Research on Power Data Analysis Algorithms Based on Knowledge Graph and Artificial Intelligence

As the power system continues to develop, the scale and complexity of power data are also increasing. Traditional data analysis methods can no longer meet the modern power system's demand for efficient and accurate data analysis. This paper proposes a method for researching power data analysis algorithms based on knowledge graphs and artificial intelligence. Firstly, by constructing a knowledge graph of power data, we achieve structured representation and relationship mining of power data. Secondly, artificial intelligence techniques, especially deep learning algorithms, are used for power data prediction, anomaly detection, and fault diagnosis. A comprehensive analysis framework is designed and implemented, and experiments are conducted using actual power data. The experimental results demonstrate that this method significantly improves the accuracy and efficiency of data analysis. Finally, this paper summarizes the research results and proposes future research directions.