Développement et évaluation de stratégies de contrôle avancées des technologies de fenêtres intelligentes

Authors: Dussault, Jean-Michel
Advisor: Gosselin, Louis
Abstract: Smart windows present a huge potential in terms of energy consumption reduction in buildings while also offering the possibility to assure occupants’ visual comfort. Since the early nineties, research in the field of smart windows gains a lot of interest on both the technologies and the controls that could be applied on such technologies to manage more efficiently solar gains passing through these windows. Many different well-known entities such as the Lawrence Berkeley National Laboratory invested efforts in this field and demonstrated the great complexity related to the thorough evaluation of smart window performances. Given its capacity to manage solar radiation, it makes sense to benefit from solar radiation measurements to control efficiently such technology. However, the costs and other technical related limitations reduce the potential to use readily available solar sensors for smart window control. Moreover, general knowledge is still limited regarding the conditions leading to optimal control decisions of smart windows. The main objective of this thesis was to gain a better understanding of how electrochromic windows could lead to improved performances in terms of energy consumption and thermal comfort. First, a new design of low cost solar sensor is proposed. The sensor uses the difference in temperature of white and black surfaces to estimate the solar heat flux through building openings. Results of solar radiation measurements are obtained through a correlation based on a 1D thermal model of the sensor. Two designs of the sensor are presented and obtained results compared with solar measurements of a high precision pyranometer. It was shown that the new sensors present sufficient accuracy for smart window control applications. Finally, it was observed that ideal sensors calibration period should consider at least half a day of measurements, including solar peak time, and should be done during clear sky conditions. Then, the impact of the applied control strategy on the overall energy consumption is investigated. The hour-by-hour state of the smart windows required to minimize overall energy consumption while respecting constraints related to comfort is determined through an optimization strategy based on genetic algorithms. This quasi-optimal control is compared to other approaches that could be applied in real-time applications, i.e. rule-based controls and a model predictive control. The impacts of thermal mass and installed light power density are also analyzed. Results show that the four control strategies under study presented similar energy consumption with differences in total energy consumption ranging from 4% to 10%. This study illustrates that simpler control strategies can also lead to satisfying results. Finally, a sensitivity analysis based on a large number of different combinations of design parameters is performed. Results related to energy and for a total of 7680 scenarios were obtained and used in this analysis considering the Main effect of the building parameters. The relative influence of the parameters is presented and the different designs improving the outputs are determined. Results have shown that the greatest total energy savings considering EC windows are for warmer climates with higher solar radiation exposures. The presence of an EC window mostly influences the cooling peak load and acts as an alternative solution to thermal mass from the perspective of peak reductions. While the choice of the specific window control strategy is having a limited impact on the energy savings and peak load reductions, the analysis revealed that this parameter has a larger impact on the visual comfort. The use of smart window does not appear to greatly influence the thermal comfort within the zone.
Document Type: Thèse de doctorat
Issue Date: 2017
Open Access Date: 24 April 2018
Permalink: http://hdl.handle.net/20.500.11794/27726
Grantor: Université Laval
Collection:Thèses et mémoires

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