106 resultados para Integration-responsiveness Framework


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Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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The purpose of this paper is to present a framework that increases knowledge sharing and collaboration in Higher Education Institutions. The paper discusses the concept of knowledge management in higher education institutions, presenting a systematization of knowledge practices and tools to linking people (students, teachers, researchers, secretariat staff, external entities)and promoting the knowledge sharing across several key processes and services in a higher education institution, such as: the research processes, learning processes, student and alumni services, administrative services and processes, and strategic planning and management. The framework purposed in this paper aims to improve knowledge practices and processes which facilitate an environment and a culture of knowledge collaboration,sharing and discovery that should characterize an institution of higher education.

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Lean Thinking is an important pillar in the success of any program of continuous improvement process. Its tools are useful means in the analysis, control and organization of important data for correct decision making in organizations. This project had as main objective the design of a program of quality improvement in Eurico Ferreira, S.A., based on the evaluation of customer satisfaction and the implementation of 5S. Subsequently, we have selected which business area of the company to address. After the selection, there was an initial diagnostic procedure, identifying the various points of improvement to which some tools of Lean Thinking have been applied, in particular Value Stream Mapping and 5S methodology. With the first, we were able to map the current state of the process in which all stakeholders were represented as well as the flow of materials and information throughout the process. The 5S methodology allowed to act on the wastage, identifying and implementing various process improvements.

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This paper presents an ongoing project that implements a platform for creating personal learning environments controlled by students, integrating Web 2.0 applications and content management systems, enabling the safe use of content created in Web 2.0 applications, allowing its publication in the infrastructure controlled by the HEI. Using this platform, students can develop their personal learning environment (PLE) integrated with the Learning Management System (LMS) of the HEI, enabling the management of their learning and, simultaneously, creating their e-portfolio with digital content developed for Course Units (CU). All this can be maintained after the student completes his academic studies, since the platform will remain accessible to students even after they leave the HEI and lose access to its infrastructure. The platform will enable the safe use of content created in Web 2.0 applications, allowing its protected publication in the infrastructure controlled by HEI, thus contributing to the adaptation of the L&T paradigm to the Bologna process.

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Atualmente, verifica-se um aumento na necessidade de software feito à medida do cliente, que se consiga adaptar de forma rápida as constantes mudanças da sua área de negócio. Cada cliente tem os seus problemas concretos que precisa de resolver, não lhe sendo muitas vezes possível dispensar uma elevada quantidade de recursos para atingir os fins pretendidos. De forma a dar resposta a estes problemas surgiram várias arquiteturas e metodologias de desenvolvimento de software, que permitem o desenvolvimento ágil de aplicações altamente configuráveis, que podem ser personalizadas por qualquer utilizador das mesmas. Este dinamismo, trazido para as aplicações sobre a forma de modelos que são personalizados pelos utilizadores e interpretados por uma plataforma genérica, cria maiores desafios no momento de realizar testes, visto existir um número de variáveis consideravelmente maior que numa aplicação com uma arquitetura tradicional. É necessário, em todos os momentos, garantir a integridade de todos os modelos, bem como da plataforma responsável pela sua interpretação, sem ser necessário o desenvolvimento constante de aplicações para suportar os testes sobre os diferentes modelos. Esta tese debruça-se sobre uma aplicação, a plataforma myMIS, que permite a interpretação de modelos orientados à gestão, escritos numa linguagem específica de domínio, sendo realizada a avaliação do estado atual e definida uma proposta de práticas de testes a aplicar no desenvolvimento da mesma. A proposta resultante desta tese permitiu verificar que, apesar das dificuldades inerentes à arquitetura da aplicação, o desenvolvimento de testes de uma forma genérica é possível, podendo as mesmas lógicas ser utilizadas para o teste de diversos modelos distintos.

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Lunacloud is a cloud service provider with offices in Portugal, Spain, France and UK that focus on delivering reliable, elastic and low cost cloud Infrastructure as a Service (IaaS) solutions. The company currently relies on a proprietary IaaS platform - the Parallels Automation for Cloud Infrastructure (PACI) - and wishes to expand and integrate other IaaS solutions seamlessly, namely open source solutions. This is the challenge addressed in this thesis. This proposal, which was fostered by Eurocloud Portugal Association, contributes to the promotion of interoperability and standardisation in Cloud Computing. The goal is to investigate, propose and develop an interoperable open source solution with standard interfaces for the integrated management of IaaS Cloud Computing resources based on new as well as existing abstraction libraries or frameworks. The solution should provide bothWeb and application programming interfaces. The research conducted consisted of two surveys covering existing open source IaaS platforms and PACI (features and API) and open source IaaS abstraction solutions. The first study was focussed on the characteristics of most popular open source IaaS platforms, namely OpenNebula, OpenStack, CloudStack and Eucalyptus, as well as PACI and included a thorough inventory of the provided Application Programming Interfaces (API), i.e., offered operations, followed by a comparison of these platforms in order to establish their similarities and dissimilarities. The second study on existing open source interoperability solutions included the analysis of existing abstraction libraries and frameworks and their comparison. The approach proposed and adopted, which was supported on the conclusions of the carried surveys, reuses an existing open source abstraction solution – the Apache Deltacloud framework. Deltacloud relies on the development of software driver modules to interface with different IaaS platforms, officially provides and supports drivers to sixteen IaaS platform, including OpenNebula and OpenStack, and allows the development of new provider drivers. The latter functionality was used to develop a new Deltacloud driver for PACI. Furthermore, Deltacloud provides a Web dashboard and REpresentational State Transfer (REST) API interfaces. To evaluate the adopted solution, a test bed integrating OpenNebula, Open- Stack and PACI nodes was assembled and deployed. The tests conducted involved time elapsed and data payload measurements via the Deltacloud framework as well as via the pre-existing IaaS platform API. The Deltacloud framework behaved as expected, i.e., introduced additional delays, but no substantial overheads. Both the Web and the REST interfaces were tested and showed identical measurements. The developed interoperable solution for the seamless integration and provision of IaaS resources from PACI, OpenNebula and OpenStack IaaS platforms fulfils the specified requirements, i.e., provides Lunacloud with the ability to expand the range of adopted IaaS platforms and offers a Web dashboard and REST API for the integrated management. The contributions of this work include the surveys and comparisons made, the selection of the abstraction framework and, last, but not the least, the PACI driver developed.

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Os videojogos são cada vez mais uma das maiores áreas da indústria de entretenimento, tendo esta vindo a expandir-se de ano para ano. Para além disso, os videojogos estão cada vez mais presentes no nosso dia-adia, quer através dos dispositivos móveis ou das novas consolas. Com base nesta premissa, é seguro de afirmar que o investimento neste campo trará mais ganhos do que perdas. Esta Dissertação tem como objetivo o estudo do estado da indústria dos videojogos, tendo como principal foco a conceção de um videojogo, a partir duma Framework Modular, desenvolvida também no âmbito desta Dissertação. Para isso, é feito um estudo sobre o estado da arte tecnológico, onde várias ferramentas de criação de videojogos foram estudadas e analisadas, de forma a perceber as forças e fraquezas de cada uma, e um estudo sobre a arte do negócio, ficando assim com uma ideia mais concreta dos vários pontos necessários para a criação de um videojogo. De seguida são discutidos os diferentes géneros de videojogos existentes e é conceptualizado um pequeno videojogo, tendo ainda em conta os diferentes tipos de interfaces que são mais utilizados na indústria dos videojogos, de forma a entender qual será a forma mais viável, conforme o género, e as diferentes mecânicas presentes no videojogo a criar. A Framework Modular é desenvolvida tendo em conta toda a análise previamente realizada, e o videojogo conceptualizado. Esta tem como grande objetivo uma elevada personalização e manutenibilidade, sendo que todos os módulos implementados podem ser substituídos por outros sem criar conflitos entre si. Finalmente, de forma a unir todos os temas analisados ao longo desta Dissertação, é ainda desenvolvido um Protótipo de forma a comprovar o bom funcionamento da Framework, aplicando todas as decisões previamente feitas.

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We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.

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This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.

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The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

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The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

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The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

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The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

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The increasing and intensive integration of distributed energy resources into distribution systems requires adequate methodologies to ensure a secure operation according to the smart grid paradigm. In this context, SCADA (Supervisory Control and Data Acquisition) systems are an essential infrastructure. This paper presents a conceptual design of a communication and resources management scheme based on an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). The methodology is used to support the energy resource management considering all the involved costs, power flows, and electricity prices leading to the network reconfiguration. The methodology also addresses the definition of the information access permissions of each player to each resource. The paper includes a 33-bus network used in a case study that considers an intensive use of distributed energy resources in five distinct implemented operation contexts.