17 resultados para energy requirement model


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Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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The project “InnovationCity Ruhr” deals with the reconstruction of the city of Bottrop with regard to energy saving measures. The aim is to make the city more environmental friendly in order to create a model for other industrial cities. Until the conclusion of the project in the year 2020, it is planned to change the surface of Bottrop in several positive ways. This paper focuses on the description of the project to give the reader an example of what exactly is done within the scope of InnovationCity Ruhr. Besides that, the link to the subject of sociology shall be given in order to show that the project is a prime example for social innovation.

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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Gestão e Sistemas Ambientais

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

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33rd IAHR Congress: Water Engineering for a Sustainable Environment

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation to obtain the Doctoral degree in Physics Engineering

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Based on the presentation and discussion at the 3rd Winter School on Technology Assessment, December 2012, Universidade Nova de Lisboa (Portugal), Caparica Campus, PhD programme on Technology Assessment

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores

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Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

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The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.

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Cryocoolers have been progressively replacing the use of the stored cryogens in cryogenic chains used for detector cooling, thanks to their higher and higher reliability. However, the mechanical vibrations, the electromagnetic interferences and the temperature fluctuations inherent to their functioning could reduce the sensor’s sensitivity. In order to minimize this problem, compact thermal energy storage units (ESU) are studied, devices able to store thermal energy without significant temperature increase. These devices can be used as a temporary cold source making it possible to turn the cryocooler OFF providing a proper environment for the sensor. A heat switch is responsible for the thermal decoupling of the ESU from the cryocooler’s temperature that increases when turned OFF. In this work, several prototypes working around 40 K were designed, built and characterized. They consist in a low temperature cell that contains the liquid neon connected to an expansion volume at room temperature for gas storage during the liquid evaporation phase. To turn this system insensitive to the gravity direction, the liquid is retained in the low temperature cell by capillary effect in a porous material. Thanks to pressure regulation of the liquid neon bath, 900 J were stored at 40K. The higher latent heat of the liquid and the inexistence of triple point transitions at 40 K turn the pressure control during the evaporation a versatile and compact alternative to an ESU working at the triple point transitions. A quite compact second prototype ESU directly connected to the cryocooler cold finger was tested as a temperature stabilizer. This device was able to stabilize the cryocooler temperature ((≈ 40K ±1 K) despite sudden heat bursts corresponding to twice the cooling power of the cryocooler. This thesis describes the construction of these devices as well as the tests performed. It is also shown that the thermal model developed to predict the thermal behaviour of these devices, implemented as a software,describes quite well the experimental results. Solutions to improve these devices are also proposed.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.