Knowledge representation and general Petri net models for power grid fault diagnosis
Open accessAbstract
This study deals with the idea that comprehensive knowledge representation should be established for fault diagnosis. Sufficient grid fault information including the network topology and protection knowledge are used with a diagnostic algorithm. In this way, the fault diagnosis programme not only facilitates accurate judgment of fault sections for which many kinds of information are available but also optimises knowledge to simplify the fault diagnosis method. Petri nets are used for logical reasoning on the basis of knowledge representation, which can be used to judge fault elements accurately even when the protective relays and circuit breakers malfunction. It was proved through experimentation here that this method meets the requirements of real‐world diagnosis. The programme can be used as an interface to the self‐healing mechanism of a smart grid. This study also posits that the smart grids should be constructed on the basis of knowledge representation for every subsystem.
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Knowledge representation and causal relationship discovery are also explored for power grid fault diagnosis and impact causal analysis.
“Besides, knowledge representation [228] and causal relationship discovery [230] are also explored for power grid fault diagnosis and impact causal analysis.”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [228]
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- Authors
- Wang, L., Chen, Q., Gao, Z., Niu, L., Zhao, Y., Ma, Z., & Wu, D.
- Affiliations
- State Grid Corporation of China (China) (CN)
- Shandong University (CN)
- Corresponding author
- Chen, Qing
- Venue
- IET Generation, Transmission & Distribution
- Published
- 2015-06
- Volume
- 9
- Issue
- 9
- Pages
- 866-873
- ISSN
- 1751-8687 (ISSN-L)
- 1751-8695
- OpenAlex
- W2062403151
- Cited by
- 44
- References
- 18
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 5 · 2022: 3 · 2021: 3 · 2020: 7 · 2019: 6 · 2018: 8 · 2017: 5 · 2015: 1
- FWCI
- 4.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- IET Generation Transmission & Distribution (publishedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (51277113)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Power Systems Fault Detection
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power System Optimization and Stability
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Keywords
- power grid fault diagnosis, knowledge representation, Petri nets, fault section identification, network topology, protective relays, circuit breakers, logical reasoning, knowledge-based diagnosis
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