Multi-layer voltage control method for parallel quantum artificial emotion deep learning

A voltage control method and deep learning technology, applied in neural learning methods, quantum computers, electrical digital data processing, etc.

Active Publication Date: 2021-05-14
GUANGXI UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the above two methods need to have better results in a larger range of data sets, and further research and analysis are still needed in real-time data coordinated control.

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  • Multi-layer voltage control method for parallel quantum artificial emotion deep learning
  • Multi-layer voltage control method for parallel quantum artificial emotion deep learning
  • Multi-layer voltage control method for parallel quantum artificial emotion deep learning

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Embodiment Construction

[0048] A multilayer voltage control method for parallel parallel quantum artificial emotion deep learning proposed by the present invention is described in detail in conjunction with the accompanying drawings as follows:

[0049] figure 1 It is the flow chart of the power system voltage prediction of the method of the present invention. First, build a parallel control system, respectively build a complex engineering control system model and an artificial engineering system model and form a closed-loop negative feedback mechanism. Then, the quantum walk search method is used as the artificial control model to search the target action solution of the current artificial system, and the control of the artificial model is completed, and the generated data parameters are mutually corrected with the complex control system; the deep neural network based on artificial emotion is used as the complex control system. The controller in the control link learns and trains the current voltag...

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Abstract

The invention provides a multi-layer voltage control method for parallel quantum artificial emotion deep learning, which combines a quantum walking search method with an artificial emotion-based deep neural network and is used for multilayer voltage control of a power system. Firstly, a quantum walking method serves as a manual control model in a parallel control system to carry out probability statistics on historical voltage data, and is used for rapidly obtaining a target control strategy through quantum and obtaining more original voltage data at the same time. And secondly, features are extracted by using voltage data generated by a quantum walking method and historical voltage data based on an artificial emotion deep neural network method, and accurate prediction of the voltage is realized. And finally, the power system decision optimization model realizes optimal control according to the predicted voltage. The method can effectively solve the problem of insufficient voltage data samples of a power system, and achieves the precise control of the voltage of a power grid. Parallel data stream transmission is adopted, and data exchange between parallel systems is efficiently completed.

Description

technical field [0001] The invention belongs to the field of power system voltage control, and relates to a power system voltage control method based on an artificial intelligence method, which is suitable for controlling the voltage of a power system generator set. Background technique [0002] Due to the current mismatch between the distribution of energy storage resources and economic development, the construction of a coordinated development of voltage networks at various levels has become the mainstream trend in the development of my country's power grid units. While the current grid system brings huge economic benefits, it also puts forward higher requirements for the accuracy, reliability and stability of the grid voltage, which brings great challenges to the coordinated control of the grid voltage. Therefore, it is of great significance to study the development of grid voltage coordination control. Among them, the prediction based on precise voltage command is the k...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06N3/04G06N3/08G06N10/00G06F113/04
CPCG06F30/27G06N3/04G06N3/08G06N10/00G06F2113/04
Inventor 殷林飞张辰微马晨骁高放
Owner GUANGXI UNIV
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