A knowledge graph-based method for intelligent risk assessment of power grid
Abstract With the advancement of science and technology, the material resources that support people’s lives are becoming increasingly abundant, leading to increasingly complex accidents in the electricity system caused by factors such as Natech. Currently, a superficial security check problem exists in analyzing potential hazards in China. Moreover, the evaluation work becomes superficial, resulting in inaccurate identification results and making it difficult to ensure the long-term safety and stability of the power system. Based on these issues, this paper proposes a power system safety assessment method based on a standardized digital knowledge graph (KG). In this method, firstly, through research on standardized digital transformation theory, a triplet dataset based on event accidents is established to support knowledge graph construction; secondly, through knowledge graph construction, hazard analysis and evaluation of the power system are achieved.
Authors
- Xiaoping Zhu (ORCID: https://orcid.org/0000-0001-7236-731X)
- Xiaoling Jin (ORCID: https://orcid.org/0000-0003-1277-2844)
- Lifei Chen
- Jun Zhang (ORCID: https://orcid.org/0000-0003-2215-8813)
- Chen Zhang (ORCID: https://orcid.org/0000-0001-9049-091X)
- Xinyang Han
- Xiaohan Liu
Institutions
- State Grid Corporation of China (China) (CN)
- China University of Mining and Technology (CN)
- Energy Research Institute (CN)
Publication Details
- Journal
- Journal of Physics Conference Series
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1088/1742-6596/2914/1/012016
- Citations
- 4
- Primary Topic
- Smart Grid and Power Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.83