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A Power System Transient Stability Assessment Method Based on Short-term Disturbed Trajectories

Inactive Publication Date: 2021-04-30
NORTHEAST DIANLI UNIVERSITY +2
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Problems solved by technology

However, due to the limitations of the shallow structure of the machine learning method, the feature expression ability of the input data is limited, and the generalization ability is restricted when solving complex classification problems.

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  • A Power System Transient Stability Assessment Method Based on Short-term Disturbed Trajectories
  • A Power System Transient Stability Assessment Method Based on Short-term Disturbed Trajectories
  • A Power System Transient Stability Assessment Method Based on Short-term Disturbed Trajectories

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Embodiment Construction

[0045] The power system transient stability evaluation method based on short-term disturbed trajectory of the present invention, it comprises the following steps:

[0046]1) Determination of input features and output results of convolutional neural network:

[0047] ① Obtain disturbed trajectories of voltage amplitude, active power, rotational speed and power angle of a large number of generators through offline simulation, select four electrical quantity trajectories within 0.2s after the fault clearing time, sampling interval T=0.01s, each trajectory has a total of With 20 sampling points, the sampling sequences of the four short-term disturbed combined trajectories obtained by simulation constitute the input sample matrix set of the convolutional neural network, and the sampling sequences of the four electrical quantities of each generator are used as the input sample matrix set of each input sample matrix. column, the dimension of each sample matrix is ​​20×4n (n is the nu...

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Abstract

The present invention is a power system transient stability evaluation method based on the short-term disturbed trajectory after the fault is cleared. The feature arrangement method when evaluating the best accuracy rate makes the local features extracted by the model more robust, and then optimizes the network window parameters with the goal of optimizing the comprehensive evaluation index of the model to enhance the generalization ability of the model , and finally establishes the mapping relationship between the short-term trajectory and the transient stability to realize fast and accurate rapid evaluation of the transient stability of the power system. The method of the present invention can effectively reduce the misjudgment and missed judgment samples of model evaluation, and is more accurate and efficient than the traditional machine learning evaluation method, and the evaluation of transient stability based on short-term disturbed trajectories leaves a certain amount of time for dispatchers margin to take control measures.

Description

technical field [0001] The invention relates to the field of safe and stable operation of power systems, and relates to a method for evaluating transient stability of power systems based on short-term disturbed trajectories. Background technique [0002] Rapid assessment of transient stability is an important prerequisite for online security prevention and control of power systems, and is of great significance to the safe and stable operation of power systems. The existing rapid transient stability assessment technology uses the geometric characteristics of the response trajectory of the system to evaluate the transient stability of the power grid after a fault. It does not depend on the model and parameters of the system, and the analytical results are universal. However, this type of method requires a long time to acquire It is difficult to meet the requirements of "instant measurement, identification, and control". [0003] The machine learning method does not need to es...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 安军李宗翰艾士琪赵高尚李京杨少波刘道伟李柏青杨红英郑恒峰邵广惠徐兴伟阴宏民王震宇刘洋高德宾李泽宇
Owner NORTHEAST DIANLI UNIVERSITY
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