Model Predictive Control Of Air Source Heat Pump

The energy consumed by buildings constitutes more than 40% of China’s total social energy consumption,and 50% of that energy is attributed to Heating,Ventilation and Air Conditioning(HVAC)usage.China’s current energy consumption structure,however,relies heavily on primary energy sources such as coal,oil,and natural gas,which leads to an increase in carbon emissions and exacerbates environmental concerns.To mitigate these challenges,it is crucial to implement cost-effective,highly efficient,and environmentally friendly energy-saving devices,while reducing the reliance on fossil fuels.Air source heat pumps(ASHPs)represent one such device,which utilize low electrical energy to drive an inverse Carnot cycle,further to extract low-grade heat energy and to convert it into a larger amount of heat or cooling capacity.As the initial heat energy comes from the air,the electrical energy consumed by the heat pump is not directly involved in the heating process,thus energy efficiency is enhanced,compared to electric heating.Nevertheless,ASHPs are non-linear,strongly coupled,and possess significant inertia,making it difficult to achieve optimal dynamic performance and energy efficiency when using conventional proportional-integral-derivative(PID)control methods.In this study,we propose an ASHP model predictive control(MPC)strategy that utilizes predictive models and rolling optimization to calculate control variables that satisfy optimization targets.In this approach the issue of large time lags is addressed,the performance of ASHPs is enhanced,and energy efficiency is improved while heating requirements are met.In this study a non-linear model predictive control(NLMPC)strategy is proposed for air source heat pump(ASHP)water heating systems with the aim of meeting heating demands,which improves system performance,and reduces energy consumption.The study commences with an analysis of the principles of thermodynamics,fluid mechanics,and the ideal gas equation of state to characterize the dynamic and fluid features of the compressor,as well as the heat transfer features of the evaporator,condenser,and water tank.Subsequently,a dynamic mathematical model of the ASHP water heating system is developed and validated using actual operational data.Based on the control target of the ASHP water heating system,the optimization target is constructed to improve the coefficient of performance(COP)and to shorten the system regulation time.Given the non-linear nature of ASHP,the sequential quadratic programming(SQP)method is employed to solve the optimal sequence of control variables in the predicted horizon to achieve rolling optimization.To validate the proposed control strategy,an ASHP heating water experimental system is constructed,since the heat pump compressor under study lacks Hall sensors,and the corresponding control system is developed based on the TMS320F28335 chip.The simulation and experimental results clearly demonstrate the effectiveness of the proposed NLMPC strategy in improving the heating rate and COP of ASHP water heating systems.Compared with conventional PI and fuzzy PI control strategies,the NLMPC strategy achieves significant improvements in both heating rate and COP,with increases of up to 13.7%and 18.5% respectively in simulation experiments,and up to 15.7% and 14.6% respectively in the experimental system.