29 resultados para energy harvesting,bimorph cantilever,resonance frequency,electrical tuning,MPPT algorithm

em Instituto Politécnico do Porto, Portugal


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In this study, energy production for autonomous underwater vehicles is investigated. This project is part of a bigger project called TURTLE. The autonomous vehicles perform oceanic researches at seabed for which they are intended to be kept operational underwater for several months. In order to ful l a long-term underwater condition, powerful batteries are combined with \micro- scale" energy production on the spot. This work tends to develop a system that generates power up to a maximum of 30 W. Latter energy harvesting structure consists basically of a turbine combined with a generator and low-power electronics to adjust the achieved voltage to a required battery charger voltage. Every component is examined separately hence an optimum can be de ned for all, and subsequently also an overall optimum. Di erent design parameters as e.g. number of blades, solidity ratio and cross-section area are compared for di erent turbines, in order to see what is the most feasible type. Further, a generator is chosen by studying how ux distributions might be adjusted to low velocities, and how cogging torque can be excluded by adapted designs. Low-power electronics are con gured in order to convert and stabilize heavily varying three-phase voltages to a constant, recti ed voltage which is usable for battery storage. Clearly, di erent component parameters as maximum power and torque are matched here to increase the overall power generation. Furthermore an overall maximum power is set up for achieving a maximum power ow at load side. Due to among others typical low velocities of about 0.1 to 0.5 m/s, and constructing limits of the prototype, the vast range of components is restricted to only a few that could be used. Hence, a helical turbine is combined in a direct drive mode to a coreless-stator axial- ux permanent-magnet generator, from which the output voltage is adjusted subsequently by a recti er, impedance matching unit, upconverter circuit and an overall control unit to regulate di erent component parameters. All these electronics are combined in a closed-loop design to involve positive feedback signals. Furthermore a theoretical con guration for the TURTLE vehicle is described in this work and a solution is proposed that might be implemented, for which several design tests are performable in a future study.

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For the past years wireless sensor networks (WSNs) have been coined as one of the most promising technologies for supporting a wide range of applications. However, outside the research community, few are the people who know what they are and what they can offer. Even fewer are the ones that have seen these networks used in real world applications. The main obstacle for the proliferation of these networks is energy, or the lack of it. Even though renewable energy sources are always present in the networks environment, designing devices that can efficiently scavenge that energy in order to sustain the operation of these networks is still an open challenge. Energy scavenging, along with energy efficiency and energy conservation, are the current available means to sustain the operation of these networks, and can all be framed within the broader concept of “Energetic Sustainability”. A comprehensive study of the several issues related to the energetic sustainability of WSNs is presented in this thesis, with a special focus in today’s applicable energy harvesting techniques and devices, and in the energy consumption of commercially available WSN hardware platforms. This work allows the understanding of the different energy concepts involving WSNs and the evaluation of the presented energy harvesting techniques for sustaining wireless sensor nodes. This survey is supported by a novel experimental analysis of the energy consumption of the most widespread commercially available WSN hardware platforms.

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Este trabalho foi realizado no âmbito da disciplina de Dissertação/Estágio do ramo de Optimização Energética na Indústria Química, do Mestrado em Engenharia Química do Instituto Superior de Engenharia do Porto e foi desenvolvido na empresa GreenWatt. O principal objectivo é efectuar uma auditoria energética e uma auditoria QAI a uma clínica de fisiatria de forma a preparar as ferramentas necessárias para a Certificação Energética e da QAI no enquadramento do Sistema de Certificação Energética. Na auditoria QAI foram analisados parâmetros físicos - temperatura, humidade relativa e partículas respiráveis PM10, parâmetros químicos - CO2, CO, O3, COVs, HCOH e o radão, e ainda parâmetros microbiológicos - bactérias, fungos e legionella. Na auditoria energética foi feita a caracterização dos vectores de energia utilizados no edifício, nomeadamente, gás natural e electricidade. Para esta caracterização efectuou-se um levantamento de toda a informação disponível relativa aos combustíveis utilizados, iluminação instalada, outros equipamentos consumidores de energia e perfis de utilização. Com recurso a analisadores de energia foram ainda medidos os consumos eléctricos do edifício. Com suporte nos dados provenientes da auditoria energética e das facturas anuais efectuou-se a validação da simulação dinâmica do edifício. Esta simulação é a base do cálculo do IEEnominal do edifício. Os resultados da auditoria QAI, permitiram verificar que existem valores nãoregulamentares em relação aos compostos orgânicos voláteis, fungos e bactérias. Da auditoria energética concluiu-se que o principal consumo de energia é o gás natural utilizado pelas caldeiras existentes. Este valor representa cerca de 81% do consumo total de energia, reproduzindo os mesmos resultados obtidos pela desagregação das facturas energéticas. No que respeita à electricidade concluiu-se que as bombas de água e os equipamentos eléctricos são os maiores consumidores deste vector, com, respectivamente, 53% e 23% do consumo total de energia eléctrica. Após a realização da simulação dinâmica, com base nos levantamentos realizados no edifício e na auditoria energética efectuada, obteve-se uma fotografia do edifício no que respeita ao seu desempenho energético, e calculou-se um IEEnominal de 40,54 kgep/m2.ano o que qualifica o edifício com uma Classe Energética E. O valor de CO2 emitido por este edifício em termos nominais, anualmente, é de 76,39 toneladas.

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A tese de mestrado teve como objetivo o estudo e análise do funcionamento das centrais de cogeração e térmica da fábrica da Unicer em Leça do Balio, com o intuito de melhorar a sua eficiência, propondo alterações processuais. O trabalho realizado consistiu no reconhecimento das instalações, seguido da formulação e resolução dos balanços de energia globais. Com o acompanhamento diário do funcionamento foi possível propor melhorias sem custos que se revelaram muito benéficas, registando-se um aumento nas recuperações térmicas e por consequência no Rendimento Elétrico Equivalente (R.E.E.), na eficiência da instalação da cogeração e da central térmica. Na cogeração registou-se um aumento de 36,2% na potência recuperada em água quente, aproximadamente 600 kW, sendo já superior à prevista pelo projeto. Na caldeira recuperativa registou-se um ligeiro aumento de 4,0% na potência recuperada. Deste modo o rendimento térmico da central aumentou 6,4%, atingindo os 40,8% e superando os 40,4% projetados. O rendimento global final foi de 83,1% o que representa um aumento de 6,3%. O R.E.E. em Maio de 2014 foi de 76,3%, superior ao valor em Junho de 2013 em 8,7%. Tendo como referência o valor alvo de 70,5% para o R.E.E. apontado no início do estágio, nos últimos 8 meses o seu valor tem sido sempre superior e em crescimento. Existe ainda a possibilidade de aproveitar a energia térmica de baixa temperatura que está a ser dissipada numa torre de arrefecimento, no mínimo 40 kW, num investimento com um período de retorno de investimento máximo de 8,1 meses. Na central térmica registou-se um aumento do rendimento para a mesma quantidade de energia produzida na central, pois esta é a principal variável do processo. Em 2014 a produção de energia apresentou um valor inferior a 2013, 6,9%, e a eficiência registou um acréscimo de 2,0%. A incorporação de biogás na alimentação de combustível à caldeira bifuel não pareceu comprometer significativamente a eficiência da central térmica, pelo que a sua utilização é benéfica. Com o aumento das recuperações térmicas na central de cogeração foram estimadas poupanças de gás natural equivalentes a 3,3 GWh, o que significa 120.680€ economizados nos últimos 11 meses do trabalho. É esperado uma poupança de 18.000€ mensais com a melhoria do funcionamento obtida nas duas centrais.

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A theory of free vibrations of discrete fractional order (FO) systems with a finite number of degrees of freedom (dof) is developed. A FO system with a finite number of dof is defined by means of three matrices: mass inertia, system rigidity and FO elements. By adopting a matrix formulation, a mathematical description of FO discrete system free vibrations is determined in the form of coupled fractional order differential equations (FODE). The corresponding solutions in analytical form, for the special case of the matrix of FO properties elements, are determined and expressed as a polynomial series along time. For the eigen characteristic numbers, the system eigen main coordinates and the independent eigen FO modes are determined. A generalized function of visoelastic creep FO dissipation of energy and generalized forces of system with no ideal visoelastic creep FO dissipation of energy for generalized coordinates are formulated. Extended Lagrange FODE of second kind, for FO system dynamics, are also introduced. Two examples of FO chain systems are analyzed and the corresponding eigen characteristic numbers determined. It is shown that the oscillatory phenomena of a FO mechanical chain have analogies to electrical FO circuits. A FO electrical resistor is introduced and its constitutive voltage–current is formulated. Also a function of thermal energy FO dissipation of a FO electrical relation is discussed.

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A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms to inter alia enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a huge overhead of device transition. The technology enhancement has allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring the system schedulability. Our results show an energy gain of up to 90% in the best case when compared to the state-of-the-art.

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A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms, inter alia to enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a very large overhead of device transitions. Technology enhancements have allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring system schedulability. Our results show an energy gain of up to 90% when compared to the techniques proposed in the state-of-the-art.

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Neste trabalho faz-se uma pesquisa e análise dos conceitos associados à navegação inercial para estimar a distância percorrida por uma pessoa. Foi desenvolvida uma plataforma de hardware para implementar os algoritmos de navegação inercial e estudar a marcha humana. Os testes efetuados permitiram adaptar os algoritmos de navegação inercial para humanos e testar várias técnicas para reduzir o erro na estimativa da distância percorrida. O sistema desenvolvido é um sistema modular que permite estudar o efeito da inserção de novos sensores. Desta forma foram adaptados os algoritmos de navegação para permitir a utilização da informação dos sensores de força colocados na planta do pé do utilizador. A partir desta arquitetura foram efetuadas duas abordagens para o cálculo da distância percorrida por uma pessoa. A primeira abordagem estima a distância percorrida considerando o número de passos. A segunda abordagem faz uma estimação da distância percorrida com base nos algoritmos de navegação inercial. Foram realizados um conjunto de testes para comparar os erros na estimativa da distância percorrida pelas abordagens efetuadas. A primeira abordagem obteve um erro médio de 4,103% em várias cadências de passo. Este erro foi obtido após sintonia para o utilizador em questão. A segunda abordagem obteve um erro de 9,423%. De forma a reduzir o erro recorreu-se ao filtro de Kalman o que levou a uma redução do erro para 9,192%. Por fim, recorreu-se aos sensores de força que permitiram uma redução para 8,172%. A segunda abordagem apesar de ter um erro maior não depende do utilizador pois não necessita de sintonia dos parâmetros para estimar a distância para cada pessoa. Os testes efetuados permitiram, através dos sensores de força, testar a importância da força sentida pela planta do pé para aferir a fase do ciclo de marcha. Esta capacidade permite reduzir os erros na estimativa da distância percorrida e obter uma maior robustez neste tipo de sistemas.

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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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Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

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The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

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Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

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Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

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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.

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Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.