FAULT DIAGNOSIS TECHNOLOGY OF RELAY PROTECTION IN MICROGRID BASED ON CONVOLUTIONAL BIDI-RECTIONAL LONG SHORT-TERM MEMORY NETWORK

Yang Zhichun; Min Huaidong; Yang Fan; Lei Yang; Hu Wei; Chen Hechong

doi:10.19912/j.0254-0096.tynxb.2023-1431

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (1) : 420-428. DOI: 10.19912/j.0254-0096.tynxb.2023-1431

FAULT DIAGNOSIS TECHNOLOGY OF RELAY PROTECTION IN MICROGRID BASED ON CONVOLUTIONAL BIDI-RECTIONAL LONG SHORT-TERM MEMORY NETWORK

Yang Zhichun, Min Huaidong, Yang Fan, Lei Yang, Hu Wei, Chen Hechong

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Abstract

The operation mode of microgrids with continuously increasing types and capacities of distributed power sources is complex and the fault characteristics are weak. The existing fault diagnosis methods for relay protection devices cannot meet the protection requirements. A fault diagnosis technique for relay protection in microgrid based on convolutional bidirectional Long short-term memory network is proposed. First, analyze the architecture of the multi energy complementary microgrid system, preprocess the collected three-phase current data, and improve the learning efficiency of the subsequent model on the data; Then, combining Convolutional neural network and bi-directional Long short-term memory network, a fault diagnosis method for micro network relay protection based on convolutional bidirectional Long short-term memory network is proposed. Long sequence and local sequence features of three-phase current data are extracted to achieve fault classification and fault location. The fusion attention mechanism focuses on features that have an impact on fault diagnosis, and improves the accuracy of fault diagnosis; Finally, the RTDS real-time simulation system is used to verify the experimental results. The experimental results show that the proposed method has high fault diagnosis accuracy and short calculation time. Compared with Convolutional neural network, long short-term memory network and artificial neural network, the accuracy of fault classification is increased by 8.53%, 9.62% and 11.45% respectively, and the accuracy of fault location is increased by 7.47%, 10.61% and 10.85%, which verifies the effectiveness and progressiveness of the proposed method.

Key words

microgrid / relay protection / fault diagnosis / convolutional bidirectional long short-term memory network / three-phase current / attention mechanism

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Yang Zhichun, Min Huaidong, Yang Fan, Lei Yang, Hu Wei, Chen Hechong. FAULT DIAGNOSIS TECHNOLOGY OF RELAY PROTECTION IN MICROGRID BASED ON CONVOLUTIONAL BIDI-RECTIONAL LONG SHORT-TERM MEMORY NETWORK[J]. Acta Energiae Solaris Sinica. 2025, 46(1): 420-428 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1431

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