Xu, WenjieSvetozarevic, BratislavDi Natale, LorisHeer, PhilippJones, Colin Neil2024-02-232024-02-232024-02-232024-01-0910.1016/j.apenergy.2023.122493https://infoscience.epfl.ch/handle/20.500.14299/205456WOS:001154992100001We study the problem of tuning the parameters of a room temperature controller to minimize its energy consumption, subject to the constraint that the daily cumulative thermal discomfort of the occupants is below a given threshold. We formulate it as an online constrained black -box optimization problem where, on each day, we observe some relevant environmental context and adaptively select the controller parameters. In this paper, we propose to use a data -driven Primal -Dual Contextual Bayesian Optimization (PDCBO) approach to solve this problem.TechnologyBuilding Thermal ControlController TuningBayesian OptimizationContextual ModelPrimal-Dual Methodtext::journal::journal article::research article