Fault prediction method and system for multi-source heterogeneous power distribution network

By clustering analysis of multi-source heterogeneous distribution network data and using improved neural networks for fault prediction, the problem of single model considerations and verification processes affecting grid safety in the prior art is solved, and more efficient and accurate fault detection and maintenance are achieved.

CN119669692APending Publication Date: 2025-03-21CTG JIANGSU ENERGY INVESTMENT CO LTD
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Patent Information

Application Number
CN202411753192.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-02
Publication Date
2025-03-21

AI Technical Summary

Technical Problem

The existing multi-source heterogeneous distribution network fault prediction technology has single model considerations, failure factors cannot be fully considered, and the model fault detection reliability is poor; at the same time, the process of verification technology requires a large number of experiments, affecting the safe operation of the power grid, and digital simulation and instrument simulation cannot fully reflect the real operation, and the calculation is large and the efficiency is low.

Method used

By clustering analysis of multi-source heterogeneous distribution network data, data fusion is achieved to provide more comprehensive data for prediction; improved neural networks, especially YOLOv7 neural network, are used to predict faults, reduce computational volume, improve efficiency and prediction accuracy.

Benefits of technology

It improves the reliability of model fault detection, reduces the impact of the verification process on the safety of the power grid, can more accurately reflect the real operation of the distribution network, comprehensively simulates complex fault types, avoids the problems of large calculation volume and low efficiency, and achieves real-time and effective maintenance of faults.

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Abstract

The invention provides a multi-source heterogeneous power distribution network fault prediction method and system, relates to the technical field of power distribution network fault identification, and aims to solve the problems that an existing model is single in consideration factor, cannot comprehensively simulate a complex fault type of a multi-source heterogeneous power distribution network, is large in calculation amount, is low in efficiency, and is poor in fault prediction accuracy. The method comprises the steps of obtaining historical data related to a power distribution fault; preprocessing the historical data related to the power distribution network fault to obtain preprocessed historical data; analyzing the preprocessed data by adopting a clustering technology to obtain a clustering result; based on a clustering result, constructing a fault prediction model for training to obtain a trained fault prediction model; and inputting real-time data related to the fault of the power distribution network into the trained fault prediction model for prediction. According to the method, the problems of delay, large calculation amount and low efficiency are avoided, the real operation condition of the power distribution network can be reflected, and the fault type of the multi-source heterogeneous power distribution network is comprehensively simulated.
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