融合多源数据的营配电网拓扑自动识别与校验方法
By constructing a multi-source data fusion architecture and utilizing time-series feature mining and causal inference algorithms, the distribution network topology is automatically inverted, solving the problem of the disconnect between static ledgers and dynamic operation. This achieves high-confidence closed-loop correction of the topology and accurate synchronization of the digital twin model, thereby improving the intelligent operation and maintenance of the distribution network.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHENGDU SUN HIGH-TECH CO LTD
- Filing Date
- 2026-05-14
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the static records of distribution network topology are disconnected from dynamic operation, and there is a lack of multi-source data fusion mechanisms. This results in delayed topology error detection and a lack of automatic correction capabilities, affecting the smooth operation of distribution and dispatching and the reliability of power supply.
A three-layer integrated architecture of 'data layer - feature layer - decision layer' is constructed. By utilizing multi-source heterogeneous data from marketing, scheduling and production systems, and through time-series feature mining and causal inference algorithms, topological relationships are automatically inverted to achieve closed-loop correction under high confidence.
It enables automatic identification and dynamic verification of distribution network topology, improves the accuracy of topology identification and closed-loop correction capability, ensures real-time synchronization between digital twin model and physical entity, reduces manual verification workload, and improves the level of intelligent operation and maintenance of distribution network.
Smart Images
Figure CN122203584B_ABST