首页|针对智慧能源网中动态负载攻击的新型信息物理协同检测和定位方法

针对智慧能源网中动态负载攻击的新型信息物理协同检测和定位方法

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  • 国家科技期刊平台
  • NETL
  • NSTL
  • 万方数据
以实现电力系统的稳定、高效和清洁运行。然而，动态负载攻击(DLAA)等信息物理攻击的出现给智慧能源网的安全性带来了巨大挑战。因此，本研究针对智慧能源网中的 DLAA 提出了一种新型信息物理协同安全框架。所提出的框架将信息层的攻击预测与物理层的攻击检测和定位整合在一起。首先，提出了一种数据驱动方法来预测网络层的 DLAA 序列。通过设计双径向基函数网络，可以消除干扰对攻击预测的影响。在预测结果的基础上，进一步为物理层设计了基于未知输入观测器的检测和定位方法。此外，还设计了一种自适应阈值，以取代传统的预计算阈值，提高 DLAA 的检测性能。因此，通过信息物理层的协同工作，有效地检测和定位了注入的 DLAA。与现有方法相比，在 IEEE 14 总线和 118 总线电力系统上的仿真结果验证了所提出的信息物理层协同检测和定位 DLAAs 的优越性。
Novel cyber-physical collaborative detection and localization method against dynamic load altering attacks in smart energy grids
Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.

Smart energy gridsCyber-physical systemDynamic load altering attacksAttack predictionDetection and localization

王新宇、王相杰、罗小元、关新平、王书征

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School of Electrical Engineering,Yanshan University,Qinhuangdao,066004,P.R.China

School of Electrical Engineering,Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing,636600,P.R.China

School of Electronic and Electrical Engineering,Shanghai Jiaotong University,Shanghai,200240,P.R.China

智慧能源电网 信息物理系统 动态负载攻击 攻击预测 检测和定位

National Nature Science Foundation of ChinaScience and Technology Plan of Hebei Education DepartmentNature Science Foundation of Hebei ProvinceOpen Research Fund of Jiangsu Collaborative Innovation Center for Smart Distribution Network,Nanjing Institute of Technology

under 62203376QN2021139F2021203043XTCX202203

2024

10.1016/j.gloei.2024.06.003

全球能源互联网(英文)

全球能源互联网(英文)

CSTPCDEI
ISSN：2096-5117
年,卷(期)：2024.7(3)