130 resultados para Drying energy saving


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Os biocombustíveis apresentam um interessante potencial de redução da dependência energética relativamente aos combustíveis fósseis. A produção de microalgas apresenta vários benefícios ambientais como sejam a utilização mais efetiva de terrenos, a captura de dióxido de carbono, a purificação de águas quando associada a um processo de tratamento de águas residuais e não provoca a disputa entre a produção de matéria-prima para alimentação e combustíveis. A cultura de microalgas para a produção de biodiesel tem recebido uma grande atenção nos últimos anos devido ao seu potencial. Neste trabalho pretende-se criar as etapas de processamento das microalgas em biodiesel onde são implementadas medidas de eficiência energética e aproveitamento de fontes poluidoras como o CO2. Para isso, formulou-se um modelo no programa Aspen Plus para simulação do processo desde a produção, colheita até à extração de óleo das microalgas e posterior avaliação económica do mesmo. Concluiu-se que para o projeto fosse pago no tempo de vida útil seria preciso vender o óleo a 13 $/kg. Aos preços atuais do óleo o projeto não é economicamente viável.

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With the growing interest in the issue of reducing powerconsumption in electricity applications, energy-saving devises and the problem of their operation gains more attention. The increase in the utilization of energy-saving lamps, especially LED lamps, leads to the wide interest in their influence on the power system. The impact of discussed devices on the voltage and current in the grid must be thoroughly studied before launching devices into the market. The studies undertaken on the LED lamps present in a wide range the issue of harmonic emission from lamps and their influence on power quality. Due to many anufacturing technologies, different LED devices can have various effects on the utility. It is significant to carry out researches concerning the adverse effects of energy-saving lamps in order to utilize devices that meet certain requirements which are set by the international commissions.

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This study addresses to the optimization of pultrusion manufacturing process from the energy-consumption point of view. The die heating system of external platen heaters commonly used in the pultrusion machines is one of the components that contribute the most to the high consumption of energy of pultrusion process. Hence, instead of the conventional multi-planar heaters, a new internal die heating system that leads to minor heat losses is proposed. The effect of the number and relative position of the embedded heaters along the die is also analysed towards the setting up of the optimum arrangement that minimizes both the energy rate and consumption. Simulation and optimization processes were greatly supported by Finite Element Analysis (FEA) and calibrated with basis on the temperature profile computed through thermography imaging techniques. The main outputs of this study allow to conclude that the use of embedded cylindrical resistances instead of external planar heaters leads to drastic reductions of both the power consumption and the warm-up periods of the die heating system. For the analysed die tool and process, savings on energy consumption up to 60% and warm-up period stages less than an half hour were attained with the new internal heating system. The improvements achieved allow reducing the power requirements on pultrusion process, and thus minimize industrial costs and contribute to a more sustainable pultrusion manufacturing industry.

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Este trabalho surgiu no âmbito da Tese de Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química, aliando a necessidade da Empresa Monteiro Ribas – Indústrias, S.A. em resolver alguns problemas relacionados com as estufas da unidade J da fábrica de revestimentos. Outro dos objectivos era propor melhorias de eficiência energética neste sector da empresa. Para tal, foi necessário fazer um levantamento energético de toda a unidade, o que permitiu verificar que as estufas de secagem (Recobrimento 1 e 2) seriam o principal objecto de estudo. O levantamento energético da empresa permitiu conhecer o seu consumo anual de energia de 697,9 tep, o que a classifica, segundo o Decreto-lei nº 71 de 15 de Abril de 2008, como Consumidora Intensiva de Energia (CIE). Além disso, as situações que devem ser alvo de melhoria são: a rede de termofluido, que apresenta válvulas sem isolamento, o sistema de iluminação, que não é o mais eficiente e a rede de distribuição de ar comprimido, que não tem a estrutura mais adequada. Desta forma sugere-se que a rede de distribuição de termofluido passe a ter válvulas isoladas com lã de rocha, o investimento total é de 2.481,56 €, mas a poupança pode ser de 21.145,14 €/ano, com o período de retorno de 0,12 anos. No sistema de iluminação propõe-se a substituição dos balastros normais por electrónicos, o investimento total é de 13.873,74 €, mas a poupança é de 2.620,26 €/ano, com período de retorno de 5 anos. No processo de secagem das linhas de recobrimento mediram-se temperaturas de todos os seus componentes, velocidades de ar o que permitiu conhecer a distribuição do calor fornecido pelo termofluido. No Recobrimento 1, o ar recebe entre 39 a 51% do calor total, a tela recebe cerca de 25% e na terceira estufa este é apenas de 6%. Nesta linha as perdas de calor por radiação oscilam entre 6 e 11% enquanto as perdas por convecção representam cerca de 17 a 44%. Como o calor que a tela recebe é muito inferior ao calor recebido pelo ar no Recobrimento 1, propõe-se uma redução do caudal de ar que entra na estufa, o que conduzirá certamente à poupança de energia térmica. No Recobrimento 2 o calor fornecido ao ar representa cerca de 51 a 77% do calor total e o cedido à tela oscila entre 2 e 3%. As perdas de calor por convecção oscilam entre 12 e 26%, enquanto que as perdas por radiação têm valores entre 4 e 8%. No que diz respeito ao calor necessário para evaporar os solventes este oscila entre os 4 e 13%. Os balanços de massa e energia realizados ao processo de secagem permitiram ainda determinar o rendimento das 3 estufas do Recobrimento 1, com 36, 47 e 24% paras as estufa 1, 2 e 3, respectivamente. No Recobrimento 2 os valores de rendimento foram superiores, tendo-se obtido valores próximos dos 41, 81 e 88%, para as estufas 1, 2 e 3, respectivamente. Face aos resultados obtidos propõem-se a reengenharia do processo introduzindo permutadores compactos para aquecer o ar antes de este entrar nas estufas. O estudo desta alteração foi apenas realizado para a estufa 1 do Recobrimento 1, tendo-se obtido uma área de transferência de calor de 6,80 m2, um investimento associado de 8.867,81 €. e uma poupança de 708,88 €/ano, com um período de retorno do investimento de 13 anos. Outra sugestão consiste na recirculação de parte do ar de saída (5%), que conduz à poupança de 158,02 €/ano. Estes valores, pouco significativos, não estimulam a adopção das referidas sugestões.

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This paper proposes a wind power forecasting methodology based on two methods: direct wind power forecasting and wind speed forecasting in the first phase followed by wind power forecasting using turbines characteristics and the aforementioned wind speed forecast. The proposed forecasting methodology aims to support the operation in the scope of the intraday resources scheduling model, namely with a time horizon of 5 minutes. This intraday model supports distribution network operators in the short-term scheduling problem, in the smart grid context. A case study using a real database of 12 months recorded from a Portuguese wind power farm was used. The results show that the straightforward methodology can be applied in the intraday model with high wind speed and wind power accuracy. The wind power forecast direct method shows better performance than wind power forecast using turbine characteristics and wind speed forecast obtained in first phase.

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The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

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The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

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The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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The end consumers in a smart grid context are seen as active players. The distributed generation resources applied in smart home system as a micro and small-scale systems can be wind generation, photovoltaic and combine heat and power facility. The paper addresses the management of domestic consumer resources, i.e. wind generation, solar photovoltaic, combined heat and power, electric vehicle with gridable capability and loads, in a SCADA system with intelligent methodology to support the user decision in real time. The main goal is to obtain the better management of excess wind generation that may arise in consumer’s distributed generation resources. The optimization methodology is performed in a SCADA House Intelligent Management context and the results are analyzed to validate the SCADA system.

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In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

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In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. 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 proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

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The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

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The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

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This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.