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Transient stability evaluation method of gate graph neural network based on unbalanced data

A transient stability, neural network technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problem of machine learning methods not being interpretable, and achieve fast and accurate transient stability The effect of high accuracy and low error rate

Active Publication Date: 2022-07-29
STATE GRID HEILONGJIANG ELECTRIC POWER COMPANY +2
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Problems solved by technology

[0006] The present invention is for the problem that current machine learning methods do not have interpretability

Method used

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  • Transient stability evaluation method of gate graph neural network based on unbalanced data
  • Transient stability evaluation method of gate graph neural network based on unbalanced data
  • Transient stability evaluation method of gate graph neural network based on unbalanced data

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Experimental program
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Effect test

specific Embodiment approach 1

[0070] The method for evaluating the transient stability of a gate graph neural network based on unbalanced data described in this embodiment includes the following steps:

[0071] Step 1. First, use the first CGAN model to generate unstable samples, and then use the second CGAN model to generate unstable samples of different events:

[0072] 1. Build a conditional generative adversarial network, namely CGAN:

[0073] Deep learning models can represent the probability distribution of various data in artificial intelligence applications. Adding discriminative models to deep learning can make the probability distribution of various data represented by the model more accurate. The generative adversarial network is a discriminative model added to deep learning. The generative adversarial network has both a generative model (G) and a discriminative model (D). The data distribution generated by the model conforms to the real data distribution.

[0074] Conditional Generative Adver...

Embodiment

[0143] A. IEEE-39 bus system:

[0144] Verification of the validity of the TSA model with the New England 39 bus system. The simulation was performed on a PC with an Intel Core i3 CPU and 8.00GB RAM. The structure of the New England 39 bus system is as follows Figure 9 shown. like Figure 9 As shown, the system has 10 generators, 39 buses, 19 loads, 12 transformers and 34 transmission lines.

[0145] B. Data Generation

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Abstract

A gate graph neural network transient stability evaluation method based on unbalanced data belongs to the technical field of transient stability analysis of power systems. The present invention addresses the problem that current machine learning methods do not have interpretability. The present invention generates unstable samples based on Conditional Generative Adversarial Network (CGAN), which can not only generate unstable samples, but also can be used to generate unstable samples with unbalanced events, so that the samples can not only achieve a balance between stability and instability, but also Equilibrium of events in unstable samples is reached. After solving the data imbalance problem of the samples, the GGNN algorithm is used to evaluate the transient stability of the power system, and to determine the cause of the instability of the power system. Mainly used for transient stability assessment of power system.

Description

technical field [0001] The invention relates to a network transient stability evaluation method of a power system, and belongs to the technical field of transient stability analysis of a power system. Background technique [0002] Transient stability refers to whether the power system can reach the steady-state operating state or the original operating state through a transient process after a sudden large disturbance in a certain operating state. The power system is an important part of the energy Internet of Things, and the transient stability assessment of the power system is also very important. These large disturbances generally refer to short-circuit faults, sudden disconnection of lines or generators, etc. If the power system cannot reach a stable or original operating state after being subjected to large disturbances, it will cause the instability of the power system, cause the power system to collapse in a large area, and cause serious social and economic losses. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06Q10/06G06Q50/06
CPCG06N3/084G06Q10/0639G06Q50/06G06N3/047G06N3/045
Inventor 孙迪李俊关心周小梅
Owner STATE GRID HEILONGJIANG ELECTRIC POWER COMPANY
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