A Power System Transient Stability Assessment Method Based on Deep Belief Network

A technology of deep belief network and transient stability assessment, applied in the field of power system, can solve the problems of low identification of critical samples, the accuracy of model evaluation cannot meet the requirements, and the control information of the system governor controller cannot be reflected too much. , to achieve the effect of transient stability

Active Publication Date: 2021-03-30
FUZHOU UNIV
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Problems solved by technology

[0003] The current post-fault feature quantities are mainly obtained through fixed delays, and the obtained feature quantities have a low degree of recognition for critical samples. At the same time, they cannot reflect too much control information of controllers such as system governors and voltage regulators. , causing the evaluation accuracy of the model to fail to meet the requirements

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  • A Power System Transient Stability Assessment Method Based on Deep Belief Network
  • A Power System Transient Stability Assessment Method Based on Deep Belief Network
  • A Power System Transient Stability Assessment Method Based on Deep Belief Network

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[0024] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0025] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0026] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to a power system transient stability evaluation method based on a deep belief network, which extracts feature quantities after a fault according to the maximum phase angle difference of the bus phase angle of the power system during the swing process, and inputs the features into the deep belief network , the invention can realize the rapid evaluation of the transient stability of the power system.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a method for evaluating transient stability of power systems based on deep belief networks. Background technique [0002] With the gradual installation of PMUs in the power grid, the control center has been able to obtain the dynamic response information of the system from WAMS in real time. With the rise of big data technology, data-driven methods have expanded traditional pattern recognition methods, which has laid a foundation for staff to analyze the safety and stability of power systems from the perspective of big data. The data-driven transient stability discriminant model only needs to build a mapping model between input and output, and input the real-time response of the system into the model to quickly obtain the status information of whether the system is stable or not. [0003] The current post-fault feature quantities are mainly obtained through fixed delays, a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 王怀远林楠
Owner FUZHOU UNIV
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