Development of a configurable model for temperature distribution estimation in multifamily houses with limited amount of sensors
Sammanfattning: The biggest environmental challenge of the current century is limiting the CO2 emissions in order to contrast the global warming and keep the temperature increase below 2.0K with respect to the pre-industrial age. For succeeding in this goal, significant changes are required in all sectors, including the energy one. For our society to reach the goal it is important to act not just on the production side of the energy, but also on the utilization one. In the last decades, the economic well-being drove people to a continuous search for comfort. In the building sector this behavior brought to the consumption of huge amounts of energy. Nowadays, the final target of most of the companies working in this sector is therefore to guarantee the thermal comfort desired by the inhabitants while minimizing the energy consumption. The parameter that most affects people thermal sensation is the perceived temperature. Several models have been already created with the purpose of estimating the temperature value inside a certain environment, but these are generally characterized by two main limitations. First of all the focus is on a single room or apartment and not on the building as a whole. Secondly the model is specific and cannot be applied to other structures. The purpose of the thesis is to elaborate a general model able to estimate the temperature distribution inside any Multifamily House (MFH). The reasoning behind the chosen typology is the significant share that it has in the building market. This model should be reliable enough and, at the same time, characterized by short computational time. Building this model could be the first step for being able in the future to operate a real time control on the thermal indoor conditions. While developing the model particular attention has been given to the impact of climatic conditions on the indoor temperature.The contribution of sun and wind has been considered at different levels of detail. On the basis of the calculation approach utilized for them, different configurations have been identified. Each of them, in addition, has been analyzed with and without optimization process of the space heating power distribution. The RMSE value of the different configurations has been utilized during the comparison as a measure of the model accuracy. From the analysis the best model resulted to be the not-optimized one considering the solar radiation dependent on the incidence angle and with negligible wind effect. The main strong characteristic of the model is its configurability: it can adapt to the geometry, orientation and apartments disposition of any MFH. The model has also some limitations such as the fact that it can be used just for buildings provided with mechanical ventilation and not one without such as green or passive houses. In addition, the model does neglect empty apartments and does not consider the heat and mass transfer between adjacent flats. The report has been developed as follows. The first chapter is an introduction to the thesis. The background provides insights about the actual situation regarding the temperature measurements inside a building. The addressed problem is reported together with the delimitation regarding the typology of building taken into consideration. The methodology utilized for developing the model closes the first chapter. The second one reports the state of art concerning the temperature distribution models. The third chapter contains the input data required by the model, the description of the different heat fluxes involved in it and how they are related to the building geometry and to the apartments disposition. The equation utilized for the temperature calculation is then analyzed. The chapter ends with the description of the steps for obtaining a 3D temperature visualization and with an overview on the whole process for evaluating the temperature distribution. In the chapter four are reported the results obtained with the different models and configurations. These are further analyzed, compared and discussed in the fifth chapter, in which is the best model is also identified. The thesis ends with the a glimpse on possible future work and a general conclusion about the developed model.
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