An AI-driven power distribution fault location system and method
The AI-driven fault location system utilizes a topology response collaborative constraint model and a reinforcement learning strategy model to eliminate false fault paths and enhance path scoring discrimination capabilities. This solves the problems of information lag and high operation and maintenance costs in traditional power distribution fault location, achieving efficient and accurate fault identification and location.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING LONGDEYUAN INTELLIGENT ELECTRIC POWER CO LTD
- Filing Date
- 2025-12-23
- Publication Date
- 2026-06-09
AI Technical Summary
Traditional power distribution fault location relies on manual inspection, which suffers from information lag, slow response, and high operation and maintenance costs. Especially in multi-feeder and multi-bus structures, there are many path assumptions and the scoring system lacks feedback enhancement mechanisms, resulting in poor fault location accuracy and convergence.
An AI-driven fault location system is constructed by using state projection construction units, state collision elimination units, differential comparison scoring units, and structural feedback location units. It utilizes topological response collaborative constraint models, AI response scoring models, and reinforcement learning strategy models to build a multi-distributed state space structure mapping system, eliminate false fault paths, enhance path scoring discrimination capabilities, and achieve accurate fault location.
It significantly reduces the candidate path search space, improves the accuracy and efficiency of fault identification, ensures the uniqueness of fault location results and the reliability of operation and maintenance decisions, and reduces operation and maintenance costs.
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Figure CN121770157B_ABST
Abstract
Citation Information
Patent Citations
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