Thermal Environment Control For Intelligent Constant Comfort Building

With the development of society and improvement of living standard, people take more and more request to the comfort of indoor environment, indoor temperature variations will directly affect the comfort of indoor environment. In order to make indoor environment in steady state when people enter room and save energy consumption in a maximum way. On the basis of Markov Theory, this paper combines with actual situation to improve the theory and method, predict indoor temperature through improved metabolic unbiased gray Markov Theory and Method,and the prediction result is applied to the prediction of later indoor air condition starting time.According to measured data, predict indoor temperature, the maximum mean absolute error between prediction results and actual results of four measured rooms is 0.19?,compared with around 30 ? temperature of indoor, above error is negligible, the analysis shows that the prediction method is accurate.In order to get the best time to turning on air condition, simple variable method is adopted to analyze influence factor of indoor lag time, the result shows that fixed impact factor, indoor temperature during air condition on, outdoor temperature during air condition off are proportional to lag time, air condition setting temperature during air condition on is inversely proportional to lag time. On the basis of above relationship, construct the prediction algorithm of lag time and turn on time of air condition.Through set object time to stabilize the temperature in measured room,according to the object time, calculate air condition starting time, compared actual stability time and planned time of four measured time, the result shows the errors are all less than 10 minutes, and in accepted deviation range.By this research, the prediction method of indoor temperature and computational method of air condition lag time are gotten, based on this to get the prediction algorithm of the best time to start indoor air condition. It's expected that the research method and the conclusion adopted in this paper can provide a reference forfuture indoor thermal environment research.