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Transient Stability Evaluation Method for VSG Multi-machine System Based on Artificial Neural Network

An artificial neural network and transient stability evaluation technology, applied in the field of microgrid, to avoid dimensionality disaster and solve complex analysis effects

Active Publication Date: 2022-05-31
HUNAN UNIV
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  • Application Information

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Problems solved by technology

However, in the field of microgrid transient stability assessment, there is currently no application of neural networks

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  • Transient Stability Evaluation Method for VSG Multi-machine System Based on Artificial Neural Network
  • Transient Stability Evaluation Method for VSG Multi-machine System Based on Artificial Neural Network
  • Transient Stability Evaluation Method for VSG Multi-machine System Based on Artificial Neural Network

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Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] Due to the high order of the virtual synchronous machine multi-machine system model, the source-source interaction coupling, and the current limiter frequently changing the system working state, it is difficult to analyze and evaluate the transient stability assessment, and the existing methods cannot meet its online transient stability assessment requirements. . For this reason, the present invention proposes a method for evaluating the transient stability of a virtual synchronous machine multi-machine grid-connected system based on an artificial neural network. In this implementation, three virtual synchronous machines are used, and the steps of the transient stability evaluation method are as follows:

[0050] Step 1: Determine the input features and output features. The input features directly affect the accuracy of the ne...

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Abstract

The transient stability evaluation method of VSG multi-machine system based on artificial neural network includes the following steps: (1) Determine the input characteristics and output characteristics; (2) Change the load level of VSG multi-machine system, change the voltage drop of the grid, and change the active power of the virtual synchronous machine Reference value, virtual inertia, damping coefficient, change the current limit value of virtual synchronous machine, change the fault duration, generate sample data, and divide training sample set and test sample set; (3) perform data preprocessing on input features and output features ; (4) build the artificial neural network; (5) initialize the artificial neural network; (6) use the training sample set to train the artificial neural network, and complete the evaluation model construction; (7) use the test sample set to conduct evaluation model testing; (8) evaluate Model online application. Based on the artificial neural network, the invention can effectively realize the rapid and accurate evaluation of the multi-computer micro-grid system.

Description

technical field [0001] The invention relates to the field of micro-grid technology, in particular to a method for evaluating transient stability of a virtual synchronous machine (VSG) multi-machine grid-connected system based on an artificial neural network. Background technique [0002] The virtual synchronous machine (VSG) simulates the frequency modulation external characteristics of the synchronous generator. When a large disturbance occurs in the microgrid, the virtual synchronous machine will have the problem of power angle instability, which will affect the safe operation of the microgrid. Therefore, in order to provide information for the prevention and control of transient stability of the microgrid and gain time to ensure the safe and stable operation of the microgrid, accurate and fast online transient stability assessment is essential. [0003] The existing transient stability assessment methods are mainly time domain simulation method and energy function method....

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/27G06N3/04G06K9/62G06V10/774
CPCG06F30/27G06N3/04G06F18/214Y02B10/10
Inventor 帅智康赵慧敏沈阳赵峰程慧婕葛俊黄文沈霞董雪梅王钰泉
Owner HUNAN UNIV