Prescribed-Time Mitigation of False Data Attacks in Microgrid Load Frequency Control
Microgrid load frequency control (LFC) operation relies extensively on cyber networks which significantly increases their susceptibility to false data injection attacks (FDIAs) that can undermine microgrid’s stability. This paper proposes a multi-layer control framework that efficiently detects and mitigates false data injected in the actuator and measurements of the LFC. Firstly, an FDIAs detection layer based on an unknown input observer (UIO) utilizing an adaptive threshold has been proposed. An adaptive threshold aims to enhance detection sensitivity and reduce false alarms by distinguishing between actual attacks and temporal discrepancies in observer error caused by internal disturbances. Secondly, to ensure timely and accurate mitigation of FDIAs, an estimation layer utilizing a prescribed-time unknown input observer (PTUIO) has been designed. PTUIO is designed to be robust against unknown inputs and parameter uncertainty. The PTUIO employs periodic time-delayed output to estimate system states and FDIAs within a predefined time. Afterward, a two-layer robust and resilient LFC system was developed. The first layer ensures the rejection of unknown inputs, including load/generation disturbances and FDIAs based on PTUIO estimations. The second layer incorporates robust state feedback control, which stabilizes the microgrid and accurately tracks the frequency reference. The effectiveness of the proposed control system is confirmed through multiple scenarios by simulations and Hardware-in-the-loop (HIL), demonstrating its robustness and reliability in addressing challenges associated with internal disturbances, and FDIAs within the microgrid.
Authors
- Mohamed Zaery (ORCID: https://orcid.org/0000-0001-7244-8152)
- Esam H. Abdelhameed (ORCID: https://orcid.org/0000-0001-8208-580X)
- Said I. Abouzeid (ORCID: https://orcid.org/0000-0002-9715-7519)
- Syed Muhammad Amrr (ORCID: https://orcid.org/0000-0001-5084-5472)
- Yong Chen (ORCID: https://orcid.org/0000-0003-4580-8655)
Institutions
- King Fahd University of Petroleum and Minerals (SA)
- University of Electronic Science and Technology of China (CN)
- Aswan University (EG)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1109/tsg.2025.3557207
- Citations
- 2
- Primary Topic
- Smart Grid Security and Resilience
- Type
- article
- Field-Weighted Citation Impact
- 2.43