Title: Transient security state identification of smart grid based on multi feature fusion

Authors: Baoyu Ye; Xibin Yang; Xiaoyu Yang

Addresses: Inner Mongolia Power (Group) Co., Ltd., Hohehot, 010020, China ' Inner Mongolia Power (Group) Co., Ltd., Hohehot, 010020, China ' Inner Mongolia Power (Group) Co., Ltd., Hohehot, 010020, China

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%.

Keywords: multi-feature fusion; smart grid; transient security state; state identification.

DOI: 10.1504/IJETP.2023.134166

International Journal of Energy Technology and Policy, 2023 Vol.18 No.3/4/5, pp.220 - 232

Received: 28 Apr 2023
Accepted: 03 Jul 2023
Published online: 12 Oct 2023 *

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