Intelligent energy resources management in the context of smart grids

Smart grids are envisaged as infrastructures able to accommodate all centralized and distributed energy resources (DER), including intensive use of renewable and distributed generation (DG), storage, demand response (DR), and also electric vehicles (EV), from which plug-in vehicles, i.e. gridable vehicles, are especially relevant. Moreover, smart grids must accommodate a large number of diverse types or players in the context of a competitive business environment. Smart grids should also provide the required means to efficiently manage all these resources what is especially important in order to make the better possible use of renewable based power generation, namely to minimize wind curtailment. An integrated approach, considering all the available energy resources, including demand response and storage, is crucial to attain these goals. This paper proposes a methodology for energy resource management that considers several Virtual Power Players (VPPs) managing a network with high penetration of distributed generation, demand response, storage units and network reconfiguration. The resources are controlled through a flexible SCADA (Supervisory Control And Data Acquisition) system that can be accessed by the evolved entities (VPPs) under contracted use conditions. A case study evidences the advantages of the proposed methodology to support a Virtual Power Player (VPP) managing the energy resources that it can access in an incident situation.

Cyber-physical intelligence in the context of power systems

Cyber-Physical Intelligence is a new concept integrating Cyber-Physical Systems and Intelligent Systems. The paradigm is centered in incorporating intelligent behavior in cyber-physical systems, until now too oriented to the operational technological aspects. In this paper we will describe the use of Cyber-Physical Intelligence in the context of Power Systems, namely in the use of Intelligent SCADA (Supervisory Control and Data Acquisition) systems at different levels of the Power System, from the Power Generation, Transmission, and Distribution Control Centers till the customers houses.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

Demsi - a demand response simulator in the context of intensive use of distributed generation

Demand response can play a very relevant role in future power systems in which distributed generation can help to assure service continuity in some fault situations. This paper deals with the demand response concept and discusses its use in the context of competitive electricity markets and intensive use of distributed generation. The paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes using a realistic network simulation based on PSCAD. Demand response opportunities are used in an optimized way considering flexible contracts between consumers and suppliers. A case study evidences the advantages of using flexible contracts and optimizing the available generation when there is a lack of supply.

Recommendation and planning through mobile devices in tourism context

In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.

Safety high accuracy Context-Aware Matrix (CAM) making based on X.509 proxy certificate

Human Computer Interaction (HCl) is to interaction between computers and each person. And context-aware (CA) is very important one of HCI composition. In particular, if there are sequential or continuous tasks between users and devices, among users, and among devices etc, it is important to decide the next action using right CA. And to take perfect decision we have to get together all CA into a structure. We define that structure is Context-Aware Matrix (CAM) in this article. However to make exact decision is too hard for some problems like low accuracy, overhead and bad context by attacker etc. Many researcher has been studying to solve these problems. Moreover, still it has weak point HCI using in safety. In this Article, we propose CAM making include best selecting Server in each area. As a result, moving users could be taken the best way.

Context-aware emotion-based model for group decision making

Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

An emotional and context-aware model for adapting RSS news to users and groups

The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.

Group decision making and Quality-of-information in e-Health systems

Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One’s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSSs), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision-making process. In this way, it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services.

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.

Plataforma de gestão de incidentes

Mestrado em Engenharia Electrotécnica e de Computadores. Área de Especialização de Telecomunicações.

Construction of womanhood in the bengali language of Bangladesh

The subject-matter of this essay is gender justice in language which, as I argue, may be achieved through the development of a gender-related approach to linguistic human rights. The last decades of the 20th century, globally marked by a “gender shift” in attitudes to language policy, gave impetus to the social movement for promoting linguistic gender equality. It was initiated in Western Europe and nowadays is moving eastwards, as ideas of gender democracy progress into developing countries. But, while in western societies gender discrimination through language, or linguistic sexism, was an issue of concern for over three decades, in developing countries efforts to promote gender justice in language are only in their infancy. My argument is that to promote gender justice in language internationally it is necessary to acknowledge the rights of women and men to equal representation of their gender in language and speech and, therefore, raise a question of linguistic rights of the sexes. My understanding is that the adoption of the Universal Declaration of Linguistic Rights in 1996 provided this opportunity to address the problem of gender justice in language as a human rights issue, specifically as a gender dimension of linguistic human rights.

Integração de informação entre Sistemas Geracionais distintos: uma experiência e sistematização na ITV

A natural evolução dos sistemas de informação nas organizações envolve por um lado a instalação de equipamentos actualizados, e por outro a adopção de novas aplicações de suporte ao negócio, acompanhando o desenvolvimento dos mercados, as mudanças no modelo de negócio e a maturação da organização num novo contexto. Muitas vezes esta evolução implica a preservação dos dados existentes e de funcionalidades não cobertas pelas novas aplicações. Este facto leva ao desenvolvimento e execução de processos de migração de dados, de aplicações, e de integração de sistemas legados. Estes processos estão condicionados ao meio tecnológico disponível e ao conhecimento existente sobre os sistemas legados, sendo sensíveis ao contexto em que se desenrolam. Esta dissertação apresenta um estado da arte das abordagens à migração e integração, descreve as diversas alternativas, e ilustra de uma forma sistematizada e comparativa os exercícios realizados usando diferentes abordagens, num ambiente real de migração e integração em mudança.

Exploração do UML para a derivação automática de requisitos arquitecturais. Uma abordagem orientada a modelos

O desenvolvimento de software orientado a modelos defende a utilização dos modelos como um artefacto que participa activamente no processo de desenvolvimento. O modelo ocupa uma posição que se encontra ao mesmo nível do código. Esta é uma abordagem importante que tem sido alvo de atenção crescente nos últimos tempos. O Object Management Group (OMG) é o responsável por uma das principais especificações utilizadas na definição da arquitectura dos sistemas cujo desenvolvimento é orientado a modelos: o Model Driven Architecture (MDA). Os projectos que têm surgido no âmbito da modelação e das linguagens específicas de domínio para a plataforma Eclipse são um bom exemplo da atenção dada a estas áreas. São projectos totalmente abertos à comunidade, que procuram respeitar os standards e que constituem uma excelente oportunidade para testar e por em prática novas ideias e abordagens. Nesta dissertação foram usadas ferramentas criadas no âmbito do Amalgamation Project, desenvolvido para a plataforma Eclipse. Explorando o UML e usando a linguagem QVT, desenvolveu-se um processo automático para extrair elementos da arquitectura do sistema a partir da definição de requisitos. Os requisitos são representados por modelos UML que são transformados de forma a obter elementos para uma aproximação inicial à arquitectura do sistema. No final, obtêm-se um modelo UML que agrega os componentes, interfaces e tipos de dados extraídos a partir dos modelos dos requisitos. É uma abordagem orientada a modelos que mostrou ser exequível, capaz de oferecer resultados práticos e promissora no que concerne a trabalho futuro.