| At present,the energy consumption of buildings in my country accounts for 30%to 40% of the total energy consumption of the whole society,and the energy consumption of heating accounts for 21% of the energy consumption of buildings.With the development of China’s urbanization,China’s urbanization rate will be as high as 70% in 10 years,and my country’s energy consumption for heating will be twice the current level.In the current heating system,there are problems such as uneven cooling and heating,and the heating adjustment time is too long,resulting in a large amount of energy being wasted.In terms of control strategy,most of the central heating systems in my country are still in the stage of semi-manual and semi-automatic control,the use of automatic control equipment is low,and the regulation efficiency is not high.Therefore,the introduction of advanced control strategies into the heating control system is an important research direction in the field of building energy conservation in the future.This paper studies the heating control strategy,and proposes a heating control strategy based on Adaptive Model Predictive Control(Adaptive Model Predictive Control).Use the data collected at the heat exchange station and the weather website combined with the subspace algorithm to build the thermal dynamic response model,energy consumption analysis model and basic prediction model required for the simulation experiment.Then,three control systems based on different strategies were designed and built on the SIMULINK platform,namely the adaptive MPC control system,the basic MPC control system and the PID control system.Among them,an update module was built for the design of the adaptive MPC control system.To update the forecast model periodically,and analyze and tune the design parameters of the three controllers.Then compare the control performance of the above three control systems in terms of room temperature and energy consumption through simulation.It is found that the control system adopting the adaptive MPC control strategy has a greater improvement than the basic MPC control system and PID control system in terms of indoor temperature control and energy saving.Compared with the original heat exchange station control strategy,the adaptive MPC control strategy reduces the control deviation of indoor temperature by 67.5% and energy consumption by 20.3%.Compared with the basic MPC,the adaptive MPC has a 27.7% reduction in indoor temperature deviation and a 6.7% reduction in energy consumption.It further compares the response speed of the three control strategies in the control process,as well as the performance against severe weather.The simulation results show that adaptive MPC is still better than the other two control strategies in terms of control speed and response to extreme weather.On the basis of simulation analysis,experiment analysis is carried out to compare the control effects of adaptive MPC and ordinary MPC in indoor temperature control and energy consumption control.For this reason,a simple transformation of the laboratory was carried out,and a dynamically changing laboratory compartment temperature was designed to simulate the real outdoor temperature.Design the real-time transmission module to connect with the laboratory control platform for real-time control.Experiments show that compared with ordinary MPC,adaptive MPC reduces the deviation of indoor temperature control by 26.3% and energy consumption by 5.8%.It further verified the feasibility of adaptive MPC in the field of heating and energy saving.In summary,adaptive MPC has a better control effect in heating control than traditional PID control and basic MPC control.In the field of energy-saving control in the future,the combination of adaptive MPC and other control technologies with advanced optimization algorithms is worthy of further research by researchers. |
