63 resultados para Hydric resources policy
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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia
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Dissertação de Mestrado apresentada ao Instituto Politécnico do Porto para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Gestão das Organizações – Ramo de Gestão de Empresas Orientador: Professor Doutor Pedro Nunes Orientador: Professor Henrique Curado
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The teaching-learning process is increasingly focused on the combination of the paradigms “learning by viewing” and “learning by doing.” In this context, educational resources, either expository or evaluative, play a pivotal role. Both types of resources are interdependent and their sequencing would create a richer educational experience to the end user. However, there is a lack of tools that support sequencing essentially due to the fact that existing specifications are complex. The Seqins is a sequencing tool of digital resources that has a fairly simple sequencing model. The tool communicates through the IMS LTI specification with a plethora of e-learning systems such as learning management systems, repositories, authoring and evaluation systems. In order to validate Seqins we integrate it in an e-learning Ensemble framework instance for the computer programming learning.
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Existing adaptive educational hypermedia systems have been using learning resources sequencing approaches in order to enrich the learning experience. In this context, educational resources, either expository or evaluative, play a central role. However, there is a lack of tools that support sequencing essentially due to the fact that existing specifications are complex. This paper presents Seqins as a sequencing tool of digital educational resources. Seqins includes a simple and flexible sequencing model that will foster heterogeneous students to learn at different rhythms. The tool communicates through the IMS Learning Tools Interoperability specification with a plethora of e-learning systems such as learning management systems, repositories, authoring and automatic evaluation systems. In order to validate Seqins we integrate it in an e-learning Ensemble framework instance for the computer programming learning domain.
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The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.
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This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.
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Purpose – Our paper aims at analyzing how different European countries cope with the European Energy Policy, which proposes a set of measures (free energy market, smart meters, energy certificates) to improve energy utilization and management in Europe. Design/methodology/approach – The paper first reports the general vision, regulations and goals set up by Europe to implement the European Energy Policy. Later on, it performs an analysis of how some European countries are coping with the goals, with financial, legal, economical and regulatory measures. Finally, the paper draws a comparison between the countries to present a view on how Europe is responding to the emerging energy emergency of the modern world. Findings – Our analysis on different use cases (countries) showed that European countries are converging to a common energy policy, even though some countries appear to be later than others In particular, Southern European countries were slowed down by the world financial and economical crisis. Still, it appears that contingency plans were put into action, and Europe as a whole is proceeding steadily towards the common vision. Research limitations/implications – European countries are applying yet more cuts to financing green technologies, and it is not possible to predict clearly how each country will evolve its support to the European energy policy. Practical implications – Different countries applied the concepts and measures in different ways. The implementation of the European energy policy has to cope with the resulting plethora of regulations, and a company proposing enhancement regarding energy management still has to possess robust knowledge of the single country, before being able to export experience and know-how between European countries. Originality/Value – Even though a few surveys on energy measures in Europe are already part of the state-of-the-art, organic analysis diagonal to the different topics of the European Energy Policy is missing. Moreover, this paper highlights how European countries are converging on a common view, and provides some details on the differences between the countries, thus facilitating parties interesting into cross-country export of experience and technology for energy management.
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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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This paper focuses on the Portuguese results from an international survey on LIS students’ information literacy skills. The results’ analysis will be grounded on a literature review on the criteria application to evaluate information and determine the credibility by undergraduate students. The guidelines for the information evaluation, especially regarding credibility aspect, on three main information literacy frameworks will be presented. After an overall presentation of the main results, the analysis of the Portuguese survey results will focus on issues related to information evaluation skills, namely on criteria to assess information credibility and on difficulties to apply them.
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Apresenta-se um projeto em curso entre a ESEIG/IPP (Portugal) e o IIBI/UNAM (México) para a criação de uma biblioteca digital na área da Biblioteconomia e dos Estudos de Informação. Considerando a missão educacional das instituições envolvidas, são analisados os conceitos conexos Ambientes Virtuais de Pesquisa e Aprendizagem nos quais a biblioteca digital fundamenta alguns dos seus princípios. É apresentado o modelo de biblioteca digital que sustenta o projeto e são caracterizadas as instituições participantes. Faz-se ainda uma reflexão sobre a conceção e o estabelecimento de uma política de informação, de modo a proporcionar um substrato para a criação e utilização dos recursos e serviços entre as comunidades envolvidas no projeto. Por fim, são apresentados os objetivos da biblioteca digital e diretrizes para a criação e partilha dos recursos digitais.
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The intensive use of distributed generation based on renewable resources increases the complexity of power systems management, particularly the short-term scheduling. Demand response, storage units and electric and plug-in hybrid vehicles also pose new challenges to the short-term scheduling. However, these distributed energy resources can contribute significantly to turn the shortterm scheduling more efficient and effective improving the power system reliability. This paper proposes a short-term scheduling methodology based on two distinct time horizons: hour-ahead scheduling, and real-time scheduling considering the point of view of one aggregator agent. In each scheduling process, it is necessary to update the generation and consumption operation, and the storage and electric vehicles status. Besides the new operation condition, more accurate forecast values of wind generation and consumption are available, for the resulting of short-term and very short-term methods. In this paper, the aggregator has the main goal of maximizing his profits while, fulfilling the established contracts with the aggregated and external players.
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The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.
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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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Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.
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In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required.