基于深度学习的电网安全态势感知方法

为了提高电力网络的安全性，实现电力网络的可持续运行，引入深度学习神经网络，开展对电力网络安全态势感知方法的设计研究，以此提出一种全新的安全态势感知方法。本文采用电力网络安全态势评估指标，结合各类电力网络环境因素，对未来可能发生的电力网络变化趋势进行预测；明确电力网络安全态势评估指标及其相关表述含义后，对电力网络安全态势风险进行综合量化，通过划分电力网络安全态势风险量化及等级，构建基于深度学习的电力网络安全态势预测模型，验证模拟安全态势感知预测结果。通过真实电力网络算例的方式，得出新的安全态势感知方法应用在现实电力网络运行环境中时，能够实现对其安全等级的精准预测，可以为电力网络的可持续运行提供安全保障条件，具有一定的实用性。

Power network security situation awareness method based on deep learning

In order to improve the security of power network and realize the sustainable operation of power network, deep learning neural network is introduced to design and study the security situation awareness method of power network, and a new security situation awareness method is proposed. This paper uses the power network security situation assessment index, combined with all kinds of power network environmental factors, to predict the possible future power network change trend; After the power network security situation assessment index and related expression meanings are defined, the power network security situation risks are comprehensively quantified. By dividing the power network security situation risk quantification and grade, the power network security situation prediction model based on deep learning is constructed to verify the simulation security situation awareness prediction results. Through the example of real power network, it is concluded that when the new security situation awareness method is applied in the operation environment of real power network, it can achieve accurate prediction of its security level and provide security guarantee conditions for the sustainable operation of power network, which has certain practicability.