Prediction Model And Application Of Lighting And Shading Control Behavior In Buildings

Lighting control in office buildings is driven by occupant’s demand for indoor light environment.The control behavior not only has a direct impact on occupants’ visual comfort,but also relates with the building lighting energy consumption.Current studies often consider lighting and shading as two independent parts,without considering the relationship between them,ignoring the linkage between lighting and shading behavior,and ignoring the diversity and difference between people.In this regard,this paper proposed a prediction model that can accurately describe the lighting and shading linkage control behavior by fully considering the difference and diversity of occupants.The light environment preferences and the usage habits of lighting and shading system of occupants was firstly investigated and classified by means of questionnaire.Markov model and log-logistic survival model were introduced to quantitatively describe the probability distribution of various shading and lighting control behaviors.On this basis,combined with the indoor work plane illumination forecast,the behavior of occupant’s lighting and shading control can be predicted.By comparing the four models considering or not considering the diversity and coupling effect,it is found that the proposed coupling prediction models show better performance,the maximum error rate is only 13.04%for the lighting energy consumption prediction.In order to verify the above model,this study takes an office building in wuhan as a case to verify the method with measured energy consumption and behavior data.By comparing the four models with or without considering the diversity and linkage effect,it is found that the proposed linkage prediction model has better prediction performance,and the maximum error rate for the prediction of lighting energy consumption is only 13.04%.On the basis of this linkage prediction model,this paper proposes an adaptive lighting-shading control strategy,and by using Simulink to build the corresponding automatic control module.Compares with other forms of commonly used control existing and found that the proposed adaptive control strategy than other existing several kind of control strategy and energy saving rate can reach 39.25%to 69.07%.