Research On Pv-sahp Start-up And Variable Capacity Control Method Based On ANN System Performance Prediction

Photovoltaic solar-assisted heat pump(PV-SAHP)performs photovoltaic power generation while providing domestic hot water to the user by utilizing solar radiation resources.Solar radiation and temperature have a great influence on the operating characteristics of the system.It is possible to adjust the control strategy according to the needs of the user and adjust the solar irradiance and environmental temperature in time,which is of great significance for the efficient operation of the system.In this paper,the influence of system startup and frequency conversion control methods on system operation characteristics under control strategy is studied,and the optimal control method is sought.Based on the lumped parameter partition calculation method,the dynamic mathematical model of PV-SAHP system is established,and the system loop simulation calculation program is written to provide system power consumption,power generation and heat generation simulation data for the simulation analysis of the system operation process and the establishment of the neural network predictive control model.The variable frequency PV-SAHP water heater system based on PLC,frequency converter and R22 refrigerant was built.The experimental verification was carried out under different weather conditions and compressor operating frequency to verify the accuracy of the system simulation cycle model.The platform also provided to the comprehensive control strategy experiments.In the best environmental conditions during the day,the simulation program was used to simulate the actual impact of system compressor frequency variation on system performance under the annual environmental conditions in Nanjing.The results show that the reduction of compressor frequency from summer to winter has gradually reduced the influence of system heating performance,but the overall system heating performance still increases with the decrease of compressor frequency,the system’s heating capacity is limited by the environmental conditions and the compressor’s adjustment range;the total power generation of the system during the day is minimally affected by the compressor frequency,so the heating performance can be used as the main evaluation index of the system.According to the conclusion of the simulation analysis,combined with the definition of the actual available heating period of the system,a new system comprehensive control principle is established: when the whole process is running at the lowest compressor frequency and the task can be completed within the actual available heating period,select the best time of environmental conditions to improve overall system performance;otherwise,according to the change of environmental conditions and the adjustment capacity of the compressor,a real-time frequency conversion control strategy capable of coping with the constant change of the heating time is established to ensure that the average operating frequency of the system compressor is the lowest when the total heating time is not exceeded.According to the different heating conditions in the control principle,combined with the hourly weather forecast,the corresponding control system startup time and variable capacity operation control strategy are formulated.Among them,the optimal starting time control strategy calculates the optimal starting time in the actual heating period through the system performance prediction model,and the control system starts at the lowest operating frequency on time;the real-time frequency conversion control strategy is based on the change and compression mechanism of the weather state during the heating period.The heat capacity distributes the heat of the different time periods,and the frequency prediction model is called to control the operating frequency of the compressor in real time according to the heat target in each time period.The system performance prediction model based on BP neural network algorithm and the real-time compressor frequency prediction model are trained based on system simulation data of all environmental conditions and compressor frequency variation values.According to the control strategy,the optimal starting time prediction control program and real-time frequency conversion control program based on the experimental platform control system are developed respectively.The control strategies of PV-SAHP system are verified experimentally under different weather conditions.The experimental results are compared with the simulation results of the traditional system startup and variable frequency control methods.The results show that the integrated control strategy can reach 3.53 in the case of poor environmental conditions,and 6.93 in the case of better environmental conditions.The overall energy output factor increase rate of the system in various irregular environmental conditions is 5.37~37.39%,and the heating time can be precisely controlled.