## 4 Main Research Content
### Research Content  
Research Topic 1: Research on the Construction and Integration of the WSHP Energy Station Digital Twin Model. Mechanism of Physical Parameterized Model of Twin Body and Non-parameterized Energy Flow Model Construction. Due to the complexity of the electromechanical system of the energy station, as well as the phenomenon of insufficient spatial spacing in some pipeline networks and chaotic system logic, the difficulty of modeling digital twins has greatly increased. This study comprehensively characterized the geometric characteristics, physical characteristics, and energy operation laws of energy stations through the construction of parameterized physical models for energy stations and the digital reconstruction of non-parameterized energy flow logic, using methods such as BIM, GIS, and IoT. We analyzed the coupling and correlation mechanisms and dynamic spatiotemporal structures among various systems, achieved their parameterized analysis in digital space, and established a DT model of energy station embedded spatiotemporal characteristics and mathematical laws containing \"physical, operation, logic, data\" information. Mechanism of Coordination and Integration of Multi-source Heterogeneous Models of Digital Twin Bodies. This study proposed a static DT model information and dynamic energy model information fusion method. This method explored the nonlinear and complex logical relationships of WSHP energy station systems, and explored multi-source heterogeneous data systems based on prior knowledge systems. At the same time, this study proposed a DT prototype system software and hardware design framework and a DT prototype system design method for cross operation platform integration in the intelligent operation and maintenance management process of energy stations. The precise matching between data and models is ultimately completed, achieving the collaborative fusion of DT models among the \"model, operation, and data\" of energy stations. The research content can support the mapping of and interaction between virtual space and real space. Research Topic 2: Operation and Maintenance Monitoring Data Mining and Knowledge Graph Construction for WSHP Energy Station. Research on Key Feature Extraction Methods for Operation and Maintenance Monitoring Data from Energy Stations. This study employed feature extraction methods such as principal component analysis, association rule analysis, attribute reduction, and deep neural networks. By mapping the source data space to a low-dimensional feature space, the correlation between variables is eliminated. The research results achieved key feature extraction and a reduction in energy station operation and maintenance structural and non-structural data while preserving the original data information to the greatest extent possible. Through this study, the problem of the redundancy or duplication of the monitoring data collected during the deep integration of IoT systems and energy systems has been resolved. Finally, by utilizing key feature extraction and mining methods from operation and maintenance data, we can better process and apply these data based on the real-time extraction of key information from energy station operation and maintenance data. Research on Knowledge Graph Construction Method for Operation and Maintenance Monitoring Data from Energy Stations. This study solved the problems of complex intelligent cognition and large and complex operation and maintenance data from energy stations through the construction method of domain knowledge graph. We obtained corresponding knowledge from various heterogeneous multi-source data through specific extraction and mining techniques, and then represented it uniformly using graphs. At the same time, based on this method, the architecture design, graph parameter selection, and graph optimization mechanism of the relationship between the operational monitoring structure and structural features were completed.