Thermal energy storage technology and its application in power data remote transmission

The author proposes a phase change heat storage component combined with the light wall interior to improve the heat storage performance. Numerical modelling of the composite wall was performed using the finite element program COMSOL connected to Multiphysics simulation, and its accuracy was verified. In order to optimize the use of phase change data and the benefit of phase change temperature, the phase change of the heating device was carried out, and the difference in the development efficiency of the thermal storage performance of the two types of light walls was obtained from the ribs in the thermal phase phase exchanger compared. The results show that the long and thin fins adjust the temperature and flow field changes of the paraffin to the corresponding fin gap and improve the heat transfer rate, 44.8 and 26.3, respectively, the aerated concrete combined wall heat storage and heat release time, added short ribs known need, and the connected wall delay time is not affected by external heat. The mature thermal insulation and thermal insulation time of the polystyrene board composite wall were shortened by 20.8 and 52.9, respectively. Ribs are able to improve heating efficiency and retain heat in the broken walls of polystyrene panels. The author?s research can provide a rationale for the design and use of phase change thermal storage.

Heat transfer performance of phase change energy storage building materials and its application in energy efficient buildings

Wang,

Zhou

2024

Lay-out of air source heat pump heating system in Lugang Logistics Park

Luo

2024

In order to understand the process of using the heat pump heat organization, the author proposes to conduct a study based on the concept of heat pump air heating system in ?Land Port Logistics Park?. The author first analyzed the heating characteristics of the ground transportation fleet according to the actual situation, optimized the design of the heat pump, and proposed the same plan. Second, taking some provincial underground parks as examples, the actual performance of the park?s air source heat pump heating system was tested. According to the test, the temperature difference between the supply and return water is 3-4?C, and the average COP of the entire heating season is only 2.1. Based on the analysis and analysis, the meaning of the problem in the actual operation of the heat pump is explained, the cause of the problem is the determination of the pressure and the design plan. After installation, energy consumption can be further reduced, and it advises on the progress and use of the ventilation system. By using electric equipment to heat the docks in the port, it is possible to meet the heating needs of the park and reduce energy consumption and air pollution. Good this is a green and low carbon promise.

Application of artificial intelligence control in the control system of cooling and heating energy stations

Qi,

Ouyang,

2024

In order to understand the application of artificial intelligence in the control system of cold and hot energy station, the author proposes a research based on artificial intelligence control in the control system of cooling and heating energy station. The author first introduces artificial intelligence technology on the basis of heating and precision heating, relies on the ?Internet plus? and IoT platform, applies indoor temperature measurement technology, intelligent control and information docking technology, and establishes a heating system based on artificial intelligence technology. This system has improved the level of enterprise management, promoted the further development of heating and intelligent energy conservation, reduced energy consumption, reduced pollution, and achieved the need for precise heating of the pipe-line network. Secondly, combined with the application case of a district, this district is selected as the application pilot to describe the role and effect of this system in the Hydronics. The experimental results indicate that the heat consumption of the residential area is 27.07 W/m2, while the heat consumption of the comparison residential area is 28 W/m2. Through indoor temperature measurement, it was found that the average indoor temperature of the comparison residential area is 22?C. Therefore, the application of artificial intelligence heating systems has improved the thermal comfort of residents, bringing users a high quality heating experience while relatively reducing energy consumption. The intelligent application of the Hydronics can more accurately grasp the heating situation, timely and efficiently adjust the heating scheme, achieve heating balance, and improve the utilization efficiency of heat sources. At the same time, it can also effectively improve the troubleshooting ability of the hydronics, prevent safety risks, improve management efficiency, and will certainly provide more powerful support for the energy-saving society and environment-friendly society.