Fault Diagnosis Knowledge Reasoning of Switching Network in Distributed Generation Based on Petri Net

Authors

  • Ziquan Liu Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China
  • Xueqiong Zhu Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China
  • Jingtan Ma Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China
  • Hui Hui Fu Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China
  • Ke Zhao Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China
  • Chengbo Hu Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

DOI:

https://doi.org/10.13052/dgaej2156-3306.37213

Keywords:

Knowledge reasoning, distributed generation, Petri net, fault diagnosis.

Abstract

Telephone network based on IMS technology has been widely applied in
power production and dispatching communication, especially in distributed
power stations. Analysis and positioning failure of IMS network is arduous,
because it’s dependent on IP data communication network. In this paper,
we first introduced IMS switching network architecture and distributed gen-
eration communication network architecture, analyzed and summarized all
kinds of network malfunction. Combining typical IMS network fault con-
nection relations, we introduced an improved Petri net fault handling model
and reasoning method. The diagnosis and positioning results could reflect
the defects of equipment logic functions. This method on fault diagnosis
and location of substation network has been proved to be effective through
practical application.

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Author Biographies

Ziquan Liu, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Ziquan Liu is an engineer of Electric Power Research Institute of State Grid
Jiangsu Electric Power Co., Ltd. He received his Ph.D. degree of Huazhong
University of Science and Technology. He studies in image recognition
technology and power equipment status evaluation.

Xueqiong Zhu, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Xueqiong Zhu is an engineer of Electric Power Research Institute of State
Grid Jiangsu Electric Power Co., Ltd. He received his Ph.D. degree of
Southeast University (SEU). He studies in electric Internet of Things and
Artificial Intelligence.

Jingtan Ma, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Jingtan Ma is an engineer of Electric Power Research Institute of State
Grid Jiangsu Electric Power Co., Ltd. He received his Ph.D. degree of Xi’an
Jiaotong University. He studies in research on state evaluation technology of
switching equipment.

Hui Hui Fu, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Hui Fu is an engineer of State Grid Jiangsu Electric Power Co., Ltd.
She received her master degree of South China University of Technology
(SCUT).She studies in power equipment condition evaluation.

Ke Zhao, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Ke Zhao is an engineer of Electric Power Research Institute of State Grid
Jiangsu Electric Power Co., Ltd. He received his master degree of Tsinghua
University. He studies in switching equipment condition evaluation.

Chengbo Hu, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Chengbo Hu is a senior engineer of Electric Power Research Institute of
State Grid Jiangsu Electric Power Co., Ltd. deputy director of Power Trans-
mission and Transformation Technology Center as well as deputy director of
Artificial Intelligence Laboratory of Power System of State Grid Corporation
(Jiangsu).

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Published

2021-11-09

How to Cite

Liu, Z. ., Zhu, X. ., Ma, J. ., Hui Fu, H. ., Zhao, K. ., & Hu, C. . (2021). Fault Diagnosis Knowledge Reasoning of Switching Network in Distributed Generation Based on Petri Net. Distributed Generation &Amp; Alternative Energy Journal, 37(2), 341–360. https://doi.org/10.13052/dgaej2156-3306.37213

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Articles