Etude de stratégies de gestion en temps réel pour des bâtiments énergétiquement performants

Abstract : To reach the objectives of reducing the energy consumption of buildings and decreasing their impact on the electrical grid, it is necessary to elaborate real time control strategies in view of smart grids and demand response programs. In this context, this thesis aims at developing real time control strategies for electric load shifting in energy efficient buildings. First, these strategies require appropriate models regarding weather forecast, occupants' behaviour and building energy simulation. Then, in order to improve the reliability of building energy simulation and to ensure optimal control of facilities, a calibration process of the model based on on-site measurements is recommended. In this way a new methodology was developed , based on a screening technique and a bayesian inference method (approximate bayesian computation). Finally, two optimisation techniques were studied to develop real time control strategies. The first technique was based on offline optimisation methods. The principle is to approximate optimisation results (and more specifically model based predictive controllers results) and to extract simplified control strategies. The second method consisted in using model predictive control and, more precisely, in solving in real time a state and input constrained optimal control problem by interior penalty methods. An actual experimental passive house being part of the INCAS platform built by the National Solar Energy Institute (INES) was used to study by numerical simulation the different strategies developed.
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Maxime Robillart. Etude de stratégies de gestion en temps réel pour des bâtiments énergétiquement performants. Ingénierie de l'environnement. Ecole Nationale Supérieure des Mines de Paris, 2015. Français. ⟨NNT : 2015ENMP0042⟩. ⟨tel-01299525⟩

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