## 4 Main Research Content
### Research Objectives Innovation  
The construction of system logic and the difficulty of real-time simulation in the operation and maintenance management process of the WSHP energy station, as well as issues such as fragmented system operation data, data redundancy, and low energy efficiency caused by supply-demand imbalance, are discussed in this paper. In response to China's \"Internet+\" smart energy development strategy in the era of carbon peaking and neutrality, this study utilized massive amounts of operation and maintenance data from energy stations and their operational logic combined with technologies such as DT, data mining, and AI to establish an operational state model of energy stations with hybrid DT capabilities. The research includes methods for constructing WSHP energy station DT models and integrating heterogeneous data from multiple sources, extracting key features from terminal monitoring data, and constructing knowledge graphs, as well as AI based operation state prediction methods and intelligent operation optimization mechanisms. The research results will contribute to achieving the goals of the information, digitization, and intelligentization of energy station construction, assisting in energy conservation and carbon reduction in building energy systems, thereby promoting the early realization of China's carbon neutrality strategy.  
The research outcomes will guide the development of smart energy systems for the WSHP energy station project in the Hankou Binjiang International Business District, assisting energy stations in achieving safe, stable, efficient, low-carbon, and cost-effectiveoperational goals. Additionally, it holds significant academic guidance and engineering reference value for the path selection towards China's carbon neutrality strategic goals. The innovative elements of this research are summarized as follows:  
1. Establishment and Integration of WSHP System Digital Twin Models Combining Dynamic and Static Aspects.  
In this study, we proposed a DT model establishment and fusion method based on \"BIM + GIS + IoT\" to address the problems of complex system logic construction and real-time simulation difficulties in the operation and maintenance management of WSHP energy stations. By constructing parameterized models for static physical devices and non-parameterized models for dynamic energy information flow, the digital unity of energy stations in different dimensions such as model, operation, and data can be achieved.
2. Construction of Knowledge Graphs Using Massive Terminal Monitoring Data with Key Feature Extraction Methods.  
In response to the problems of fragmented and redundant operational data in the energy station system during the operation and maintenance management of a WSHP energy station, we proposed the use of key feature method to extract massive amounts of terminal monitoring data and construct a knowledge graph of the complex operation and maintenance status of energy stations. According to the knowledge graph, this strategy can help energy stations to achieve the digital expression of logical relationships under complex coupling effects of multiple systems.
3. Prediction and Optimization of Operational Situational Awareness Using a Hybrid Digital Twin Model Integrated with Artificial Intelligence Algorithms.  
To address the issue of low energy efficiency caused by supply-demand imbalance in the operation and maintenance management process of the WSHP energy station, a hybrid DT model based on the mapping of digital twin and artificial intelligence dual models was proposed. Building upon this model, a dynamic analysis of energy station operational states can be conducted to assist energy stations in load forecasting and intelligent system optimization under various operating conditions.