Research On Ground Source Heat Pump Optimization System Based On LVQ Neural Network

Ground source heat pump technology is a heating and cooling air conditioning system.It uses shallow geothermal resources on the Earth’s surface as a source of heat and cold for energy conversion.It is almost independent of geographical and resource constraints and has a wide range of applications.The ground source heat pump system is a general term,and the groundwater source heat pump system is one of them,and it is used more and more in life,and it has also received much attention.The research on the groundwater source heat pump system and its development direction are summarized by consulting relevant literature.Firstly,the groundwater source heat pump system in a building in Tangshan City is studied to monitor the summer work conditions,collect data at the same time,analyze the factors affecting the energy efficiency of the system,and then calculate the energy efficiency ratio to analyze whether the system is fully energy-efficient.Claim.Then,the energy efficiency ratio is divided into levels,and the LVQ neural network is established based on the divided results and the data obtained by the test.The LVQ neural network energy efficiency ratio prediction model was established for the system.The collected data was divided into two parts.The first 40 groups were used as network training samples,and the last 20 groups were used as test samples.The EER level is simulated by MATLAB programming.Finally,the results of LVQ neural network and BP neural network are compared.The results show that LVQ neural network can be applied to the EER level prediction of groundwater source heat pump system.Compared with BP neural network,LVQ neural network saves time.The accuracy is improved and the extrapolation ability is strong.However,the groundwater source heat pump system of the building is insufficient in terms of energy saving.Optimize for situations that do not meet the requirements in the forecast results.Figure25,Table8,Reference 56...