This study addresses 5 uncertainties that exist in the operation of HVAC systems, which will presumably affect the actual energy consumption of the HVAC system in comparison to the consumption under idealized bahavior. We consequently add these parameters and their uncertainty range into the source code, eventually resulting in an EnergyPlus program in which the HVAC operation uncertainty is embedded as so-called model form uncertainty. The upgraded EnergyPlus is tested for each parameter uncertainty separately, and to show the impact of each uncertainty albeit for hypothetical uncertainty ranges of the parameters.

This exploratory research examined the degree of adoption and impact of the concepts of Building Information Model (BIM), Integrated Project Delivery (IPD), Integrated Design Process (IDP) and Building Energy Simulation (BES) on the design processes of advanced architectural firms when executing sustainable design. Six offices identified by the press for a strong commitment to sustainable design and influence in the design of high performance buildings were selected as cases. In semi-standardized interviews, these firms presented their perceptions of the influence of BIM, BES, and IPD/IDP. The results show that a generalization of sustainable design processes is possible. A design process for sustainability (DEPROSU) model was created by collecting best practices from data gathered from the interviews and the critical literature review. Secondary contributions show that BIM, IDP/IPD and BES have a synergistic effect in sustainable design methods, and that the human resource profile from these firms has evolved towards multi-skilled professionals knowledgeable in BES, BIM, parametric design, sustainability and construction processes. This research provides evidence of commonalities found in the design processes of the selected firms. These commonalities, which have been represented in the DEPROSU model, can potentially be validated as protocols or standards for sustainable design, providing architectural design practices with concrete patterns for improvement and or validation of their design methods.

abstract: With the increasing interest in energy efficient building design, whole building energy simulation programs are increasingly employed in the design process to help architects and engineers determine which design alternatives save energy and are cost effective. DOE-2 is one of the most popular programs used by the building energy simulation community. eQUEST is a powerful graphic user interface for the DOE-2 engine. EnergyPlus is the newest generation simulation program under development by the U.S. Department of Energy which adds new modeling features beyond the DOE-2's capability. The new modeling capabilities of EnergyPlus make it possible to model new and complex building technologies which cannot be modeled by other whole building energy simulation programs. On the other hand, EnergyPlus models, especially with a large number of zones, run much slower than those of eQUEST. Both eQUEST and EnergyPlus offer their own set of advantages and disadvantages. The choice of which building simulation program should be used might vary in each case. The purpose of this thesis is to investigate the potential of both the programs to do the whole building energy analysis and compare the results with the actual building energy performance. For this purpose the energy simulation of a fully functional building is done in eQUEST and EnergyPlus and the results were compared with utility data of the building to identify the degree of closeness with which simulation results match with the actual heat and energy flows in building. It was observed in this study that eQUEST is easy to use and quick in producing results that would especially help in the taking critical decisions during the design phase. On the other hand EnergyPlus aids in modeling complex systems, producing more accurate results, but consumes more time. The choice of simulation program might change depending on the usability and applicability of the program to our need in different phases of a building's lifecycle. Therefore, it makes sense if a common front end is designed for both these simulation programs thereby allowing the user to select either the DOE-2.2 engine or the EnergyPlus engine based upon the need in each particular case. / Dissertation/Thesis / M.S. Architecture 2010

The European Union (EU) has expressed determination of reducing its energy consumption and the EU’s 2010 Energy Performance of Buildings Directive states that all new buildings must be nearly zero energy by the end of the year 2020. Dynamic or “smart” windows have been shown to be able to reduce HVAC energy consumption, lighting energy and peek cooling loads in hot climates in the US but it is difficult to find any work concerned with colder climates. This study is intended to capture the performance of dynamic windows in a variety of European climates to explore potential contributions to reaching the EU’s energy goals. The building energy simulations of this study have been conducted in IDA ICE for an office section with a large window. Three model variants are compared: without a window shading, with an external window blind and with a dynamic window. This comparison is repeated for six different locations; Kiruna, Reykjavik, Stockholm, Copenhagen, Paris and Madrid. The results of this study show that the dynamic window can reduce the total consumed energy for lighting, heating and cooling in the range of 10%-30% more than the external blind, depending on location. The reduction is 50%-75% when compared to the unshaded window. This level of performance can move Europe a step closer to zero energy buildings.

About 12% of the greenhouse gas emissions and 40% of the total energy use in the EU derive from the buildings. User behavior, construction, and HVAC systems has a significant impact on a building’s energy use. If a building is to be energy-efficient it is important to understand how all these parameters are connected. This study is motivated by the need to decrease the energy use in buildings to reach the goals of energy use and greenhouse gas emissions.  In this thesis, measurements of indoor climate and electricity use, together with time diaries was used to create input data for an energy simulation model of a retirement home. A parametric study was conducted to simulate how energy demand was affected by changes in five different parameters in an office building. Also, two different energy-efficiency indicators were used to see how indicators can affect the perceived energy-efficiency of buildings. High amount of airing and low electricity use had the most impact on the heating demand in the retirement home, and electricity use had the highest impact on the total energy demand in the office building. The model of the retirement home using data gathered on-site had 24% higher energy use than the model using standard user input data. In the office building, total energy demand for heating and cooling could be lowered with 12-31% by lowering the electricity use with 30% compared to standard user input data. For office buildings the most important thing to lower total energy demand seems to be lowering the electricity use. Using today’s standard user input data does not correspond well to using on-site gathered data in a retirement home and it is therefore important to develop the standard user input data further. The indicator kWh/m2, seems to promote buildings with low occupancy. This could lead to buildings being utilized in an in-efficient way. The indicator kWh/m2 should either be replaced or combined with an indicator that takes occupancy into consideration. / Runt 12% av utsläppen av växthusgaser och 40% av den totala energianvändningen i EU kommer från byggnader. Brukarbeteende, konstruktion och HVAC-system har signifikant påverkan på en byggnads energianvändning. Om en byggnad ska bli så energieffektiv som möjligt är det viktigt att förstå hur dessa parametrar hör ihop. Denna studie motiveras av behovet att minska energianvändning i byggnader för att nå målen för energianvändning och utsläpp av växthusgaser.  I denna avhandling användes mätningar av inomhusklimat och elanvändning, tillsammans med tidsdagböcker, för att skapa indata till en energisimuleringsmodell av ett ålderdomshem. En parameterstudie genomfördes för att simulera hur energibehovet påverkades av ändringar i fem olika parametrar i en kontorsbyggnad. Två olika indikatorer för energieffektivitet användes också, för att se hur olika indikatorer påverkar hur en byggnads energieffektivitet uppfattas. Hög grad av vädring och låg elanvändning hade störst påverkan av energibehovet i ålderdomshemmet, och i kontorsbyggnaden påverkades det totala energibehovet mest av elanvändningen. Modellen av ålderdomshemmet där data insamlad på plats användes hade 24% högre värmebehov än modellen som använde standardiserade brukarindata. Det totala energibehovet för värme och kyla i kontorsbyggnaden kunde sänkas med 12-31% genom att sänka elanvändningen med 30% jämfört med standardiserad brukarindata. Det viktigaste för att få ner det totala energibehovet i kontorsbyggnader verkar vara att sänka elanvändningen. Att använda dagens standardvärden för brukarindata överensstämmer inte väl med att använda data insamlad på plats för ett ålderdomshem. Det är därför viktigt att vidareutveckla standardiserad brukarindata. Indikatorn kWh/m2 verkar främja byggnader med låg beläggning. Detta skulle kunna leda till att byggnader utnyttjas på ett ineffektivt sätt. Indikatorn kWh/m2 skulle därför behöva ersättas eller kombineras med en indikator som även tar byggnadens beläggning i beaktande.

Reliable evaluation methods is needed to ensure that investments in energy conservation measures (ECMs) and the construction of new energy efficient buildings lives up to the promised and expected performance. This thesis presents and evaluates a regression method for estimation of influential building parameters: transmission losses above ground (including air leakage), ground heat loss, and overall heat loss coefficient. The analysis is conducted with separately metered electricity, heating and weather data using linear regression models based on the simplified steady-state power balance for a whole building. The evaluation consists of analyzing the robustness of the extracted parameters, their suitability to be used as input values to building energy simulations (BES) tools. In addition, differences between uncalibrated and calibrated BES models are analyzed when they are used to calculate energy savings. Finally the suitability of using a buildings overall heat loss coefficient as a performance verification tool is studied. The presented regression method exhibits high robustness and good agreement with theory. Knowledge of these parameters also proved beneficial in BES calibration procedures as well as in performance verifications. Thus, the presented method shows promising features for reliable energy performance assessments of buildings.

In traditional planning process, energy analysts work on finalized architectural designs and have limited capability to amend inefficient energy features such as high aspect ratio. Energy efficiency being a major part of sustainable design, the need for performance-oriented design tools has become imminent. There is a wide range of energy simulation tools across the world. Crawley et al. (2005) proposes a plain comparison of the most common ones based on vendor-supplied information. The present report aims to identify simulation tools that can help architects making energy-efficient design decisions in early stage of building process and the most suitable programs will be tested on a standard case in Stockholm area with respect to their architecture, functionalities, usability and limitations.

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: 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.