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A distribution network fault prediction method and system based on reinforcement learning

A technology for fault prediction of distribution network, applied in the field of electric power, can solve problems such as failure to predict failure, failure to achieve failure, affecting the accuracy of supervised learning model prediction, etc.

Active Publication Date: 2022-04-15
BEIJING INHAND NETWORKS TECH
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Problems solved by technology

However, it is impossible to predict the failures that will occur, and it is impossible to prevent possible failures in time.
[0009] The supervised learning model can be used to predict the faults of the distribution network, but when using the supervised learning model, if the distribution network managers intervene in the operation of the distribution network according to the prediction results generated by the supervised learning model, the fault data will be distorted , thus affecting the prediction accuracy of the supervised learning model

Method used

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  • A distribution network fault prediction method and system based on reinforcement learning
  • A distribution network fault prediction method and system based on reinforcement learning
  • A distribution network fault prediction method and system based on reinforcement learning

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[0079] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0080] Figure 7 is a schematic diagram of a fault prediction flow chart according to an embodiment of the present invention, Figure 8 It is a structural schematic diagram of a specific embodiment of the deep convolutional neural network in the reinforcement learning type fault prediction model of the present invention; Figure 9 It is a structural schematic diagram of a specific embodiment of the deep convolutional neural network of the evaluation model used by the reinforcement learning type fault prediction model of the present invention when performing model training; Figure 7 , 8 and 9 illustrate this method.

[0081] First, the optimal prediction model is obtained according to the model training method of the present invention by using the training data...

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Abstract

The invention discloses a distribution network fault prediction method based on reinforcement learning. The method includes: extracting the previous time, down-sampling waveform and local waveform from the fault recording data in the distribution network section to be predicted; Input the previous time, down-sampled waveform and local waveform into the fault prediction model to obtain the prediction result, and the fault prediction model includes a deep convolutional neural network and a long-short-term memory network unit.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a distribution network fault prediction method and system based on reinforcement learning. Background technique [0002] The distribution network is an important part of the power system. With the rapid development of the smart grid, a large number of uncertain connections of distributed power sources make the fault information of the distribution network more and more complicated, and the accurate and rapid analysis of the fault becomes more and more difficult. In order to ensure the highly intelligent operation of the distribution network, real-time monitoring of feeder operation data, timely warning of abnormal conditions, and rapid fault location and processing are required. Therefore, the distribution network is usually equipped with devices such as line fault indicators and feeder terminals, and these devices are used to record the operation of the distribution netw...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/08G06K9/00G06K9/62G06N3/04G06N3/08
CPCG01R31/086G01R31/088G06N3/08G06N3/045G06F2218/16G06F2218/02G06F2218/08G06F18/214
Inventor 姚蔷戴义波张建良
Owner BEIJING INHAND NETWORKS TECH