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Simulation-aided development of automated solar shading control strategies using performance mapping and statistical classification

Samuel de Vries, Roel Loonen, Jlm Jan Hensen

2021Journal of Building Performance Simulation18 citationsDOIOpen Access PDF

Abstract

This paper presents a structured, generically applicable, method for using building performance simulation to aid the development of comfort-driven solar shading controls by mapping predicted occupant comfort conditions to sensor measurements. The method uses confusion matrices as a statistical classification approach to facilitate (i) selection of sensor deployment strategies that offer beneficial trade-offs considering multiple performance aspects and (ii) identification of control algorithms that optimise comfort conditions using non-ideal sensors. The support method requires relatively little effort from a developer, only a small number of simulations and fits well within the current practice of shading control development. The method is tested using a sun-tracking control strategy for indoor roller blinds as a case study, which demonstrates that the method can identify high-performance solutions. Finally, generally applicable features of the method are extrapolated from the case study, and alternative applications and the method's limitations are discussed.

Topics & Concepts

Software deploymentIdentification (biology)ConfusionComputer scienceShadingControl (management)Selection (genetic algorithm)Control engineeringSimulationEngineeringData miningMachine learningArtificial intelligencePsychologyOperating systemBiologyPsychoanalysisBotanyComputer graphics (images)Building Energy and Comfort OptimizationWind and Air Flow Studies
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