115 resultados para Retailer awareness


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Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Auditoria Orientada por Mestre Carlos Manuel Antunes Mendes

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Relatório de Estágio apresentado ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Assessoria de Administração Orientadora: Doutora Isabel Ardions

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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.

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This paper describes an architecture conceived to integrate Power Sys-tems tools in a Power System Control Centre, based on an Ambient Intelligent (AmI) paradigm. This architecture is an instantiation of the generic architecture proposed in [1] for developing systems that interact with AmI environments. This architecture has been proposed as a consequence of a methodology for the inclu-sion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Sys-tems Research for Ambient Intelligence). The architecture presented in the paper will be able to integrate two applications in the control room of a power system transmission network. The first is SPARSE expert system, used to get diagnosis of incidents and to support power restoration. The second application is an Intelligent Tutoring System (ITS) incorporating two training tools. The first tutoring tool is used to train operators to get the diagnosis of incidents. The second one is another tutoring tool used to train operators to perform restoration procedures.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

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Currently, Power Systems (PS) already accommodate a substantial penetration of DG and operate in competitive environments. In the future PS will have to deal with largescale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. This cannot be done with the traditional PS operation. SCADA (Supervisory Control and Data Acquisition) is a vital infrastructure for PS. Current SCADA adaptation to accommodate the new needs of future PS does not allow to address all the requirements. In this paper we present a new conceptual design of an intelligent SCADA, with a more decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). Once a situation is characterized, data and control options available to each entity are re-defined according to this context, taking into account operation normative and a priori established contracts. The paper includes a case-study of using future SCADA features to use DER to deal with incident situations, preventing blackouts.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, taking into account context awareness and the unobtrusive integration in the working environment.

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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.

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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.

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This paper presents the proposal of an architecture for developing systems that interact with Ambient Intelligence (AmI) environments. This architecture has been proposed as a consequence of a methodology for the inclusion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Systems Research for Ambient Intelligence). The ISyRAmI architecture considers several modules. The first is related with the acquisition of data, information and even knowledge. This data/information knowledge deals with our AmI environment and can be acquired in different ways (from raw sensors, from the web, from experts). The second module is related with the storage, conversion, and handling of the data/information knowledge. It is understood that incorrectness, incompleteness, and uncertainty are present in the data/information/knowledge. The third module is related with the intelligent operation on the data/information/knowledge of our AmI environment. Here we include knowledge discovery systems, expert systems, planning, multi-agent systems, simulation, optimization, etc. The last module is related with the actuation in the AmI environment, by means of automation, robots, intelligent agents and users.

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Dissertação de Mestrado apresentada ao Instituto Supeior de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob a orientação da Doutora Sandrina Francisca Teixeira

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Dissertação de Mestrado apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação de Doutor António Correia de Barros

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Mestrado em Engenharia Informática

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A CIF é um sistema de classificação adotado pela OMS, que serve de referência universal para descrever, avaliar e medir saúde e incapacidade, a nível individual e ao nível da população. Contudo, apesar do interesse internacional gerado em torno da CIF, esta é considerada uma classificação complexa e extensa, fato que despoletou a criação de core sets – listas de itens da CIF especificamente selecionados pela sua relevância na descrição e qualificação de uma determinada condição de saúde – como resposta a esta problemática. Até à data, foram desenvolvidos core sets para várias patologias comuns. Contudo, apesar do controlo motor ser uma área de investigação muito reconhecida nos últimos 20 anos, ainda não possui um core set próprio. Assim, o objetivo deste estudo é contribuir para o desenvolvimento de um core set, com base na CIF-CJ, dirigido para uma descrição abrangente das competências inerentes a crianças, dos 6 aos 18 anos de idade, com défices no controlo motor. Deste modo, recorreu-se a uma revisão da literatura sobre a temática em estudo, de modo a reunir informação para a construção de uma proposta a core set, posteriormente sujeita ao escrutínio de peritos, através do recurso ao método de Delphi. Após várias rondas, foi alcançado um consenso acerca da lista final de códigos CIF que constituem o core set final.

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Consumer awareness, pesticide and fertilizer contaminations and environmental concerns have resulted in significant demand for organically grown farm produce. Consumption of berries has become popular among health-conscious consumers due to the high levels of valuable antioxidants, such as anthocyanins and other phenolic compounds. The present study evaluated the influence that organic farming (OF) and integrated pest management (IPM) practise exert on the total phenolic content in 22 strawberry samples from four varieties. Postharvest performance of OF and IPM strawberries grown in the same area in the centre of Portugal and harvested at the same maturity stage were compared. Chemical profiles (phenolic compounds) were determined with the aid of HPLC-DAD/MS. Total phenolic content was higher for OF strawberry extracts. This study showed that the main differences in bioactive phytochemicals between organically and IPM grown strawberries concerned their anthocyanin levels. Organically grown strawberries were significantly higher in antioxidant activity than were the IPM strawberries, as measured by DPPH and FRAP assays.