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Study On Operation Optimization Strategy Of Transmission And Distribution System For Ground-source Heat Pump Based On Featur Recognition

Posted on:2020-05-03Degree:MasterType:Thesis
Country:ChinaCandidate:Z H FengFull Text:PDF
GTID:2392330620956056Subject:Heating, Gas Supply, Ventilation and Air Conditioning Engineering
Abstract/Summary:PDF Full Text Request
The ground source heat pump air conditioning system has been rapidly developed in the field of HVAC due to its remarkable energy saving and environmental protection advantages.However,due to the selection of the maximum load during the design phase,the ground source heat pump air conditioning system is under partial load conditions for a long time in the actual operation.The operation of the air conditioning system designed to achieve the best performance of the system under rated load is difficult to operate efficiently under partial load.The transmission and distribution system has a higher proportion of energy consumption under partial load,and there is potential for further optimization.In this paper,the feature recognition method was used to establish the ground source heat pump air conditioning system simulation model.Based on the simulation model,the transmission and distribution system operation optimization strategy was studied,and the transmission and distribution system optimization strategy was applied to optimize the overall operation to realize the optimal operation of the existing building ground source heat pump air conditioning system.Main tasks as follows:(1)The simulation model of ground source heat pump air conditioning system was established based on feature recognition method.For a prefabricated ground source heat pump air conditioning system,the unknown structural parameters of each component are aggregated as characteristic parameters,and a small amount of operational data was measured to solve the characteristic parameters,and a simulation model of ground source heat pump air conditioning system based on feature recognition was established.The measured data was compared with the simulation results to verify the accuracy of the model.The results showed that the air conditioning system simulation model based on feature recognition has high precision and can be used to study the optimal operation strategy of air conditioning system.(2)An optimization operation strategy of transmission and distribution system based on feature recognition simulation model was proposed.Based on the feature recognition simulation model,the characteristics of the pipe network and pump in the transmission and distribution system when multiple pumps are connected in parallel were studied.The operation law of the parallel source pump on the ground source side and the air conditioner side under different frequency conversion combinations was summarized,and the ground source side and the air conditioning side were obtained.The optimal parallel frequency conversion strategy of the transmission and distribution system in different flow ranges proposed an optimal operation strategy suitable for the actual ground source heat pump transmission and distribution system.(3)Based on the optimized operation strategy of the transmission and distribution system,the model search method was used to optimize the ground source heat pump air conditioning system.Aiming at the optimal system efficiency,the model search algorithm was introduced to optimize the ground source heat pump air conditioning system,and the variation law of the optimal values of various operating parameters under different load rates was discussed.Comparing the global optimization results of the air conditioning system with the optimizedoperation strategy of the transmission and distribution system and the optimized operation strategy of the transmission and distribution system,the results showed that the energy saving rate of the former was 8% to 15% higher than the latter.
Keywords/Search Tags:ground source heat pump, feature recognition, part load, transmission and distribution system, operation optimization
PDF Full Text Request
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