Research on Bus Load Forecasting System Based on Cloud Edge Fusion Platform

The integration of large-scale new energy and energy storage equipment has increased the complexity of bus load forecasting and affected the refined management of scheduling. In order to achieve high-precision bus load forecasting based on big data, this paper proposes the design of a bus load forecasting system based on cloud edge fusion platform. Combining the advantages of cloud edge fusion platform and the demand for bus load forecasting, the overall architecture of the bus load forecasting system based on cloud edge fusion platform is designed. The cloud is responsible for data processing, model training, model downloading, and prediction result reception, while the edge is responsible for data monitoring, data uploading, model reception, result prediction, and result application. Using Docker container technology as the foundation of computing resource management, a rapid container deployment method based on cloud edge container mirroring is proposed. A task scheduling method for analyzing the power system cloud edge collaborative platform based on hierarchical management is further proposed. The proposed system realizes the effective allocation of cloud edge fusion platform resources under the demand of big data artificial intelligence bus load forecasting and ensures the implementation foundation of high-precision bus load forecasting. Finally, the effectiveness and superiority of the proposed system in resource management in bus load forecasting applications are further verified through examples.