Identification of Intensive Oscillation Parameters of Power System Based on CS-CNN-GRU Network

Abstract

Broadband oscillations caused by power electronic devices contain a large number of high harmonics and interharmonics, and the frequencies of these harmonic/interharmonic components are likely to be very close. In order to improve the accuracy of dense oscillation parameter identification, this paper proposes a cyclic gate unit-convolutional neural network (CNN-GRU) dense oscillation parameter identification method optimized by the cuckoo search algorithm (CS). The Cuckoo search algorithm combined with the cross-entropy function realizes the automatic acquisition of the parameters of the CNN-GRU network and improves the adaptive ability of the model. The analysis of the measured data shows that the method in this paper has high accuracy in identifying the dense oscillation parameters of dense frequency harmonics, interharmonics, and neighboring fundamental interharmonic pairs, etc., and the computational speed is also improved compared with the traditional deep learning network.

Keywords:

• Dense oscillation
• parameter identification
• Cuckoo search algorithm
• CNN-GRU

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Teng Yunxue

Teng Yunxue (1971.09-) Siping City, Jilin Province, People’s Republic of China, graduated from Jilin Institute of Technology, Bachelor’s Degree, is now working for State Grid Corporation Siping Power Supply Company. Research interests: application of artificial intelligence in power system. Email: [email protected].

Sun Shuo

Sun Shuo (1996.01-) Changchun City, Jilin Province, People’s Republic of China, graduated from Northeast Electric Power University, Master, now works in State Grid Corporation Siping Power Supply Company. Research interests: application of artificial intelligence in power system. Email: [email protected].

Zhang Haonian

Zhang Haonian (1998.01-) Changchun City, Jilin Province, People’s Republic of China, graduated from Harbin Institute of Technology, Master, now works in Siping Power Supply Company of State Grid Corporation. Research Interests: Application of energy storage in power system, health state analysis of energy storage battery, integrated energy system, etc. Email: [email protected].

Xing Shibiao

Xing Shibiao (1991.06-) Linyi City, Shandong Province, People’s Republic of China, graduated from Linyi University, Bachelor’s Degree, is now working in State Grid Corporation Siping Power Supply Company. Research Direction, Electrical Engineering and Automation Direction, Email: [email protected].

Yue Yuming

Yue Yuming (1972.02-), Siping City, Jilin Province, People’s Republic of China, graduated from Jilin Institute of Technology, Bachelor’s Degree, now works in State Grid Corporation of China, Siping Power Supply Company. Research Direction, Electrical Engineering and Automation, Email: [email protected].

Zhang Ming

Zhang Ming (1984.10-), People’s Republic of China, Siping City, Jilin Province, China, graduated from Northeast Electric Power University, Master’s Degree, now working in State Grid Corporation of Jilin Province, Siping Power Supply Company. Research interests: big data application in smart grid. Email: [email protected].

Zhu Shihua

Zhu Shihua (1985.06-) Siping City, Jilin Province, People’s Republic of China, graduated from Harbin Institute of Technology, M.S., now working in State Grid Corporation of China Siping Power Supply Company. Research interests: application of artificial intelligence in power system. Email: [email protected].