Power grid security situation predicting method based on improved deep learning model

Abstract

The invention discloses a power grid security situation predicting method based on an improved deep learning model and belongs to the technical field of power system safety. The power grid security situation predicting method includes: performing power grid security situation evaluation through power grid data collection and preprocessing; aiming at the characteristic that indicator data of power grid security situation evaluation are high in relevance and dimension, providing an improved self-coding network method to lower dimension of the indicator data, and utilizing a data sample after dimension reduction and a power grid security situation value corresponding to a next time monitoring point; adopting an improved deep belief network to build a deep learning situation predicting model with multi-input and multi-output for power grid security situation prediction. By the power grid security situation predicting method, speed and accuracy of power grid security situation prediction can be improved effectively.

Description

Technical field [0001] The invention belongs to the field of power system security technology, and in particular relates to a power grid security situation prediction method based on an improved deep learning model. Background technique [0002] The existing power dispatching system is still mainly "experience + analysis", and its degree of automation and intelligence is not high. The main reason is that the system lacks accurate control over the development and changes of the power grid's operating status. At the same time, the analysis results provided by various analysis application software in the system only focus on a certain aspect of the power grid operation, and lack comprehensive analysis results and decision-making suggestions from the overall operation situation of the entire network, requiring dispatching operators to manually review various analysis results. , operating control based on manual experience and offline strategies. Therefore, with the rapid expans...

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Problems solved by technology

[0003] At present, the power grid security situation prediction mainly uses time series analysis and prediction, intelligent prediction, combined prediction, prediction methods based on gray theory, etc., but only predicts the future situation value, and does not explain that the size of the situation value specifically represents the security level of the power grid. At the same time, it rarely analyzes the trend of situation changes and explains the dynamic characteristics of power grid security situation elements. It belongs to passive perception and cannot comprehensively understand the power grid security situation as a whole. The auxiliary decision-making support for dispatchers is not enough, and dispatchers can only obtain partial data and information. Information, unable to fully perceive the power system security risk situation in real time

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