Research On Optimization Of The Parameters And Operation Strategy Of Ground Source Heat Pump Air-conditioning System In Hot Summer And Cold Winter Area

Ground source heat pump(GSHP)air-conditioning systems have good energy efficiency performance and low operating costs while relatively high initial investment and complex system structure also limiting its further promotion and application.The normal GSHP system parameter design and optimization methods rarely consider the interaction of multiple variables.Traditional air-conditioning control methods and operating strategies often ignore the impact of system time lag and load dynamic changes during the operation.This dissertation conducts reseach on parameter design optimization and control operation optimization of GSHP system in hot summer and cold winter areas.Research on parameters design optimization of GSHP system in hot summer and cold winter area.This dissertation first analyzed the energy efficiency performance of the GSHP system under partial load conditions in winter and summer through experiments,and explored the relationship between unit cooling/heating,power consumption and COP with the change of the heat pump on-off ratio.With the increase of the times of on-off ratio of heat pump,the COP can be reduced by up to 19.8%.The influence of heat pump outlet water temperature on the system energy consumption and indoor temperature and humidity under the full load condition of the system in summer is analyzed.The COP of heat pump increased as the heat pump outlet temperature increases and it can increase by up to 15.8%.The effect of the eight variables,including the types of pipes,heat pump outlet water temperature,etc,on energy efficiency,economy,and soil heat balance of the system had been analyzed by simulation.The utility function(UF)and the average weight distribution method are applied to the parameter estimation model to determine the optimal parameter combination.The response surface method(RSM)model was then used to analyze theirs influence on different objective functions of the system.Then the RSM model was coupled with the NSGA-II multi-objective optimization algorithm to find the optimum solutions.The system was comprehensively evaluated in terms of energy efficiency ratio,operating cost,and indoor thermal comfort.According to the Analytic Hierarchy Process(AHP),the system was optimized and two final optimized working conditions were determined.Compared with the reference condition,the seasonal performance factors(SPF)of the two optimized conditions increased by 4.2% and 4.1%,respectively;the operating costs were respectively reduced by 17.8% and 13.0% while ensuring the comfort.Research on optimization of control and operation of GSHP system in hot summer and cold winter area.An hourly load forecasting was proposed in this dissertation.The model of SVM,BPNN,LSTM and hybrid LSTM-BPNN models were selected for prediction comparison and evaluation.Then the LSTM-BPNN model and the BPNN model were coupled to obtain the cooling load forecat model(LSTM-BPNN+BPNN),which had the best predictive effect.Combining the hourly load forecasting model and the conventional daily load forecasting model based on LSTM network,a parallel load forecasting control strategy and an improved laboratory GSHP-energy storage system were proposed.The system could realize the dual energy-saving on both the energy supply side and the energy storage side.The results show that compared with the conventional energy-storage system,the improved GSHP system could achieve 11.5% and 8.7% reduction in energy-consumption,and had 7.5% and 13.1% reduction in operating costs in summer and winter,respectively.Compared with traditional GSHP systems,the improved system had similar energy consumption while reducing operating costs by 21.3% and 25.1% in summer and winter.The research results of this paper can provide references for the related research,design and operation of GSHP systems.