A method and system for checking monthly planned distribution transformer repeated power outages based on artificial intelligence technology
By applying artificial intelligence technology and RPA robots in the power grid management and distribution operation support system, we can automatically obtain and intelligently check the monthly planned distribution network power outage application form data and actual power outage distribution data, and solve the problems of inefficient manual screening and insufficient data integration in the existing technology, and achieve efficient and accurate repeated power outage identification and optimization of power outage plans.
Patent Information
- Application Number
- CN202411728813.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-28
- Publication Date
- 2025-04-01
AI Technical Summary
During the review and implementation of the distribution network power outage plan, the existing technology has problems such as inefficient manual screening, insufficient data integration and sharing, and lack of intelligence in the comparison of power outage records, resulting in the failure to effectively solve the problem of repeated power outages.
Through the power grid management platform and distribution operation support system, artificial intelligence technology and RPA robots are used to realize the automatic acquisition and intelligent verification of monthly planned distribution network power outage application data and actual power outage distribution data. Automatic comparison is carried out based on semantic analysis and text similarity algorithm, a list of repeated power outage distribution is generated, and the repeated power outage situation is displayed through the data visualization interface.
It realizes automatic acquisition, intelligent calibration and visual display of distribution network power outage plan data, improves the accuracy and reliability of repeated power outage recognition, reduces manual calibration workload, improves efficiency, and optimizes the power outage plan arrangement.