Fault location method for overhead line-cable hybrid line based on the LSTM network
DOI: 10.23977/jeeem.2022.050101 | Downloads: 29 | Views: 1051
Author(s)
GAO Shang 1, ZHAO Laijun 1, ZOU Wenlei 1, SUN Kang 1
Affiliation(s)
1 School of Electrical Engineering and Automation, Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Henan Polytechnic University., Jiaozuo 454003
Corresponding Author
ZHAO LaijunABSTRACT
The intelligent algorithm has attracted broad attention in recent research of fault location method for the overhead line-cable hybrid line. To aim at the problems of high computational complexity and poor fault tolerance in existing hybrid line intelligent fault location algorithms, a new fault location method based on Long Short-term Memory (LSTM) network is proposed. Firstly, a 220kV hybrid line is built to collect line-mode voltage signals on the bus side of the line under different fault types. Secondly, discrete wavelet transform is used to decompose the line-mode voltage signal to extract fault features, and the data is preprocessed to obtain a sample set. Finally, the LSTM network performs adaptive learning on the input and output samples to obtain the LSTM fault location model. PSCAD/Matlab simulation results show that the fault location algorithm is simple to implement and has high fault tolerance. It is not affected by the transition resistance and the initial phase angle of the fault. It meets the requirements of engineering practice that the positioning accuracy is within 200 meters.
KEYWORDS
Hybrid line; long short-term memory network; fault location; intelligent algorithmCITE THIS PAPER
GAO Shang, ZHAO Laijun, ZOU Wenlei, SUN Kang, Fault location method for overhead line-cable hybrid line based on the LSTM network. Journal of Electrotechnology, Electrical Engineering and Management (2022) Vol. 5: 1-8. DOI: http://dx.doi.org/10.23977/jeeem.2022.050101.
REFERENCES
[1] Zhang Yining. Summary of fault location methods for overhead-cable hybrid transmission lines [J]. Electric Power Engineering Technology, 2020, 39 (06): 44-51.
[2] Yang Jian, Tang Zhong. Design of traveling wave fault location algorithm for hybrid transmission lines [J]. Journal of Power system and Automation, 2017, 29 (01): 63-68.
[3] Deng Wenling, Lu Jiping, Shi Jiawei, et al. Hybrid line fault location method based on double-terminal asynchronous data [J]. Grid Technology, 2021, 45 (04): 1574-1580.
[4] Yan Limei, Fu Chungeng, Xu Jianjun, et al. Transmission line traveling wave fault location based on improved interpolation HHT algorithm [J]. Foreign Electronic Measurement Technology, 2019, 38 (09): 1-6.
[5] Deng Feng, Li Xinran, Zeng Xiangjun. Single-ended traveling wave location method for hybrid lines based on full waveform information [J]. Journal of Electrotechnology, 2018, 33 (15): 3471-3485.
[6] Huang Yuanliang, Hao Zhenzhen, Jiang Tiantian, et al. A new double-ended traveling wave fault location algorithm for transmission lines [J]. Journal of Electronic Measurement and Instruments, 2016, 30 (01): 20-29.
[7] Feng Kuan, Wang Sihua. Hybrid line fault location considering harmonic natural frequency and VMD [J]. Electrical Measurement and Instrumentation, 2019, 56 (17): 109,115.
[8] Zhang Yuanyuan, Yu Lijie, Wang Yongsheng, et al. Research on fault location method for double-ended transmission lines [J]. Electronic Measurement Technology, 2018, 41 (16): 143,146.
[9] MAHESHWARI A, AGARWAL V, SHARMA S K. Comparative analysis of ANN-based FL and travelling wave-based FL for location of fault on transmission lines[J]. Journal of the Institution of Engineers, 2019, 100(3): 1-10.
[10] Zhou Niancheng, Xiao Shuyan, Yu Yinshu, et al Distribution network fault location based on centroid frequency and BP neural network [J] Journal of electrotechnics, 2018, 33 (17): 4154-4166.
Downloads: | 1973 |
---|---|
Visits: | 94000 |
Sponsors, Associates, and Links
-
Power Systems Computation
-
Internet of Things (IoT) and Engineering Applications
-
Computing, Performance and Communication Systems
-
Journal of Artificial Intelligence Practice
-
Advances in Computer, Signals and Systems
-
Journal of Network Computing and Applications
-
Journal of Web Systems and Applications
-
Journal of Wireless Sensors and Sensor Networks
-
Journal of Image Processing Theory and Applications
-
Mobile Computing and Networking
-
Vehicle Power and Propulsion
-
Frontiers in Computer Vision and Pattern Recognition
-
Knowledge Discovery and Data Mining Letters
-
Big Data Analysis and Cloud Computing
-
Electrical Insulation and Dielectrics
-
Crypto and Information Security
-
Journal of Neural Information Processing
-
Collaborative and Social Computing
-
International Journal of Network and Communication Technology
-
File and Storage Technologies
-
Frontiers in Genetic and Evolutionary Computation
-
Optical Network Design and Modeling
-
Journal of Virtual Reality and Artificial Intelligence
-
Natural Language Processing and Speech Recognition
-
Journal of High-Voltage
-
Programming Languages and Operating Systems
-
Visual Communications and Image Processing
-
Journal of Systems Analysis and Integration
-
Knowledge Representation and Automated Reasoning
-
Review of Information Display Techniques
-
Data and Knowledge Engineering
-
Journal of Database Systems
-
Journal of Cluster and Grid Computing
-
Cloud and Service-Oriented Computing
-
Journal of Networking, Architecture and Storage
-
Journal of Software Engineering and Metrics
-
Visualization Techniques
-
Journal of Parallel and Distributed Processing
-
Journal of Modeling, Analysis and Simulation
-
Journal of Privacy, Trust and Security
-
Journal of Cognitive Informatics and Cognitive Computing
-
Lecture Notes on Wireless Networks and Communications
-
International Journal of Computer and Communications Security
-
Journal of Multimedia Techniques
-
Automation and Machine Learning
-
Computational Linguistics Letters
-
Journal of Computer Architecture and Design
-
Journal of Ubiquitous and Future Networks