Adaptive Personalized Shading Control Strategies To Maximize Occupant Satisfaction While Reducing Lighting Energy Use In Buildings

Key

33685

Conference Year

2016

Authors

Jie Xiong, Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana USA / Center for High Performance Buildings, Ray W. Herrick Laboratories, Purdue University, West Lafayette, Indiana USAFollow
Seungjae LeeFollow
Athanasios TzempelikosFollow
Panagiota KaravaFollow

Keywords

adaptive control, shading control, personalized control, visual comfort, probabilistic preference model

Abstract

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.