Building Indoor Thermal Environment Control Strategy Considering Thermal Comfort And Energy Saving

With the continuous development of the economy and improvement of living standards,people have higher requirements on the comfort of indoor environments in buildings.On the other hand,building systems consume a large amount of energy in an attempt to create a comfortable indoor environment,which is also an important reason for the annual increase in building energy consumption.In this context,introducing advanced control ideas to study control schemes for indoor environments has important practical significance and application value.Considering both thermal comfort and energy-saving requirements,this thesis focuses on the research of indoor thermal environment control strategies.Main work includes the following aspects:(1)An indoor thermal environment control method is presented based on the predicted mean vote(PMV)inverse model.Firstly,based on the classical PMV model,the inverse PMV model is proposed as an indoor temperature set point estimator.Secondly,extreme learning machine is used to train the inverse PMV model.Then,the trained inverse model and pulse width modulation based PID(PWM-PID)algorithm are used to realize the temperature set point tracking control.Finally,the feasibility and effectiveness of the proposed control method are verified by TRNSYS/MATLAB co-simulation.(2)A model prediction-based optimization control strategy is investigated for indoor thermal environment.Based on the principles of model predictive control,a model predictionbased optimization control strategy incorporating genetic algorithm(GA)is proposed for optimizing the indoor thermal environment.Considering the challenges in establishing accurate mathematical models for variable air volume air conditioning systems,an indoor environment simulation model based on TRNSYS is utilized as the predictive model.Simulation results demonstrate that,compared with conventional fixed setpoint control(26°C),the proposed strategy can achieve approximately 7.6% reduction in energy consumption of the air conditioning system while ensuring the thermal comfort of occupants.(3)An experimental scheme is implemented for optimizing the indoor multi-zone thermal environment.Firstly,considering the spatial distribution characteristics of temperature fields in large spaces,the indoor environment is divided into multiple zones.Secondly,a time-varying linear model is employed to estimate the steady-state temperatures of different zones under varying setpoints.Then,a suitable objective function is defined,and the GA is employed to achieve rolling optimization of temperature setpoints.Experimental results demonstrate that this control method can effectively balance occupants’ average thermal comfort and energy-saving requirements of the air conditioning system.