<p>In June 2006 the Swedish government decided that the use of energy in buildings should be reduced by 20 percent until 2020, compared to the level of energy used in 1995. To contribute to this goal, the real estate company “Eskilstuna Kommunfastigheter AB”, set up own goals for their buildings. In 2009, the goal for schools was to have a maximum energy use of 118 kWh/m²year for heating and hot water.</p><p>The school “Hållsta skola”, just south of Eskilstuna, exceeds the limit since it used 270 kWh in 2008. The school is heated by oil burners, which is not desirable since oil is a fossil fuel. The aim of this study was to identify cost effective measures for decreased energy use for heating and hot water in the school, and to find alternatives to the oil burners.</p><p>The school was built between 1963 and 1975 and consists of two buildings. The insulation in the roof, walls, windows and floor is poor and the ventilation is mainly performed without heat recovery. Measures including insulation of the roof, new windows, heat recovery in the ventilation system and more effective water taps were studied with Life Cycle Cost analysis (LCC) and Pay-off analysis. The energy use with and without the new performance was calculated with the building simulation program VIP+. If all of the economically favorable measures are carried out the total energy use would decrease to 167 kWh/m²year.</p><p>One of the alternatives to oil burners that were suggested is heat pumps. The two types of heat pumps studied, ground source or air source, were both found to be profitable, although the ground source heat pump would be slightly more profitable. In the calculations it was considered that an electric boiler would back up the heat pumps during cold days. With heat pumps, the energy bought for heating and hot water would be about 55 kWh/m²year, which is well below the goal of maximum 118 kWh/m²year.</p>

In June 2006 the Swedish government decided that the use of energy in buildings should be reduced by 20 percent until 2020, compared to the level of energy used in 1995. To contribute to this goal, the real estate company “Eskilstuna Kommunfastigheter AB”, set up own goals for their buildings. In 2009, the goal for schools was to have a maximum energy use of 118 kWh/m2year for heating and hot water. The school “Hållsta skola”, just south of Eskilstuna, exceeds the limit since it used 270 kWh in 2008. The school is heated by oil burners, which is not desirable since oil is a fossil fuel. The aim of this study was to identify cost effective measures for decreased energy use for heating and hot water in the school, and to find alternatives to the oil burners. The school was built between 1963 and 1975 and consists of two buildings. The insulation in the roof, walls, windows and floor is poor and the ventilation is mainly performed without heat recovery. Measures including insulation of the roof, new windows, heat recovery in the ventilation system and more effective water taps were studied with Life Cycle Cost analysis (LCC) and Pay-off analysis. The energy use with and without the new performance was calculated with the building simulation program VIP+. If all of the economically favorable measures are carried out the total energy use would decrease to 167 kWh/m2year. One of the alternatives to oil burners that were suggested is heat pumps. The two types of heat pumps studied, ground source or air source, were both found to be profitable, although the ground source heat pump would be slightly more profitable. In the calculations it was considered that an electric boiler would back up the heat pumps during cold days. With heat pumps, the energy bought for heating and hot water would be about 55 kWh/m2year, which is well below the goal of maximum 118 kWh/m2year.

Baigiamajame magistro darbe nagrinėjamos pastatų energijos vartojimo efektyvumo problemos. Ieškoma būdų, kaip galima būtų dar projektavimo arba renovacijos stadijoje sukurti energetiškai efektyvų pastatą naudojant naujoviškus metodus. Darbe atlikta literatūros, susijusios su kompiuteriniu energetiniu modeliavimu, analizė, atliktas kelių populiariausių energetinio modeliavimo programų palyginimas ir tolesniems skaičiavimams pasirinkta geriausia dinaminio modeliavimo programa – EnergyPlus. Buvo užsibrėžtas tikslas ištirti šios panaudojimo programos galimybes sprendžiant hipotetinio administracinės paskirties pastato modelį. Buvo užsibrėžti pagrindiniai uždaviniai – ištirti šio modelio šildymo/šaldymo galios priklausomybes per projektinę parą nuo įvairių faktorių. Sukūrus duomenų rinkmeną, aprašančią pastatą, buvo atliktas modeliavimas įvairiems įstiklinimo plotams, įvairioms pastato orientacijoms ir įvairioms stiklo rūšims. Buvo nustatyta atskirai šių faktorių įtaka pastato šildymo/šaldymo galiai. Tam, kad būtų galima įvertinti potencialų energijos sąnaudų sumažėjimą, kuris gali būti pasiektas taikant modeliavimą, buvo išanalizuotos dvi skirtingos to paties pastato modifikacijos: blogiausias ir geriausias variantas. Skirtumas tarp jų buvo gautas didelis, ypatingai potencialios šalčio santaupos. EnergyPlus apskaičiuota šildymo galia taip pat buvo palyginta su dviem kitomis paprastesnėmis skaičiavimo metodikomis. EnergyPlus paskaičiuota galia žymiai mažesnė, nei kitais dviem... [to full text] / In this final Master paper were analyzed problems, related with buildings energy consumption and energy efficiency. For further analysis were chosen innovative tools – energy simulation programs, which help to save energy before building is built or renovated. After literature, related with building energy simulation, was analyzed, comparison of the most popular energy simulation programs was done. After this, EnergyPlus was chosen as the best dynamic energy simulation program. The main purpose of this paper – to investigate adaptability of the program in our applications. For investigation was chosen model of hypothetical office building. The main tasks were to calculate, how different factors influence building heating/cooling loads during design days. Main data file, describing building, was created and were made simulations for different cases of glazing, building orientations and glass types. After the influence of these factors was defined, for evaluating potential energy saving through energy simulation, was created the best and the worst case for the same building. Difference between cases was very big, especially in cooling loads. EnergyPlus calculation results were also compared with results of two simpler, often used heating power calculation methods. Heating power, calculated with EnergyPlus, was much smaller, than in other two cases. After all was made conclusion, that EergyPlus is adaptable in our appliances and, just through using dynamic energy simulation... [to full text]

Les bâtiments représentent un des principaux leviers d'action pour optimiser l'efficacité énergétique et la réduction des émissions de CO2 dans les villes. Afin d'optimiser les performances énergétiques, différentes études ont été menées sur les performances thermiques aussi bien du de point de vue de la conception, de la calibration de modèle que de l'impact de changement climatique. L'analyse de sensibilité vise à évaluer la part d'incertitude due à chacune des variables ou des paramètres qui peuvent influencer ces performances.La plupart des études en bâtiment menées dans la littérature se placent dans un cadre statique qui ne représente pas l'évolution du système. Il est très vite apparu nécessaire de développer des méthodes qui prennent en compte à la fois la dépendance des entrées et la dimension temporelle qui elle-même comporte toujours de la dépendance. Parmi les différentes méthodes d'analyse de sensibilité, nous avons privilégié la méthode globale, reposant sur le calcul des indices de sensibilité de Sobol. Le calcul effectif des indices de sensibilité permet de hiérarchiser les paramètres d'entrée en fonction de leur influence sur la sortieLes indices de Sobol peuvent se calculer de différentes façons. Nous nous sommes intéressés notamment à la méthode Pick and Freeze basée sur l'échantillonnage. Celle-ci repose sur l'hypothèse fondamentale et dans la pratique le plus souvent non vérifiée d'indépendance des entrées. Cela nous a amené du point de vue statistique à développer des techniques nouvelles pour tenir compte du caractère des entrées de type dynamique et dépendantes entre elles à la fois dans le temps et à chaque instant.Nous avons placé notre travail dans l'optique de méthodes permettant de se ramener au cas d'entrées indépendantes. Notre préoccupation a été de modéliser les entrées de manière souple, aisément transposable à d'autres situations concrètes et permettant des simulations relativement aisées. Afin de rendre compte du lien temporel entre les variables, nous avons choisi de considérer un indice dépendant de l'instant de calcul et de quantifier la variabilité de la sortie non pas seulement à la variabilité de l'entrée à l'instant t mais aussi à cette même variabilité provenant des instants précédents. Cette vision permet d'introduire la notion de mémoire utile pour le calcul de la sensibilité. Nous avons développé une méthode d'estimation des indices de Sobol pour des entrées dépendantes statiques a priori. Elle peut néanmoins être mise en œuvre pour des entrées dynamiques de courte mémoire mais les calculs sont alors très lourds dès que le nombre d'entrées est grand ou les mémoires importantes. Cette méthode permet de séparer des variables dépendantes de loi quelconque en des variables indépendantes de loi uniforme. Facile à mettre en œuvre ces méthodes d'estimation ne s'appuient pas sur des hypothèses d'indépendance des entrées, elles permettent alors un large éventail d'applications.Nous avons appliqué notre méthodologie à un bâtiment existant, apportant ainsi un outil utile à l'analyse du comportement thermique et donc à son optimisation. Nous avons pu montrer différentes situations en analysant l'ordre des variables suivant les sensibilités à partir de mesures. Deux critères ont été étudiés. Un critère de confort : l'étude de la température intérieure et un critère de performance : l'énergie de chauffage. / Buildings represent one of the main levers of action to optimize energy efficiency and reducing emissions of $ CO_2 $. To understand how perform energy consumption of a building, different studies have been conducted on the thermal performance both the point of view of design and model calibration as the climate change impact. Energy performance can be optimized according to these studies by evaluating the degree of uncertainty due to each of the variables or parameters that may influence performance. This stage is called sensitivity analysis.Most building studies in the literature are placed in a static framework that does not represent the evolution of the system. The variables whose sensitivity to be studied are either considered at a given time or the input-output models are not dynamic. It became necessary to develop methods that take into account both the dependence of the inputs and the temporal dimension which itself always involves dependence. Among the different methods of sensitivity analysis, we have focused on the global method, based on the calculation of Sobol sensitivity indices. Sobol index of a parameter (or group of parameters) is a statistical indicator of easy interpretation. It allows to measure the importance of this parameter (or group of parameters) on the variability of a scalar quantity of interest, depending on the model output. Sensitivity indices allow to rank input parameters according to their influence on the output.Sobol indices can be calculated in different ways. We focused on the Pick and Freeze method based on sampling. This is based on a fundamental assumption and in practice often unverified : inputs independence. This led us statistically to develop new techniques to take into account the dynamic characteristic of inputs and dependents both in time and in every moment. Our work focuses on methods that can bring back to the case of independent inputs. Our concern was modelled in a flexible way inputs, easily transferable to other concrete situations and allowing relatively easy simulations. The input-output relationships are not important as the only constraint, of course not trivial, possible simulation.In order to reproduce the temporal relationship between the variables, we chose to consider an index dependent, in the non-stationary case (especially if there are seasonal phenomena), on the time of calculation and quantify the variability of output not not only to the variability of the input at time $ t $, but also to the same variability from previous times. This vision allows to introduce the concept of usable memory for the calculation of the sensitivity.The second method that we have developed is an estimation method of Sobol indices for static dependent inputs a priori. It may nevertheless be implemented for dynamic inputs with short memory but the calculations are then very heavy when the number of inputs are large or own important memories. This method allows to separate dependent variables of any law in independent variables uniformly distributed.Easy to implement these estimation methods developed are not based on assumptions of independence of inputs. It then allows a wide range of applications.This method applied to an existing building can help improve energy management and can be useful in the design from the implementation scenarios. We could show different situations by analysing the variable order according to the sensitivities from measurements on a test building. Two criteria were studied. A criterion of comfort: the study of indoor temperature and performance criteria: the heating energy.

abstract: Buildings in the United States, account for over 68 percent of electricity consumed, 39 percent of total energy use, and 38 percent of the carbon dioxide emissions. By the year 2035, about 75% of the U.S. building sector will be either new or renovated. The energy efficiency requirements of current building codes would have a significant impact on future energy use, hence, one of the most widely accepted solutions to slowing the growth rate of GHG emissions and then reversing it involves a stringent adoption of building energy codes. A large number of building energy codes exist and a large number of studies which state the energy savings possible through code compliance. However, most codes are difficult to comprehend and require an extensive understanding of the code, the compliance paths, all mandatory and prescriptive requirements as well as the strategy to convert the same to energy model inputs. This paper provides a simplified solution for the entire process by providing an easy to use interface for code compliance and energy simulation through a spreadsheet based tool, the ECCO or the Energy Code COmpliance Tool. This tool provides a platform for a more detailed analysis of building codes as applicable to each and every individual building in each climate zone. It also facilitates quick building energy simulation to determine energy savings achieved through code compliance. This process is highly beneficial not only for code compliance, but also for identifying parameters which can be improved for energy efficiency. Code compliance is simplified through a series of parametric runs which generates the minimally compliant baseline building and 30% beyond code building. This tool is seen as an effective solution for architects and engineers for an initial level analysis as well as for jurisdictions as a front-end diagnostic check for code compliance. &#8195; / Dissertation/Thesis / Rocky Mountain Institute- Model Manager Tool / ECCO Spreadsheet Tool / M.S. Built Environment 2011

abstract: City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study. The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation. Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models. The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits. From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction. / Dissertation/Thesis / Masters Thesis Architecture 2017

Les bâtiments existants reposent sur un équilibre stable qui assure leur durabilité. Toute exécution de travaux de réhabilitation qui déplace cet équilibre peut être à l'origine de désordres. En ce sens, les travaux peuvent être qualifiés de pathogènes. Dans le cadre de rénovations énergétiques, la problématique de l'humidité dans les bâtiments existants nécessite donc une attention particulière. Il convient donc de fournir aux acteurs de la construction des modèles de simulation du comportement hygrothemique global des bâtiments et d'évaluer les risques de pathologies liées à l'humidité. L'élaboration de ces modèles passent par la résolution de problèmes non-linéaires, de grande échelles spatiales et temporelles, et parfois paramétrique. Ils sont donc complexes à résoudre et les méthodes de réduction de modèle permettent de répondre à cette problématique. Deux techniques de réduction de modèles ont été explorées: la Décomposition Orthogonale Propre (POD) et la Décomposition Générale Propre (PGD). Elles ont été appliquées sur des problèmes de diffusion non-linéaire, couplée chaleur et humidité, dans les matériaux poreux. Ces deux méthodes ont été évaluées et comparées sur les critères de réduction du coût numérique de résolution du problème et sur la précision de calcul de la solution. Sur la base de ces analyses, la PGD a été retenue pour la suite des travaux. Grâce à ses caractéristiques, la méthode PGD présente plusieurs avantages d'ordre structurel, recensés dans la littérature. Au chapitre 3, nous avons utilisé ces prérogatives pour répondre aux problématiques de complexité des modèles de simulation des bâtiments. Notre intérêt s'est concentré sur la réduction de la complexité numérique de problèmes multi-dimensionnels, sur la globalisation de problèmes locaux et sur la création de méta-modèle ou solution PGD paramétrique. Plusieurs cas académiques ont été considérés pour illustrer ces propos. Nous avons traité des problèmes de transferts non-linéaires dans les matériaux poreux et des problèmes de transferts multizone dans un bâtiment. Enfin, la dernière partie des travaux est axée sur la construction d'un modèle global articulant des modèles réduits PGD. Deux modèles sont construits. Le premier couple un modèle réduit enveloppe PGD avec un modèle complet multizone. Ces travaux ont été réalisés dans le cadre d'une collaboration avec le laboratoire LST de l'université PUCPR de Curitiba, Brésil. Ce partenariat a permis de bénéficier du modèle reconnu et validé Domus pour la simulation des transferts multizones. Les nombreuses possibilités du logiciel ont pu être exploitées. Deux cas d'études sont abordés. Le premier concerne la résolution d'un problème paramétrique pour l'étude de scénarios de réhabilitation en fonction de la perméabilité à la vapeur de l'isolant. Le second porte sur la modélisation globale d'un bâtiment bi-zone intégrant une simulation bi-dimensionnelle d'un pont thermique. Il est possible d'élaborer un modèle global présentant une plus grande réduction de la complexité du problème que celui réalisé avec Domus. Le deuxième modèle couple donc un modèle réduit PGD pour le problème enveloppe et une solution PGD paramétrique pour le problème multizone. Les performances de ce modèle ont été discutées en terme de précision de calcul de la solution et d'économie numérique de résolution du problème. La pertinence des méthodes de réduction de modèle pour la simulation du comportement des bâtiments a été montrée. En particulier, la méthode PGD permet d'apporter une nouvelle approche de résolution ces problèmes. / Excessive levels of moisture in buildings may damage the construction quality. Moisture also has an effect on indoor air quality and thermal comfort of the occupants. Thus moisture is a possible source of disorders in buildings. It is therefore important to continue developing numerical models to simulate the global hygrothermal behaviour of buildings. To achieve this aim, it is necessary to solve non-linear problems, with high space and time scales, with fine discretisation and sometimes parametric. This mathematical problems are complex to solve. Thus model reduction techniques and efficient ways of numerical simulation are worth investigations. Two techniques were assessed : the Proper Orthogonal Decomposition (POD) and the Proper Generalised Decomposition (PGD). They were first applied on non-liner coupled heat and mass transfers in porous materials. Both were compared and evaluated carrying about the reduction of the cost of resolution and the precision of the solution computed. Following this analysis, the PGD was selected for our next investigations. Due to it representation, the PGD method has several interesting features, already reviewed in literature.Thus, chapter 3 proposed to illustrate this advantages on different issues of modelling buildings hygrothermal behaviours. We focused on the reduction of the complexity of multi-dimensional problems, on the globalisation of local problems and on building PGD parametric solution or meta-model. Several academic case study were considered to illustrate these points. We analysed non-linear heat and mass transfers in porous materials and multizone air building transfers. In last part, we elaborated a PGD reduced order model to perform whole building energy simulation. Two different models were built. The first one associates a PGD model for envelope problem and a large original model for multizone problem. This work was done during a collaboration with the LST laboratory, at PUCPR University, Curitiba, Brazil. The main interest was the benefits of using their validated and admitted model Domus for solving multizone problem. Two case study were analysed. The first one analyse a parametric problem for the study of the retrofitting a building in function of the vapour permeability of the insulating material. The second one focused on the whole building energy simulation of a two-zone building with 2-dimension transfers in the wall assembly. A second global PGD reduced order model was elaborated, with a higher reduction of the numerical complexity of the problem. This model associates a PGD model for solving envelope problem and a PGD parametric solution for the multizone problem. The performance of this model was analysed investigating the numerical gain and the precision of the solution computed. In conclusion, the relevance of reduction model techniques for performing whole building energy simulation was revealed. The PGD method contributes to a new approach for solving this problems.

By 2050, the world’s population is expected to reach 9.7 billion, with over half living in urban settlements (United Nations, 2015). Planning and designing new urban developments and improving existing infrastructure will create or reshape urban landscapes and will carry significant implications for energy consumption, infrastructure costs, and the urban microclimate on a larger scale. Researchers and industry professionals must recognize how changes in land use affect the urban microclimate and, therefore, building energy consumption. Built environment and microclimate studies commonly involve modeling or experimenting with mass and energy exchanges between natural and the built environment. Current methods to quantify these exchanges include the isolated use of microclimate and building energy simulation tools. However, current urban planning and building design processes lack a holistic and seamless approach to quantifying all thermodynamic interactions between natural and built environments; nor is there a method for communicating and visualizing the simulated building energy data. This dissertation has developed a coupling method to quantify the effects of the urban microclimate on building energy consumption. The coupling method was tested on a medium-sized office building and applied to a design case, a redevelopment project in Pittsburgh, PA. Three distinct approaches were used. First, to develop the coupling method, a study was conducted to quantify the importance of accurate microclimate model initialization for achieving simulation results that represent measured data. This initialization study was conducted for 24 cases in the Pittsburgh climate. The initialization study developed a rule-based method for estimating the number of ENVI-met simulations needed to predict the microclimate for an annual period. Second, a coupling method was developed to quantify these microclimate effects on building energy consumption. The Center for Sustainable Landscapes (CSL) building was used as a test-case for this coupling method to measure improvement in predicting building heating and cooling energy consumption. Results show that the coupling method, more than the TMY3 weather data used for energy simulations, can improve building energy consumption predictions for the winter and summer months. Third, to demonstrate industry implications, the coupling method was applied to a design case, the Lower Hill District Redevelopment, Pittsburgh, PA. Comparing the decoupled energy model and TMY3 weather data revealed a high degree of variation in the heating and cooling energy consumption. Overall results reinforced the hypothesis that building surface level coupling is not essential if the energy model accounts for the microclimate effects. A Design Decision Support (DDS) method was also developed as a tool for project stakeholders to communicate high-fidelity simulated energy data.

Construction projects are complex endeavors that require the involvement of different professional disciplines in order to meet various project objectives that are often conflicting. The level of complexity and the multi-objective nature of construction projects lend themselves to collaborative design and construction such as integrated project delivery (IPD), in which relevant disciplines work together during project conception, design and construction. Traditionally, the main objectives of construction projects have been to build in the least amount of time with the lowest cost possible, thus the inherent and well-established relationship between cost and time has been the focus of many studies. The importance of being able to effectively model relationships among multiple objectives in building construction has been emphasized in a wide range of research. In general, the trade-off relationship between time and cost is well understood and there is ample research on the subject. However, despite sustainable building designs, relationships between time and environmental impact, as well as cost and environmental impact, have not been fully investigated. The objectives of this research were mainly to analyze and identify relationships of time, cost, and environmental impact, in terms of CO2 emissions, at different levels of a building: material level, component level, and building level, at the pre-use phase, including manufacturing and construction, and the relationships of life cycle cost and life cycle CO2 emissions at the usage phase. Additionally, this research aimed to develop a robust simulation-based multi-objective decision-support tool, called SimulEICon, which took construction data uncertainty into account, and was capable of incorporating life cycle assessment information to the decision-making process. The findings of this research supported the trade-off relationship between time and cost at different building levels. Moreover, the time and CO2 emissions relationship presented trade-off behavior at the pre-use phase. The results of the relationship between cost and CO2 emissions were interestingly proportional at the pre-use phase. The same pattern continually presented after the construction to the usage phase. Understanding the relationships between those objectives is a key in successfully planning and designing environmentally sustainable construction projects.

The master thesis will concern design of hybrid photovoltaic system for a family house with accumulation of electric energy. Three alternatives of power consumption will be made. For each alternative multiple simulations will be carried out with different amount of photovoltaic panels and batteries. The most appropriate alternative and size of photovoltaic system will be chosen based on those simulations. Finally the choice of alternative will be described.