Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Optical Transducers Based on Amorphous Si/SiC Photodiodes

Amorphous Si/SiC photodiodes working as photo-sensing or wavelength sensitive devices have been widely studied. In this paper single and stacked a-SiC:H p-i-n devices, in different geometries and configurations, are reviewed. Several readout techniques, depending on the desired applications (image sensor, color sensor, wavelength division multiplexer/demultiplexer device) are proposed. Physical models are presented and supported by electrical and numerical simulations of the output characteristics of the sensors.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

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.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Modelação e concepção da carroçaria do veículo eléctrico ecológico (VEECO)

Neste trabalho aborda-se o desenvolvimento da carroçaria do Veículo Eléctrico Ecológico – VEECO recorrendo a tecnologias assistidas por computador. Devido à impossibilidade de abranger toda a temática das tecnologias assistidas por computador, associadas ao desenvolvimento de uma carroçaria automóvel, o foco deste trabalho assenta no processo de obtenção de um modelo digital válido e no estudo do desempenho aerodinâmico da carroçaria. A existência de um modelo digital válido é a base de qualquer processo de desenvolvimento associado a tecnologias assistidas por computador. Neste sentido, numa primeira etapa, foram aplicadas e desenvolvidas técnicas e metodologias que permitem o desenvolvimento de uma carroçaria desde a sua fase de “design” até à obtenção de um modelo digital CAD. Estas abrangem a conversão e importação de dados, a realização de engenharia inversa, a construção/reconstrução CAD em CATIA V5 e a preparação/correcção de modelos CAD para a análise numérica. Numa segunda etapa realizou-se o estudo da aerodinâmica exterior da carroçaria, recorrendo à ferramenta de análise computacional de fluidos (CFD) Flow Simulation da CosmosFloworks integrado no programa SolidWorks 2010. Associado à temática do estudo aerodinâmico e devido à elevada importância da validação dos resultados numéricos por meio de dados experimentais, foi realizado o estudo de análise dimensional que permite a realização de ensaios experimentais à escala, bem como a análise dos resultados experimentais obtidos.

Simulação numérica aplicada ao tratamento de efluentes

A existência de estações de tratamentos de águas residuais (ETAR) é, nos dias de hoje, fundamental na medida em que permite, reduzir a poluição ambiental associada às águas e, também, a reutilização da água tratada para diversos fins. A constante necessidade de cumprir os limites de descargas nos meios recetores conduziu a um melhoramento nas técnicas e processos de tratamento de efluentes, nomeadamente, nos processos biológicos. O processo por lamas ativadas é um processo amplamente utilizado para a remoção de poluentes orgânicos presentes nas águas residuais, pelo que um estudo mais intensivo sobre estes tratamentos resultou na publicação de uma série de conceitos e pressupostos, através de modelos numéricos. A modelação numérica de processos de tratamento de águas residuais e a utilização de ferramentas de simulação numérica têm sido largamente utilizadas, a nível mundial, por exemplo em investigação, desenvolvimento de processos, atividade de consultoria e igualmente por entidades reguladoras, na medida em que os auxiliam no planeamento, dimensionamento e análise do comportamento de infraestruturas de tratamento. No presente trabalho, recorreu-se ao software de simulação GPS-X (versão 6.0) para implementar o esquema de tratamento da ETAR de Beirolas. O objetivo deste trabalho é verificar a aplicabilidade de modelos numéricos na simulação de unidades de tratamento de efluentes e avaliar a resposta dos diferentes modelos, assim como a influência na alteração de características das águas afluentes no comportamento dos modelos. Os resultados obtidos permitiram concluir que os modelos numéricos podem ser utilizados para prever a resposta dos sistemas biológicos e as suas perturbações. Conclui-se ainda que o comportamento, dos modelos estudados (ASM1, ASM2d, ASM3 e mantis), é semelhante, contudo deve-se referir que devido à complexidade do modelo e a falta de informação experimental sobre as características do efluente, não permitiram efetuar uma completa caracterização e calibração do caso de estudo, e toda a informação disponível sobre as características físico-químicas da água foram baseadas em estimativas de concentrações de carências de oxigénio e sólidos suspensos.

Evaluation of IMRT and VMAT techniques with and without flattening filter using pareto optimal fronts

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

Dynamical analysis in growth models: Blumberg’s equation

We present a new dynamical approach to the Blumberg's equation, a family of unimodal maps. These maps are proportional to Beta(p, q) probability densities functions. Using the symmetry of the Beta(p, q) distribution and symbolic dynamics techniques, a new concept of mirror symmetry is defined for this family of maps. The kneading theory is used to analyze the effect of such symmetry in the presented models. The main result proves that two mirror symmetric unimodal maps have the same topological entropy. Different population dynamics regimes are identified, when the intrinsic growth rate is modified: extinctions, stabilities, bifurcations, chaos and Allee effect. To illustrate our results, we present a numerical analysis, where are demonstrated: monotonicity of the topological entropy with the variation of the intrinsic growth rate, existence of isentropic sets in the parameters space and mirror symmetry.

Numerical optimization experiments using the hyperbolic smoothing strategy to solve MPCC

In this work we solve Mathematical Programs with Complementarity Constraints using the hyperbolic smoothing strategy. Under this approach, the complementarity condition is relaxed through the use of the hyperbolic smoothing function, involving a positive parameter that can be decreased to zero. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.