deles acaba por falecer de velhice ou de outras doenças, que não a DC que os acompanhou grande parte da vida. Para estas pessoas viverem uma boa vida o processo de ajustamento é decisivo. O ajustamento à DC torna-se então um objectivo fundamental para as pessoas e para a sociedade. O ajustamento pode definir-se como uma resposta a uma alteração do meio ambiente, que leva um organismo a adaptar-se a essa alteração. Esta definição, explicam as autoras, implica que ele ocorre ao longo do tempo e, também, que é um resultado desejável. Para Stanton, Revenson, e Tennen, (2007), o ajustamento engloba inúmeros componentes que cruzam domínios interpessoais, cognitivos, emocionais, físicos e comportamentais. Estes autores referem que da revisão da literatura se pode concluir que, grosso modo a DC requer, ajustamento em múltiplos domínios, que o ajustamento se desenrola ao longo do tempo, e que existe uma heterogeneidade acentuada no modo como os indivíduos se ajustam à DC. O ajustamento é um conceito do senso comum que tanto é verbo como substantivo.

Machine Learning Algorithms at Myocardial Perfusion Imaging - a Preliminary Study

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.

Limite : uma noção (real) fundamental!

[...]. Para exemplificar o conceito de limite, vamos considerar um círculo com 15 centímetros de raio. Matematicamente, um círculo é o conjunto dos pontos do plano cuja distância ao centro é menor ou igual que um dado valor, ao qual chamamos raio. [...].

Harvesting dynamic aspects from a real rational map : the bulb of period 5

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

Inspeção e diagnóstico de edifícios recentes: estudo de um caso real

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Edificações