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Power supply equipment load and life prediction model construction method

A life prediction model and technology for power supply equipment, applied in the field of power equipment, can solve problems that affect the safety of electricity use, low accuracy, low precision, etc., and achieve the effect of avoiding equipment failure problems

Pending Publication Date: 2022-02-25
STATE GRID ZHEJIANG ELECTRIC POWER +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing life and life loss predictions for repaired equipment often have low accuracy and low accuracy, which affects the timely repair of the repaired equipment by relevant personnel, causing power failures to occur on the user side, which affects the users. Experience affects the safety of electricity use

Method used

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  • Power supply equipment load and life prediction model construction method
  • Power supply equipment load and life prediction model construction method
  • Power supply equipment load and life prediction model construction method

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Experimental program
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Embodiment

[0030] Embodiment: A method for constructing a power supply equipment load and life prediction model, the described power supply equipment load and life prediction model is an ES-LSTM network model, including three parts of construction:

[0031] S1: Input training data to the power supply equipment load and life prediction model;

[0032] S2: Construct the sub-model of the power supply equipment load and life prediction model, the sub-model is a sub-model using the classic long short-term memory network model (LSTM);

[0033] S3: Construct the fusion network, and organically fuse the laws captured by any two sub-models on their respective input data. Through the three steps of S1, S2, and S3, the construction of the ES-LSTM fusion network model is completed. The training and testing process of the ES-LSTM network model is as follows: image 3 As shown, it contains the network structure diagram of the sub-model and the network structure diagram of the fusion model.

[0034]...

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PUM

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Abstract

The invention discloses a power supply equipment load and life prediction model construction method, which solves the defects in the prior art. The power supply equipment load and life prediction model is an ES-LSTM network model, and comprises the construction of three parts of S1, inputting training data to the power supply equipment load and life prediction model, S2, constructing a sub-model of the power supply equipment load and life prediction model, wherein the sub-model is a sub-model adopting a classic long short-term memory (LSTM) network model, and S3, constructing a fusion network, and organically fusing the laws captured by any two sub-models on respective input data. The design further improves the prediction precision.

Description

technical field [0001] The invention relates to the technical research field of power equipment, in particular to a method for constructing a power supply equipment load and life prediction model. Background technique [0002] In order to meet the needs of my country's sustainable economic development, the technical level of the power system is also constantly improving and perfecting. As a key link in the power system, the distribution network plays an important role in the distribution of electric energy. With the rapid growth of distribution network scale, when planning and designing it, in addition to ensuring the reliability of power supply for users, how to ensure power quality and reduce losses is also an important goal that needs to be considered. [0003] As one of the main contents of distribution network planning, the load and life prediction of power supply equipment mainly evaluates the reliability of power supply equipment to judge the risk of its operation. W...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/08G06N3/044Y04S10/50
Inventor 陈蕾赵深朱炯余慧华刘宏伟刘兴业向新宇郑洁徐重酉林胥登黄梦庆徐国轩陆倩如
Owner STATE GRID ZHEJIANG ELECTRIC POWER