English

In this article, the main research goal is to present a model for rapid assessment of specific heating energy consumption of residential buildings. In the first part of this research paper the main inputs that could influence the building heating demand are identified.The next step in the development of the prediction model was to conduct dynamic simulations with different combinations of the inputs and to obtain a database of results.  With this database, a multiple regression was applied and a simple (3 inputs) and accurate (R2=0.987) model was obtained.  

This paper presents the first step modelling process of a smart building  in order to ensure better energy management and human comfort in buildings. It consists on combining physical models and experimental measurements in order to have more adapted models for virtual simulation and optimal control. Advantages and difficulties related to this process will be detailed through a defined use case of a smart building: PREDIS.   The paper starts, by introducing the studied building and its different components: HVAC system and thermal envelope.

Increasing concern about building sector energy consumption and the simultaneous need for an acceptable thermal environment makes it necessary to estimate in advance what effect different thermal factors will have on occupants. So far most human thermal comfort models are based on estimates assuming steady-state conditions. However, this often leads to underestimations of local cold or hot surfaces. These kinds of models does not take into account variable conditions.

To study the impact variations in input on output vari-ation (Sobol index) of building model, a stochastic model (time series) of variables is introduced. To build the time series we used data measured in a building for each hour for a duration of one month.
The external temperature does not appear directly in the model but affects all the input. So after model it as Auto-Regressive process we propose to model input, for example the heating flux, by an ARMAX process.

For the purpose of revitalizing traditional architecture, we considered the characteristics of a traditional architecture cluster with regard to cross ventilation, and from an environmental engineering point of view, we proposed techniques to improve the surrounding environment. In this report we make use of and improve the urban area model used in a prior report, as well as use CFD to take into account the effects of surrounding topography. To improve the urban area model, we make detailed computations of the wind pressure coefficient distribution.

Spaces with high heat generation such as telecommunication base stations (TBS) increase sharply recently. Huge energy is consumed for air-conditioning because of large indoor heat rejection and year round cooling in these spaces. Thermosyphon heat exchanger is an appropriate cooling technique for TBS, which can make full use of natural outdoor cooling resources without much electrisity consumption.

The Birmingham Zero Carbon House is a retrofitted Victorian house that has achieved carbon negative performance.! Future predictions of temperatures are showing an increase in Cooling Degree Days (CCD), even under a low carbon emissions scenario.! This paper aims to investigate the human behaviour effect on maintaining indoor thermal comfort in future weather, in various models of cooling in the Zero Carbon House.

The decrease of heat demand in low energy build-ings, very sensitive to solar and internal gains, and the development of new HVAC systems call for a reexam-ination of the usual modeling approaches in building simulation. A focus is brought on an air-to-water heat pump plugged to a radiant heating floor (RHF) by a hydraulic loop installed in a typical low energy dwelling. Using a RADTEST evaluated Modelica slab model, several floor thermal masses under four differ-ent control strategies are compared to determine their impact on HVAC system performances.