Electric Power Multi-Source Heterogeneous Data Fusion Model Based on Edge Computing

Based on the electric power big data network system, this article conducts a comprehensive analysis of the current application status of electric power big data technology, and deeply discusses the research work on the electric power data information processing system with multi-source heterogeneous data fusion technology as the core, with a view to providing technology for relevant personnel in the electric power system. The classic data fusion method Kalman filter algorithm is improved, and an event-driven distributed Kalman filter algorithm is proposed. This algorithm adds an event determination strategy in the process of data processing and transfer between sensor nodes, controls the number of communications between nodes in an event-driven manner, and at the same time reduces redundant data and data affected by noise through algorithm processing, while ensuring data quality, improving the fusion efficiency. Finally, by comparing it with the conventional distributed Kalman filter algorithm, the effectiveness of the algorithm was verified through experimental simulation.