摘要
随着电力系统规模的不断扩大、大量新能源的并网,以及电力电子等新技术的发展,现代电力系统的结构框架趋于复杂化,具有高度随机性。随机扰动下电力系统暂态稳定的评价越来越重要。为此,提出基于支持向量机(SVM)和卷积神经网络(CNN)的方法进行电力系统的暂态稳定性评估。实验结果表明,该方法在准确性和鲁棒性方面均优于传统方法,可以有效地评估电力系统的暂态稳定性。
With the continuous expansion of power system scale,the grid connection of a large number of new energy sources,and the development of new technologies such as power electronics,the structural framework of modern power system tends to be complex and shows a strong randomness.The assessment of the transient stability of power system under random disturbance is becoming increasingly important.To this end,a method based on support vector machine(SVM)and convolutional neural networks(CNN)is proposed for the assessment of transient stability of power system.The experimental results show that the method outperforms traditional methods in terms of accuracy and robustness,and can effectively assess the transient stability of power system.
作者
余云昊
张博达
郭翔
YU Yunhao;ZHANG Boda;GUO Xiang(Guizhou Power Grid Co.,Ltd.,Guiyang 550002,China)
出处
《微型电脑应用》
2024年第7期80-84,共5页
Microcomputer Applications
基金
新型电力系统网络安全防护与支撑技术(0665002022030103WL00002)。
