期刊
IEEE TRANSACTIONS ON SMART GRID
卷 10, 期 6, 页码 6000-6013出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2019.2895306
关键词
Cyber security; false data injection attacks; multiphase and unbalanced systems; power distribution systems; state estimation; smart grid
资金
- Natural Science and Engineering Research Council
- Alberta Innovates Technology Futures Post-Doctoral Fellowship
- Nanyang Technological University Internal Funding (SUG, CoE) [M4082287]
In power transmission systems, the false data injection (FDI) attacks against state estimation (SE) have been well studied. However, due to the unique features of power distribution systems including: the low x/r ratio, existence of one-and/or two-phase branches, unbalanced load distributions, and unsymmetrical line parameters; the research on FDI attacks against distribution system SE (DSSE) is still open. In this paper, we investigate the vulnerability of DSSE to FDI attacks. In particular, we first propose a local state-based linear DSSE for multiphase and unbalanced smart distribution systems, which can facilitate the construction of FDI attacks numerically with the least information of system states. Then, the construction of three-phase coupled FDI attacks is introduced. The consideration of the coupling among phases by the three-phase coupled FDI attacks may require the modification of a large number of measurements by the attackers. To reduce the number of required measurements, the perfect three-phase decoupled FDI attacks, which consider the weak couplings among phases, is investigated. The probabilities of successful three-phase decoupled FDI attacks in strongly three-phase coupled systems are also derived numerically. The performance of the proposed FDI attacks against DSSE is evaluated based on IEEE test feeders. The case study results indicate the feasibility of the FDI attacks against DSSE in practical multiphase and unbalanced smart distribution systems. Future research directions including potential countermeasures are also highlighted.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据