State Grid Hebei Electric Power

Solution

State Grid Hebei Electric Power used Baidu AI Cloud to build an AI middle platform that serves as a common infrastructure layer for grid operations. The implementation splits work between an AI training platform and an AI runtime platform. The training side handles sample collection, labeling, management and model training; the runtime side governs deployment, unifies model management and accommodates frameworks from different vendors. Together, these capabilities create a platform-service-scenario pattern in which Hebei can build applications for resource management, operations monitoring, fault alarms, load management, visual inspection and transmission-line intelligence on one governed stack instead of separate tools. Baidu positions the platform as a reusable utility AI asset: it standardizes models, raises reuse, reduces repeated investment and gives upper-level decision systems a consistent base for future AI deployment. For a grid operator, that means AI moves from isolated pilots into a shared operating environment for production, maintenance and customer-facing services.

Data flow

Operational data and labeled samples are prepared on the training platform, deployed to the runtime platform for inference, and then consumed by grid applications for monitoring, alarms, visual recognition and transmission-line scenarios.