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International audience; The building stock accounts for 43% of the total French final energy consumption in 2017. The French building stock mainly includes residential and tertiary buildings, which have very different consumption patterns. Today, building stock models are largely used in many countries for energy demand forecast and decision making. In this context, good knowledge of the building stock is essential for modeling. However, this type of model is lacking for the tertiary sector, as it is difficult to categorize buildings that have a wide variety of area and energy uses, different systems and complex dynamic trends. Existing stock models are mostly based on an aggregated representation of the total heated floor area of the building stock. Such a representation limits explicit studies of the factors affecting the energy demand and fails at taking into account heterogeneity. This paper exposes and discusses new methods aiming at modeling the tertiary building stock at the city scale in France. While mainly relying on open source public data, methods are designed to be applicable at any scale (from small cities to large region or even national scale). 1. Introduction For many years, building energy modeling and simulation have been largely used in advising decision makers in the domain of energy policy [1]. The building stock accounts for 43% of the total French final energy consumption in 2017 [2]. The tertiary sector is responsible for one third of the total building stock's consumption. Whereas considerable research has been devoted to the residential building stock, less attention has been paid to the tertiary building stock. Heterogeneity is the main reason that makes it difficult to study the tertiary sector. The representation of the tertiary building stock is usually based on the total heated floor area of economic sub-sectors, aggregated at national scale, omitting heterogeneity. Through this work, we develop a building stock model which allows a detailed description of this sector's building stock. The purpose of this model is to study the energy demand as well as long-term projections of the tertiary stock. Recently, detailed individual building and building stock models have begun to merge into hybrid methods that might help evaluating the energy demand of a group of buildings, which may contain from dozens to thousands individuals [3]. Our ambition is to represent the tertiary building stock as a group of individual buildings. The first important step is to determine the area of each building. Many building stock models use the area as a key variable for estimating the energy demand. For example in the econometric model NEMS-National Energy Modeling System, the US tertiary building stock is described in its Commercial Demand Module [4]. In NEMS, the floor area is used in many of

International audience

Thanks to their high theoretical efficiency, residential heat pumps (HP) are a promising technology when attempting to reduce the energy consumption of heating in dwellings. Evaluation of their real performances on-field is thus crucial to promote their development and deployment. However, measuring accurately real heating capacity of air-to-air HP is not easy, since measuring air enthalpy and mass flow rate is challenging. A previously developed non-intrusive internal method based on the compressor energy balance has been improved. It can calculate the coefficient of performance (COP) of different HP types, including air-to-air, on field, thanks to real-time measurements, without interfering with normal operation of the system, and without technical data of the specific heat pump. In this study, a complete validation of this method has been led on a test bench, using an air-to-water HP in order to compare the results of the method with the water-side measurements. This internal refrigerant method was tested for various climatic conditions and heating needs, in stationary and dynamic conditions, including starting and defrosting phases. Different faults were simulated to analyse the behaviour of the method in these conditions, including refrigerant undercharging and exchanger fouling. The analysis also extends to identifying which parameters need to be observed to early detect these faults. The method proves to be robust and its uncertainty to remain low, although it varies with the different working phases. The precise knowledge of real-time performances obtained with this method can help to assess the performance impact of faults and thus to improve associated fault detection and diagnostic methods. On a longer-term scale, the comparison of measured field performances and performances obtained via simplified models, such as regulatory models for instance, could give interesting indications to improve these models.

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International audience; Natural ventilation helps to cool buildings in summer without energy consumption, but its application may be restricted by acoustic and glare constraints. Here, a modelling approach integrating different physical aspects was developed and connected to TRNSYS. Different control strategies of glazed openings were defined and simulations were performed with an office room and a detached family house. We find the natural ventilation potential is largely reduced due to acoustic and visual comfort constraints. An acoustic shutter, which facilitates more frequent window opening during occupancy by decreasing outdoor noise transmission, was equally studied in detail with the help of this modelling approach. The acoustic shutter improves the acoustic and thermal comforts for intelligent control strategy and is an attractive solution to enhance the natural ventilation potential under a moderate noisy environment.

The current evaluation of heating and cooling system performances has become a major issue in European buildings sector. A promising method for measuring heat pump performances on-field has been previously developed and published. However, the accuracy of the method is strongly dependent on the evaluation of heat transfer from compressor towards the ambient air. In this paper a developed compressor heat transfer model that couples integral and differential formulations is presented. The model consists of three fundamental steps: thermodynamic analysis of the compression process, detailed thermophysical flow analysis using a CFD software, and finally compressor thermal network analysis consisting of integral equations that describe heat transfer of solid-fluid interfaces. Temperature distribution of the compressor shell is the main output of the model. Internal and external thermal profiles obtained from the numerical model and experimental measurements are compared in one operating condition at two compressor speeds. The RMS errors of external profiles are 3.20 °C and 1.96 °C, at 30 rps and 60 rps, respectively. The model can be used to determine the minimum number of surface temperature sensors and their locations on the compressor shell necessary to measure heat losses on-field. More accurate evaluation of compressor heat losses towards the ambient air will improve the accuracy of the performance measurement method.

International audience; Micro-Combined Heat and Power (µCHP) is a technology allowing to produce distributed electricity (electrical power below 36 kWel). The main advantage of µCHP is to avoid thermal energy losses while producing and distributing electricity in order to use primary energy rationally. The electricity can be consumed locally in the building or in the neighborhood area while thermal energy can be recovered to satisfy space heating (SH) and domestic hot water (DHW) demands. Stirling Engine (SE) is one of the various µCHP technologies that can be integrated in individual or small multi-family residential buildings. The aim of this paper is to study the impact of storage configurations, hydraulic schemes and control strategies on the performance of a µCHP system. This study is carried out on an individual residential building with various electrical, DHW and SH loads. A dynamic model was developed to represent a 1 kWel gas Stirling µCHP system (producing up to 24 kWth thanks to an auxiliary burner) and has been experimentally calibrated and validated. The model and storage, emitter and distribution network models are implemented in DYMOLA/Modelica environment in order to get a dynamic representation of the whole installation coupled to the building. The comparison between the different cases is shown in terms of primary energy consumption and analysis of operating conditions. The results allow to identify the best SE-µCHP designs according to building conditions.

International audience; Description of the District Cooling System Chilled-Water Production Flow Chart Centrifugal Chiller Model

International audience; En Europe, les réglementations de plus en plus contraignantes du point de vue environnemental poussent le secteur du chauffage résidentiel à remplacer les anciennes chaudières à énergie fossile (gaz ou fioul) par des technologies plus performantes, comme les pompes à chaleur (PAC). Des pompes à chaleur air/eau double service peuvent être installées en remplacement de chaudière. Cependant, les performances d’une pompe à chaleur sont très dépendantes du processus d’installation et de la qualité de son exploitation. Dans ce contexte, cette étude vise à évaluer l’impact potentiel d’un mauvais paramétrage d’une PAC double service en termes de confort et de consommation électrique, au travers d’une modélisation sous Modelica. Ceci montre que la phase de paramétrage est effectivement très influente sur les performances du système ; le COP saisonnier, le bon fonctionnement et la durér de vie du système ainsi que le confort des utilisateurs nécessitent que le paramétrage de la machine soit adapté à la maison, aux émetteurs et aux organes de régulation de l’installation.

International audience; RÉSUMÉ. Les outils de simulation sont couramment employés pour évaluer la consommation énergétique d'un bâtiment. Lors du processus de modélisation, des choix doivent être réalisés par l'utilisateur de l'outil, tels que la division du bâtiment en zones thermiques. Le but de ce travail est d'évaluer l'influence du découpage en zones sur les résultats de la simulation thermique dynamique en incluant ou non les flux d'air et les transferts thermiques entre les zones. À cette fin, cinq découpages en zones (modèles de 49 à 11 zones) sont appliqués au même immeuble de bureau. L'impact de la fusion des étages est analysé en considérant différents isolants de plancher et toiture et celui de l'union des orientations est étudié à l'aide de différents taux de surface vitrée. Les résultats des simulations thermiques dynamiques sont comparés en termes de besoins énergétiques (chauffage et refroidissement) ainsi qu'en temps de calcul et de paramétrage du modèle.ABSTRACT. Simulation tools are widely used to assess the energy consumption of a building. In the modeling process, some choices should be made by the simulation tool user such as the division of the building into thermal zones. The aim of this work is to assess the influence of building zoning on the results of the dynamic thermal simulation including or not airflow and thermal transfers between zones. For this purpose, several different building zonings (49-zone to 11-zone models) are applied to the same office building. The impact of merging the floors is analyzed by considering different roof and floor insulations and the impact of merging the orientations is studied by using different glazed surface ratio. The results of the dynamic thermal simulations are compared in terms of energy demand (heating and cooling) and computational and setup times.

International audience; Une solution de micro cogénération à moteur Stirling à gaz est testée sur la plateforme Climatherm à l'INSA de Strasbourg. Ce micro cogénérateur intègre une chaudière auxiliaire montée en série et en aval du moteur Stirling. Un modèle numérique, permettant de simuler les performances énergétiques du moteur Stirling et de la chaudière auxiliaire a été développé et calibré à partir d'essais expérimentaux réalisés au laboratoire. Sur la base de ce modèle, implémenté dans l'environnement TRNSYS, des études d'optimisation ont été réalisées afin de mesurer l'impact de la taille du stockage et des stratégies de régulation sur les performances énergétiques et la pertinence économique de ces systèmes. Les premiers résultats ainsi obtenus montrent que la stratégie de régulation et le montage hydraulique utilisés influent fortement sur les performances du micro cogénérateur.

Simulation tools are widely used to assess the energy consumption of a building. In the modeling process, some choices should be made by the simulation tool user such as the division of the building into thermal zones. The zoning process is user dependent, which results in some difference in energy consumption results and model set-up and computational times. The aim of this work is to assess the influence of building zoning on the results of the dynamic thermal simulation including airflow and thermal transfers between zones For this purpose, several different building zonings are applied to the same office building, and then the results of the dynamic thermal simulations are compared in terms of energy consumption (heating, cooling, and auxiliaries) and computational and set-up times. To assess the impact of thermal zoning, five cases are studied (from the most to the least complex): - 1) *49-zone model* : each zone gathers the premises with the same air handling system, the same occupancy profile, at each floor and building orientation. - 2) *44-zone model* : the premises containing the same air handling system are gathered at every floor, even though their occupancy profile is different. - 3) *26-zone model*: all floors are merged, except for the first and the top floors (under-roof). - 4) *21-zone model* : the first and the under-roof floors are merged with the others if the premises have the same occupancy profile and handling system. - 5) *11-zone model* : the premises with a different orientation but with the same occupancy profile and handling system are gathered. The importance of airflow coupling is evaluated by using the most detailed model (49 zones) and comparing the cases with or without considering air transfer from offices to corridors and toilets (from which air is extracted). Then, to study the impact of thermally connecting juxtaposed zones, the “21-zone model” with and without thermal transfer are compared. Finally, the impact of merging the floors is analyzed by considering different roof and floor insulations and the impact of merging the orientations is studied by using different glazed surface ratio.

International audience; Des travaux de recherche ont été menés afin de tester et modéliser un système de micro cogénération biomasse. Un modèle semi physique de type boîte grise a été créé afin de simuler le comportement dynamique d’un micro cogénérateur biomasse à moteur à vapeur. Celui-ci a été calibré à l’aide d’essais effectués en laboratoire. Ces essais ont permis également d’établir précisément les performances de ce système en régimes permanent et transitoire aux niveaux énergétique et des émissions de polluants.

International audience; The substitution of low-performance gas and fuel boilers by air to water electrical heat pumps is a solution to meet the energy challenge to reduce GHG dwellings emissions. Indeed, most dwelling emissions in Europe are due to heating and DHW generation with fossil fuels. Apart from low carbon emissions, high energy savings are expected from rated performances, but an AWHP may not deliver the expected efficiency because of a bad commissioning. Nowadays, these machines present a high number of parameters – over 40 on average – to be set during the installation, which makes this process very complex. Unfortunately, the parameter setting is a crucial step for the proper operation of the system throughout its life cycle. A non-optimal choice of AWHP parameters may lead to severe performance losses or discomfort. The first part of the paper describes the functions and parameters that the installer must adjust for the commissioning phase. In a second step, the consequences of a non-optimal parameterization of an AWHP are evaluated. This analysis is based on a computer model using Modelica language. The model consists of a heating system, installed in a typical detached dwelling. Simulations are run by pairing the heat pump with the dwelling and the heating system. Simulations show the potential energy savings and the accuracy of indoor air control when control parameters, in particular the heating curve, are adapted to the dwelling and to the heating network. Final results confirm that an optimization of the parameterization of an AWHP makes a significant difference, in both energy savings and indoor air temperature control accuracy.

International audience; Due to the development of energy performance contracting and the needs for peak electric demand reduction, the interest for optimal building control is renewed. In this context, the real time prevision and optimization of building heat demand can help the manager to reduce the energy bill and to propose peak shaving offers. Our study aims to illustrate such heat control strategies on a one floor elementary school. The building is modeled through a second order inverse “grey box” model. The inverse model identified during a short learning period is first validated on its ability to forecast heat load and indoor temperature. Then it is used for optimal control and for that purpose two strategies are proposed. The first one consists in optimizing the night setback period with a constant electricity price. The second one aims to set a varying indoor temperature set point in a context of peak and off peak hours. The results show about 5% off electricity consumption for the first strategy and 4% off electricity bill for the second strategy. For a very cold week it appears that the optimization could lead to an over-consumption to improve the comfort.

International audience; The use of artificial neural networks in the field of building energy management has led to remarkable results over the recent years. In this study, the development of room temperature neural network models, to be used for predictive control of geothermal heat pump systems, is discussed. The training process, including the determination of optimal input data, algorithm and structure, is detailed. The prediction performance of the developed neural network is compared to linear ARX models. Simulated data used for training and validation is generated using the TRNSYS environment. The developed model is then implemented into a predictive controller for geothermal heat pumps systems. Simulation results showed that the predictive controller can provide up to 17% energy savings in comparison with conventional controllers.

International audience; The decrease of heat demands in the low energy buildings requires to reexamine modeling approaches in the building simulation, particularly the dynamic response of the building and its equipments lead to re-examine modeling rules. From a review of air-to-air heat pump models, three types are compared in order to evaluate the ability of each one to predict the energy consumption and power demands. These air-to-air heat pump models coupled to a single zone building are simulated on Modelica. The aim is to underline the advantages and the drawbacks of the different modeling approaches for dynamicsimulationinrespectofthedifferentphenomena to represent.

International audience; One way to predict the behavior of a building is to use an inverse model, identified from energy data measured on site. The inverse models are adaptive, faster to execute and easier to configure than detailed building models. The objective of this study is to select an inverse model suitable to implement heating load shedding. A linear "black box" model (state space model) is compared to a simplified “grey box” physical model. The results show that the selected “grey box” model has the same performance as a black box model for heating load prediction, and is more accurate for predicting indoor temperature and to represent load shedding strategies. Moreover, unlike the "black box", it allows to set up scenarios imposing a limit of heating power.; Une des façons de prévoir le comportement d’un bâtiment est d’utiliser un modèle inverse, construit à partir de données énergétiques mesurées sur site. Les modèles inverses sont adaptatifs, rapides à exécuter et plus faciles à paramétrer que des modèles de bâtiment détaillés. L’objectif de cette étude est de sélectionner un modèle inverse adapté à la mise en place de stratégies de délestage en chauffage. Un modèle linéaire de type « boîte noire » (équations d’état) est comparé à un modèle physique simplifié de type « boîte grise. Les résultats montrent que le modèle « boîte grise » sélectionné a des performances équivalentes au modèle « boîte noire » pour la prévision des besoins de chauffage, et est plus précis pour la prévision de température intérieure et pour représenter les stratégies d’effacement. En outre, contrairement au modèle « boîte noire », il permet de mettre en place des scénarios imposant une limite de puissance de chauffage.