adaptive control, shading control, personalized control, visual comfort, probabilistic preference model
In this study, a personalized shading control framework is developed to maximize occupant satisfaction while minimizing lighting energy use using a multi-objective optimization scheme. A personalized satisfaction model was developed based on specially-designed experiments in private offices, to quantify the occupant satisfaction level with motorized roller shades by predicting the override probability of occupants considering different variables. Then, a multi-objective optimization algorithm was constructed, considering the shading override probability and predicted lighting energy use as objectives, where the occupants are the decision makers in the final balancing between their personalized comfort limits and energy use considerations. The developed method serves as a prototype study on adaptive shading controls with learned personalized comfort profiles and parallel energy use considerations.