Evaluation of Efficient, Energy-Saving, and Environmentally Friendly Transcritical CO2 Heat Pump Technology Based on Deep Learning Algorithms

With the continuous development of society and economy, energy consumption is increasing, and environmental pollution is becoming increasingly serious. Energy conservation and emission reduction have become an important task of environmental protection work. In traditional energy consumption reduction measures, the main starting point is to improve energy utilization efficiency. At present, for systems with high requirements for building water conservation and reducing boiler combustion steam emissions, it is difficult to use deep learning algorithms for improvement research, which has the characteristics of high computational cost and low efficiency. This article modeled and analyzed the heat pump system based on neural networks and compared the simulation results of the model with experiments using MATLAB software to verify its effectiveness and accuracy. The verification results showed that the energy-saving efficiency of the system reached over 92%.