Method and device for training and predicting transient stability prediction model of power system

Abstract

The invention discloses a method and device for training and predicting a transient stability prediction model of a power system, and the method comprises the steps: obtaining the historical operationdata of the power system, and processing the historical operation data to obtain a first sample data set, wherein the first sample data set comprises positive sample data and negative sample data, the positive sample data is used for representing that the power system is in a stable state, and the negative sample data is used for representing that the power system is in an unstable state; training the neural network fusion model by using the first sample data set to obtain a power system transient stability prediction model, wherein the neural network fusion model is a neural network fusion model constructed according to a bidirectional long-short-term memory network, a convolutional neural network and a support vector machine. By implementing the method, the feature vectors are extractedby using the bidirectional long-short-term memory network and the convolutional neural network, and the feature vectors are input into the support vector machine for stable prediction, so that the prediction accuracy of the transient stability of the power system is improved.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a training and prediction method and device for a prediction model of transient stability of a power system. Background technique [0002] The stable operation of the power system is directly related to people's production and life and the normal operation of society. With the continuous expansion of power system scale, the development of AC-DC hybrid transmission mode, the continuous increase of new equipment and the application of new energy technologies, the operating state of the power system is getting closer and closer to its stability limit, and its security and stability problems are becoming more and more serious. Large-scale power outages occur frequently in the power system, and there is an urgent need for a method that can quickly and accurately evaluate the transient stability of the power grid. At present, machine learning methods are commonly used in the indu...

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Problems solved by technology

[0003] In view of this, an embodiment of the present invention provides a training and prediction method and device for a power system transient stability prediction model to solve the problem of low accuracy of the power system transient stability evaluation method based on the machine learning method

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