Transient security state identification of smart grid based on multi feature fusion Online publication date: Thu, 12-Oct-2023
by Baoyu Ye; Xibin Yang; Xiaoyu Yang
International Journal of Energy Technology and Policy (IJETP), Vol. 18, No. 3/4/5, 2023
Abstract: In order to improve the power supply stability of the smart grid and accurately identify the transient safety status of the power grid, a smart grid transient safety status identification method based on multi feature fusion is proposed. Firstly, extract the transient zero sequence active energy features of the smart grid, and use the S transform to extract the transient energy features and comprehensive phase angle features. Secondly, based on the extracted multiple features, a deep belief network (DBN) is used to fuse multiple features. Finally, based on the results of multi feature fusion, the SVM algorithm is used to classify and identify the transient safety status of the power grid. The experimental results show that the transient safety state identification accuracy of this method is high, stable at 98%; and the misjudgement rate of this method has been reduced, with a maximum of no more than 3%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Energy Technology and Policy (IJETP):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com