False data injection attacks strategy for microgrids based on detection constraints
DOI:
CSTR:
Author:
Affiliation:

School of Electric Power Engineering,South China University of Technology,Guangzhou 510641,China

Clc Number:

TM73; TN91

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Existing security research on microgrid frequency control systems lacks a comprehensive analysis of severe attack scenarios, particularly high-concealment attacks executed by adversaries using internal information. The system vulnerabilities and the extent of their potential impact remain insufficiently assessed. This paper develops a load frequency control model of microgrid that incorporates wind, solar, and storage, and performs a vulnerability analysis of its communication layer to identify potential attack vectors. To address concealment constraints, an optimized attack model is formulated by introducing slack variables, which transforms the nonlinear optimization problem into a linear programming problem, enabling faster solutions and the generation of specific attack sequences. Finally, multiple attack tests are conducted on microgrids in islanded operation mode. Compared to traditional random attack methods, the proposed optimized attack sequence achieves approximately 40% improvement in attack effectiveness while maintaining over 95% stealth. The effects of key microgrid system parameters, different operation modes, and various renewable energy penetration rates on optimal attacks are analyzed. Results show that the proposed optimizationbased attack can significantly improve attack success rate and effectiveness while maintaining stealthy, indicating that microgrid systems remain potentially vulnerable to well-designed attacks.

    Reference
    Related
    Cited by
Get Citation
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: May 12,2025
  • Published:
Article QR Code