Mitigating Load-Altering Attacks Against Power Grids Using Cyber-Resilient Economic Dispatch
Mitigating Load-Altering Attacks Against Power Grids Using Cyber-Resilient Economic Dispatch
复制标题
使用网络弹性经济调度减轻针对电网的负载改变攻击
DOI：
10.1109/tsg.2022.3231563
复制
发表时间：
2023
影响因子：
9.6
通讯作者：
Chu Z
中科院分区：
文献类型：
--
作者：
Chu Z
针对物联网（IoT）大功率电器的大规模负载改变攻击（LAAs）对电力系统的安全和稳定构成严重威胁。本文首次从系统角度探讨了针对此类攻击的最优缓解策略。特别是，提出了网络弹性经济调度（CRED）概念，并将其与攻击检测和识别无缝集成，以形成网络弹性增强框架。CRED不是仅仅依赖于本地资源，而是协调系统中基于逆变器的资源（ibr）的频率下降控制增益，以减轻laa的不稳定影响，同时最大限度地降低总体运行成本。为此，建立了包含laa的系统频率动力学模型，并基于参数灵敏度显式导出了相应的系统稳定性约束，并通过一种新颖的递归线性化方法将其纳入到误差最小的系统调度模型中。此外，提出了一种分布式鲁棒方法来解释由LAA检测/参数估计误差驱动的系统动力学相关的不确定性。通过在改进的IEEE可靠性测试系统中进行大量仿真，证明了所提出的CRED模型的整体性能。
Large-scale Load-Altering Attacks (LAAs) against Internet-of-Things (IoT) enabled high-wattage electrical appliances pose a serious threat to power system security and stability. This paper investigates, for the first time, the optimal mitigation strategy from a system perspective against such attacks. In particular, a Cyber-Resilient Economic Dispatch (CRED) concept is proposed and seamlessly integrated with attack detection and identification to form a cyber resiliency enhancement framework. Instead of only relying on local resources, CRED coordinates the frequency droop control gains of Inverter-Based Resources (IBRs) in the system to mitigate the destabilizing effect of LAAs while minimizing the overall operational cost. To achieve this, the LAA-inclusive system frequency dynamics is formulated and the corresponding system stability constraints are explicitly derived based on parametric sensitivities, which are further incorporated into the system scheduling model with minimum error through a novel recursive linearization method. In addition, a distributionally robust approach is proposed to account for the uncertainty associated with system dynamics driven by the LAA detection/parameter estimation errors. The overall performance of the proposed CRED model is demonstrated through extensive simulations in a modified IEEE reliability test system.
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