| Title | Development and Applications of Integrated Numerical Model and Artificial Intelligence Technology for Hot Spring Pool System |
|---|---|
| Authors | Chunhua Jiang, Zhaoxin Zhang, Peijun Pan, Xi Chen, Taojun Chen, Xianhua Deng |
| Year | 2023 |
| Conference | World Geothermal Congress |
| Keywords | Hot spring pool, Heat loss, Numerical mode, Artificial intelligence. |
| Abstract | With the successful development of the health industry, the construction of geothermal (hot springs) projects has been developed all over the country in China. Within the projects, hot springs designed as therapy baths in a garden-style landscape are an important supporting and promotional highlight of the system construction. Due to the significant environmental differences in climate in different regions where the hot spring projects are located, no industry standards can be referred to. Therefore, the engineering design of the projects is carried out from experience, resulting in significant deviations between the estimated project operation data and the actual one and directly increasing the costs related to the investment and operation. This paper addresses a numerical model to guide the project plan, engineering design, equipment selection, and system intelligent control to ensure low loss and high-efficiency operation of the project energy utilization. The numerical model of the pool heat loss is highly feasible and practical by collecting a large amount of project data, verifying and validating the calculations, summarizing the key factors affecting the heat loss of hot spring pools, carrying out project validation, and obtaining a numerical model to solve this fundamental bottleneck problem plaguing the development of the industry. The model uses the Python language package as the simulation platform. By inputting environmental data, the model can get the heat loss of the hot spring pool hourly and automatically generate the energy consumption index, heat source configuration, electricity load, and daily water consumption. These outputs greatly facilitate the engineers to carry out design work, further optimize the process, and select the appropriate devices. The combination of model predictions and artificial intelligence (AI) technology makes it possible to integrate R&D and intelligent control of geothermal system equipment. It integrates heat control, data acquisition and transmission, associated APP link control, and intelligent system integration. It can reduce the energy consumption of the system, save the operation and maintenance costs, promote the effective and reasonable utilization of geothermal resources, and as well help the country achieve the grand goal of carbon peak and carbon neutrality.” |