ABSTRACT
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.
KEYWORDS
PAPER SUBMITTED: 2023-04-11
PAPER REVISED: 2023-06-24
PAPER ACCEPTED: 2023-08-03
PUBLISHED ONLINE: 2024-04-13
THERMAL SCIENCE YEAR
2024, VOLUME
28, ISSUE
Issue 2, PAGES [1321 - 1328]
- Bedrikovetski, S., et al., Artificial Intelligence for Body Composition and Sarcopenia Evaluation on Computed Tomography: A Systematic Review and Meta-Analysis, European Journal of Radiology, 1 (2022), 110218
- Miao, D., Design of Power Network Fault Diagnosis Based on Time Series Matching, Thermal Science, 23 (2019), 5A, pp. 2595-2604
- Zhou, Z., et al., Artificial Intelligence Biology - Biology v3.0, Scientia Sinica Vitae, 52 (2022), 3, pp. 291-300
- Giudicessi, et al., Artificial Intelligence-Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device, Circulation, 143 (2021), 13, 14
- Shin, D., Embodying Algorithms, Enactive Artificial Intelligence and the Extended Cognition: You Can See as Much as You Know about Algorithm: Journal of Information Science, 49 (2021), 1, pp. 18-31
- Junejo, A. R., et al., Molecular Communication Networks: Drug Target Scalability Based on Artificial Intelligence Prediction Techniques (Retraction of Vol. 23, p. 1, 2021), Journal of Nanoparticle Research, An Interdisciplinary Forum for Nanoscale Science and Technology, 14 (2021), 5, 24
- Tripathy, S. S., et al., Image Processing-Based Artificial Intelligence System for Rapid Detection of Plant Diseases, Bioinformatics in Agriculture, 61 (2022), 9, 624
- Hvid, H., Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Gttingen Minipigs, Toxicologic Pathology, 49 (2021), 4, pp. 912-927
- Hu, X., Analysis of a Permanent Magnet Dc Motor Explosion-Removal Robot System Based on Thermal Energy Optimization Control, Thermal Science, 25 (2023), 4B, pp. 2991-2998
- Xu, A., Thermal Energy Storage Technology and Its Application in Power Data Remote Transmission, Thermal Science, 27 (2023), 2A, pp. 1175-1181