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To achieve the aim of low carbon cities and zero energy districts, it is important to adapt the efficient technologies while maintaining the thermal comfort and sustainable environment. The new challenge in design and building new districts lies in a sustainable and smart way to minimize energy consumption and thus carbon emission. This challenge can be overcome by the use of early-stage energetic and environmental analysis of the planned districts, which can result in sustainable and efficient use of the resources. This thesis aims to assess the energy demand and the carbon emission for the proposed design of Jakobsgårdarna district in Borlänge, Sweden. The complete analysis of the neighbourhood is assessed through a tool - Urban Modeling Interface, a Rhinoceros-based plugin developed by the Sustainable Design Lab at Massachusetts Institute of Technology, USA. A base case scenario is evaluated for energetic performance, lighting, heating, cooling, hot water, daylight potential, walkability, and life cycle assessment. Then, a sensitivity analysis is addressed, in particular to evaluate the impact of daylight potential, archetypes, window to wall ratio, wall materials, future climate, and a possible lockdown, on energy consumption and carbon emission. In the base case, the analysis shows that preschool has the lowest specific energy consumption of 64.1 kWh/m2, while retail shops have the highest (92.2 kWh/m2) energy consumption. The simulated energy consumption of the offices and residential buildings is 72.1 kWh/m2, and 80.4 kWh/m2 respectively. The life cycle assessment reveals the advantage of the environment from building wooden houses instead of using concrete or masonry. The total embodied carbon for the whole district is 149.3 kgCO2/m2 divided as follow: 160.9 kgCO2/m2 for the school; 164.9 kgCO2/m2 for the offices, 159.6 kgCO2/m2 for the retail shops, 55.0 kgCO2/m2 for the wood residential buildings, 164.9 kgCO2/m2 for the masonry residential buildings. The sensitivity analysis explains exhaustively the influence, which has changes in the base case scenario. In particular, the future climate will decrease heating consumption due to the increase of the mean annual temperature and, on the other hand, increase cooling demand. While a possible lockdown to the district will rise consumption in residential buildings due to a higher use of equipment and lighting, but it will lower the energy use of offices and schools. The overall research results are expected to be useful to propose suggestions and recommendations for the next steps of design about Jakobsgårdarna district in Borlänge.

The primary energy costs of building materials and structures are discussed and comparisons are made between typical dwelling types. The economics of alternative wall, roof and floor constructions, providing various levels of insulationy are examined. Costs are assessed for a number of periods from 1970 to early 1980 for heating by gas and night rate electricity. The effect of price changes-on the economic attractiveness of insulation is investigated and the likely effects of future price rises are considered. It is concluded that, in certain circumstances, higher levels of insulation than those normally used in the UK have been economically attractive for the last few years and may possibly become more so. A survey of over fifty local authority houses with central heating, carried out by the author in Spring 1978, is described. Three types of houses of similar size were involved, having gas-fired 'wet' systems, and ducted warm air heating from electric storage and gas-fired units respectively. The survey was designed to determine certain aspects of occupant behaviour relevant to fuel consumption. Using regression techniques, relationships are obtained which explain more than two thirds of the variance of mean useful energy input rate between the houses of a given type in cold weather in terms of hours of use of central heating window opening habits, and for warm air heating, the closing of outlet registers. It was also revealed that for the house types with gas-fired heating the number of hours of use of the central heating was strongly influenced by household size and occupancy patterns. The implications for building design of the effects of occupant behaviour and of financial and energy costs are discussed.

The introduction of building management systems in large buildings have improved the control of building services and provided energy savings. However, current building management systems are limited by the physical level of integration of the building's services and the lack of intelligence provided in the control algorithms. This thesis proposes a new approach to the design and operation of building management systems using rule-based artificial intelligence techniques. The main aim of is to manage the services in the building in a more co-ordinated and intelligent manner than is possible by conventional techniques. This approach also aims to reduce the operational cost of the building by automatically tuning the energy consumption in accordance with occupancy profile of the building. A rule-based design methodology is proposed for building management systems. The design adopts the integrated structure made possible by the introduction of a common communications network for building services. The 'intelligence' is coded in the form of rules in such a way that it is both independent of any specific building description and easy to facilitate subsequent modification and addition. This is achieved using an object-oriented approach and classifying the range of data available into defined classes. The rules are divided into two knowledge-bases which are concerned with the building's control and its facilities management respectively. A wide range of rule-based features are proposed to operate on this data structure and are classified in terms of the data classes on which they operate. The concepts presented in this thesis were evaluated using software simulations, mathematical analysis and some hardware implementation. The conclusions of this work are that a rule-based building management system could provide significant enhancements over existing systems in terms of energy savings and improvements for both the building's management staff and its occupants.

abstract: Pavement surface temperature is calculated using a fundamental energy balance model developed previously. It can be studied using a one-dimensional mathematical model. The input to the model is changed, to study the effect of different properties of pavement on its diurnal surface temperatures. It is observed that the pavement surface temperature has a microclimatic effect on the air temperature above it. A major increase in local air temperature is caused by heating of solid surfaces in that locality. A case study was done and correlations have been established to calculate the air temperature above a paved surface. Validation with in-situ pavement surface and air temperatures were made. Experimental measurement for the city of Phoenix shows the difference between the ambient air temperature of the city and the microclimatic air temperature above the pavement is approximately 10 degrees Fahrenheit. One mitigation strategy that has been explored is increasing the albedo of the paved surface. Although it will reduce the pavement surface temperature, leading to a reduction in air temperature close to the surface, the increased pavement albedo will also result in greater reflected solar radiation directed towards the building, thus increasing the building solar load. The first effect will imply a reduction in the building energy consumption, while the second effect will imply an increase in the building energy consumption. Simulation is done using the EnergyPlus tool, to find the microclimatic effect of pavement on the building energy performance. The results indicate the cooling energy savings of an office building for different types of pavements can be variable as much as 30%. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2015

The residential sector in England is often identified as having the largest potential for emissions reduction at some of the lowest costs when compared against other sectors. In spite of this, decarbonisation within the residential sector has not materialised. This thesis explores the complexities of decarbonising the residential sector in England using a whole systems approach. It is only when the interaction between social, psychological, regulatory, technical, material and economic factors are considered together that the behaviour of the system emerges and the relationships between different system components can be explained giving insight into the underlying issues of decarbonisation. Building regulations, assessments and certification standards are critical for motivating and driving innovation towards decarbonising the building stock. Many existing building performance and evaluation tools are shown to be ineffective and confound different policy objectives. Not only is the existing UK SAP standard shown to be a poor predictor of dwelling level energy demand but it perversely incentivises households to increase CO2 emissions. At the dwelling level, a structural equation model is developed to quantify direct, indirect and total effects on residential energy demand. Interestingly, building efficiency is shown to have reciprocal causality with a household’s propensity to consume energy. That is, dwellings with high-energy efficiency consume less energy, but homes with a propensity to consume more energy are also more likely to have higher energy efficiency. Internal dwelling temperature is one of the most important parameters for explaining residential energy demand over a heterogeneous building stock. Yet bottom up energy demand models inadequately incorporate internal temperature as a function of human behaviour. A panel model is developed to predict daily mean internal temperatures from individual dwellings. In this model, socio-demographic, behavioural, physical and environmental variables are combined to estimate the daily fluctuations of mean internal temperature demand. The internal temperature prediction model is then incorporated in a bottom-up engineering simulation model. The residential energy demand model is then used to project decarbonisation scenarios to 2050. Under the assumption of consistent energy demand fuel share allocation, modelling results suggest that emissions from the residential sector can be reduced from 125 MtCO2 to 44 MtCO2 after all major energy efficiency measures have been applied, the power sector is decarbonised and all newly constructed dwellings are zero carbon. Meeting future climate change targets will thus not only require extensive energy efficiency upgrades to all existing dwellings but also the complete decarbonisation of end use energy demand. Such a challenge can only be met through the transformation of existing building regulations, models that properly allow for the effects of human behaviour, and flexible policies capable of maximising impact from a heterogeneous residential building stock.

No description available.

Together with a global concern for the reduction and conservation of energy, the oil crisis of 1973 brought about a turning point in the design of buildings. Responses in this vein were mostly concentrated on the simplistic one of sealing the building against outdoor conditions. This approach towards energy consumption, associated with the introduction of air-conditioning systems, led to different problems such as Sick Building Syndrome. Lack of user satisfaction also appeared to be a common complaint in such sealed, air-conditioned buildings, leading to a marked drop in employee efficiency and, hence, return on capital investments. In this study, Emek iShani, a sealed office building located in Ankara, whose curtain wall system was renovated in 2001, was investigated in terms of its natural ventilation potential under two sub-topics. With a survey conducted, user perception towards environmental conditions, and health problems they suffered were investigated. With a computer simulation, natural ventilation potential of the building in terms of energy consumption was examined. It was resulted from the survey that building occupants have serious health problems. They are also not satisfied with the way the ventilation system functions and most of the occupants liked to have a window opening to outside in order to adjust the inner conditions. It was resulted from the computer simulation that integration of natural ventilation did not make any significant difference in the annual energy consumption of the building. On the other hand, cooling loads of the building were eliminated in summer months. As a result, introduction of natural ventilation appeared to be an appropriate tool for more user satisfaction and energy conservation.

Les systèmes solaires thermiques combinés à un système d’appoint tel que une chaudière, une pompe à chaleur ou intégrant une machine à absorption, peuvent jouer un rôle important dans la réduction des consommations des bâtiments pour les besoins de chauffage, de climatisation et de production d’eau chaude sanitaire. Dans ce sens, la caractérisation des performances énergétiques des systèmes thermiques est un enjeu crucial.Les méthodes de caractérisation actuellement disponibles sont soit basées sur plusieurs essais physiques séparés des composants du système à évaluer, chose qui ne prend pas en compte les vraies interactions entre ces derniers, soit sur des modèles physiques qui peuvent être complexes et difficilement identifiables notamment du fait que les systèmes actuels sont compacts et préfabriqués en usine. En l’absence de méthode fiable pour estimer les performances des systèmes solaires thermiques avant leur intégration au bâtiment, le marché de ses derniers subit de fortes contraintes pour son développement.Dans ce contexte il devient indispensable de développer une méthodologie générique qui peut être appliquée à différentes typologies de systèmes et qui pallie les difficultés rencontrées par les méthodes actuelles.L’approche d’évaluation proposée dans ce mémoire est constituée de quatre étapes principales : la détermination d’une séquence de test, l’essai du système dans un banc d’essai semi-virtuel selon la séquence déterminée, l’acquisition des données et l’identification d’un réseau de neurones artificiels (RNA) du système et enfin la simulation du modèle en vue de l’estimation de la consommation du système dans l’environnement désiré. L’avantage d’utiliser un modèle complètement « boîte noire » du système complet à l’aide des RNA la rend totalement « non intrusive ». La connaissance des paramètres internes aux systèmes (rendements, conductivités thermiques, régulation etc.) n’est en conséquence pas nécessaire pour l’application de la méthodologie.La validation de la méthodologie a été réalisée à travers plusieurs expérimentations numériques, pour 7 systèmes issus de 3 typologies différentes, durant lesquelles les estimations des RNA ont été comparées aux calculs des modèles physiques dans plusieurs conditions différentes (qualité du bâtiment, climat et surface du capteur). Une application de l’approche développée dans le cas de 5 systèmes réels a permis la confirmation de la pertinence de la méthodologie. / Solar thermal systems combined with a backup system such as a boiler, a heat pump or incorporating an absorption chiller, can play an important role in reducing buildings energy consumption for heating, cooling and hot water production needs. In this sense, characterizing the energy performance of thermal systems is crucial.Currently available methods of system characterization are either based on several separate physical tests of system components to be evaluated, which do not take into account the real interactions between them, or on physical models that can be complex and difficult to identify especially because systems nowadays are compact and prefabricated in the factory. Due to the lack of a reliable method to estimate the performance of solar thermal systems before their integration into buildings, their market faces a lot of impediment to be developed.In this context, it becomes essential to develop a generic methodology that can be applied to different types of systems which overcomes the difficulties encountered by the current ones.The proposed evaluation approach in this manuscript is composed of four main steps: determining a test sequence, testing the system in a semi-virtual test bench according to predetermined sequence, data acquisition and identifying an artificial neural network (ANN) of the system and finally the model simulation in order to estimate the system consumption in the desired boundary condition. Using a completely "black box" model of the whole system using the ANN makes the methodology totally "non-intrusive". No prior knowledge about the systems internal parameters (yields, thermal conductivities, regulation etc.) is necessary to apply the proposed approach.The methodology validation was performed through several numerical experiments for seven systems coming from three different typologies. During the validation process, ANN estimates were compared with calculations of physical models in several different conditions (quality of building, climate and collector area). The developed approach was applied to five real systems as well. The application results allowed the confirmation of the methodology relevance.

This thesis deals with heating system in accommodation facility. It clarifies the way of controlling multiple decentralized systems which results in automatization of the whole heating system. Heating distrubition into individual zones is controlled by central server which communicates with reservation system of accommodation facility. The main goal is to lower expenses for heating.