Construction and Application of Cyber Attack Simulation Platform for Power Systems
This study has designed and implemented a simulation platform to address the security challenges posed by the networking of power systems. The platform simulates the response and stability of power systems under cyber attacks, such as Denial of Service (DoS) and False Data Injection (FDI). It integrates energy management systems, communication networks, and physical power system simulators to create a controlled environment for testing and optimizing security strategies. By applying advanced communication protocols and network latency simulation techniques, the platform ensures secure and efficient data transmission while allowing comprehensive testing of security measures. Simulation results demonstrate the platform's ability to effectively model various cyber attack scenarios and assess their impact on the stability and security of power systems. This research underscores the importance of implementing robust cyber and physical security measures and the necessity of providing comprehensive security for power systems. Through this platform, the study not only reveals the vulnerabilities of power systems under cyber attacks but also provides experimental data and theoretical support for future security strategy development.
Authors
- Bo-Cheng Charles Lai (ORCID: https://orcid.org/0000-0002-9729-5196)
- Pandeng Li (ORCID: https://orcid.org/0000-0002-0717-8659)
- Jinran Du
- Chao Hong (ORCID: https://orcid.org/0000-0003-1361-7483)
- Zhihong Liang (ORCID: https://orcid.org/0000-0001-8118-753X)
- Yiwei Yang (ORCID: https://orcid.org/0009-0009-5225-791X)
- Wenqian Xu (ORCID: https://orcid.org/0000-0002-4605-6769)
- Lin Chen (ORCID: https://orcid.org/0000-0002-2775-9012)
Institutions
- China Southern Power Grid (China) (CN)
Publication Details
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1109/appeec61255.2024.10922450
- Citations
- 1
- Primary Topic
- Smart Grid and Power Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.21