Substation Decision-making Platform Based on Artificial Intelligence

Authors

  • Jianhua Qin 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
  • Zhen Wang 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
  • Shan Gao 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/dgaej2156-3306.3524

Keywords:

Decision-making platform, logistic regression model, inference engine.

Abstract

In view of the actual needs faced by the substation maintenance, this paper
proposes a kind of substation decision-making platform based on artificial
intelligence. The platform formalizes and integrates the basic data, electrical
data and the operational data of the equipment, qualitatively triggers the
maintenance task abide by the result of the logistic regression model, provides
further results of data processing through quantitative analysis, and provides
knowledge navigation to the operation guidance of the corresponding equip-
ment. The platform matches the electrical data with the inference engine
stored in the knowledge base. If the data match the condition of the inference
successfully, the inference is triggered and the action is executed. The result
is provided to the relevant staff as a suggestion to assist the final decision.
After the task is completed, the cause, effect and solution of the equipment
failure are backfilled and expanded into the equipment base as a new instance.

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Author Biographies

Jianhua Qin, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Jianhua Qin received his Ph.D. degree of Nanjing University of Aeronautics
and Astronautics (NUAA) in 2019. He is now an engineer of Electric Power
Research Institute of State Grid Jiangsu Electric Power Co., Ltd. He focuses
on wireless sensor network technology and artificial intelligence technology
in power system research.

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.

Zhen Wang, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Zhen Wang is an engineer of Electric Power Research Institute of State Grid
Jiangsu Electric Power Co., Ltd. He received his master degree of South
China University of Technology (SCUT). He studies in research on Intelligent
Transportation and Inspection Technology.

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.

Shan Gao, Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd, Nanjing, 210000, China

Shan Gao is an engineer of Electric Power Research Institute of State Grid
Jiangsu Electric Power Co., Ltd. He studies in switchgear status diagnosis.

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 Corpora-
tion (Jiangsu). He has been committed to the intelligent sensing technology
research and application of power equipment for so many years, and he led
the project of Internet of Things Architecture of transmission and transfor-
mation equipment of State Grid Corporation, in which he is responsible for
wireless sensor network protocol, data code, edge computing framework,
research on standard compound networking equipment, construction of Q&A
system and other important works. He has completed the work of 3 industry
standards and 7 enterprise standards in this field.

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Published

2021-04-12

How to Cite

Qin, J. ., Zhu, X. ., Wang, Z. ., Ma, J. ., Gao, S. ., & Hu, C. . (2021). Substation Decision-making Platform Based on Artificial Intelligence. Distributed Generation &Amp; Alternative Energy Journal, 35(2), 151–172. https://doi.org/10.13052/dgaej2156-3306.3524

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Section

Articles