Méthode d'évaluation des performances annuelles d'un régulateur prédictif de PAC géothermiques sur banc d'essai semi-virtuel

Abstract : With the recent development of innovative controllers for the building, there is a need to develop a testing method that is fast, reproducible and realistic. The method developed in this study aims to estimate the annual performance of ground source heat pump (GSHP) controllers in only a few days of test. Based on emulation techniques already used for GSHP and solar combined systems, the test immerses the controller and a real GSHP in a simulated environement that is calibrated with in-situ data. Each day of test represents a typical day of the month. The development of the method consists in determining the optimal typical days that ensure an accurate estimation of annual performance. The method is then experimentally tested on the semi-virtual test bench for the comparison of a predictive controller and a conventionnal controller over an entire heating season.To develop the method, a predictive controller for GSHP is elaborated. The controller is based on artificial neural networks used for the prediction of weather data and indoor temperature. A new module for the prediction of floor heating and boreholes fluid temperatures is also proposed. The predictive controller is tested by simulation over a heating season for various climates and types of single family house. According to the reference case, the energy savings vary between 6% and 15%.
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Tristan Salque. Méthode d'évaluation des performances annuelles d'un régulateur prédictif de PAC géothermiques sur banc d'essai semi-virtuel. Energie électrique. Ecole Nationale Supérieure des Mines de Paris, 2013. Français. ⟨NNT : 2013ENMP0095⟩. ⟨tel-01144416⟩

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