Research on comprehensive energy data fusion method based on semantic association feature mining

Inhalt:
With the promotion of the construction of urban integrated energy system, there are more and more intelligent businesses such as distributed energy access control and distribution automation. The storage and processing of massive associated data need reliable business perception, calculation, analysis and processing models, so as to better support the real-time analysis and intelligent processing of local businesses of integrated energy. This paper proposes an integrated energy data fusion method and device. The intelligent terminal collects multi service scenario data and completes the preliminary screening of multi-source heterogeneous data of integrated energy through data cleaning. Based on the simplified echo state network, the structure of the reserve pool is simplified into a ring topology composed of neural unit nodes, so as to reduce the complexity of the reserve pool in the echo state network, realize the perception of multiple types of power business, and then use the semantic association feature mining method to extract the data features and realize the heterogeneous fusion of multi-source data. Through verification and analysis, the method proposed in this paper effectively improves the accuracy of business recognition and fusion efficiency.