Distribution network voltage trend early warning method based on evidence theory fusion quantum network

A technology of evidence theory and trend prediction, applied in data processing applications, neural learning methods, electrical digital data processing, etc., to solve the problems of model accuracy and generality, improve accuracy, and improve accuracy and robustness.

Active Publication Date: 2020-07-24
南京和源电力实业有限公司
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AI Technical Summary

Problems solved by technology

The invention can well solve the problems of model accuracy and versatility in the voltage trend prediction problem, improves the accuracy and robustness of the trend prediction, and provides an active prevention and control strategy for voltage anomalies in the distribution network

Method used

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  • Distribution network voltage trend early warning method based on evidence theory fusion quantum network
  • Distribution network voltage trend early warning method based on evidence theory fusion quantum network
  • Distribution network voltage trend early warning method based on evidence theory fusion quantum network

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Embodiment Construction

[0070] The present invention is described in further detail now in conjunction with accompanying drawing.

[0071] Such as Figure 1 to Figure 3 As shown, the technical solution of the present invention is described in further detail.

[0072] refer to figure 1 Describe the general process of the inventive method, concrete steps are as follows:

[0073] Step 1: Obtain the historical data of the distribution network through the database;

[0074] Step 2: Preprocess the historical data of the distribution network and divide it into long-term (annual data), medium-term (seasonal data), short-term (weekly data) training set and test set, and the time units of different data sets are different;

[0075] Step 3: Construct the initial quantum neural network;

[0076] Step 4: Adjust the quantum neural network parameters and train the quantum neural network model;

[0077] Step 5: Test the neural network, and correct the voltage trend prediction results in combination with the act...

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Abstract

The invention discloses a distribution network voltage trend early warning method based on evidence theory fusion quantum network. The method comprises the following steps: S1, obtaining historical data of a distribution network; S2, preprocessing the historical data of the power distribution network, and dividing the historical data into a long-term (annual data) training set, a medium-term (seasonal data) training set, a short-term (week data) training set and a test set; S3, constructing an initial quantum neural network; S4, adjusting quantum neural network parameters, and training a quantum neural network model; S5, testing the neural network, and correcting a voltage trend prediction result in combination with the actual condition of the line; S6, improving the voltage trend prediction function of the quantum neural network through the DS evidence theory fusion; and S7, realizing a voltage abnormity early warning function. The invention can provide a new active prevention and control method for voltage abnormity of the distribution network and improve the power supply quality of the distribution network and the power grid operation economy.

Description

technical field [0001] The invention belongs to the technical field of distribution network voltage trend prediction, and in particular relates to a distribution network voltage trend early warning method based on evidence theory fusion quantum network. Background technique [0002] In recent years, with the development of my country's economy and the improvement of people's living standards, people's demand for electricity has also increased sharply, and the power load has increased rapidly. However, the development of the distribution network is relatively slow compared with the main network, and the replacement of power distribution equipment is relatively slow. Lag, distribution network voltage abnormal problem is becoming more and more prominent. At present, the common types of distribution network voltage anomalies mainly include long-term voltage anomalies, seasonal voltage anomalies, and short-term voltage anomalies. However, in the actual power grid system, due to t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06Q50/06G06F16/2458
CPCG06N3/084G06F16/2474G06Q50/06G06N3/045Y02D10/00
Inventor 陈光宇贺臻张仰飞郝思鹏李干黄良灿
Owner 南京和源电力实业有限公司
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