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Cloud-Based Optimization and Defense in Active Distribution Networks Under Compound Attacks
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AI
DOI：10.1109/JIOT.2026.3680421.png)
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Abstract
En 中文
A collaborative cloud-based control and defense framework is presented to address the challenges of low-carbon economy and compound attacks such as false data injection (FDI) and denial of service (DoS) in distribution networks (DNs). The framework consists of two main layers: the cloud-based multiobjective optimization layer and the control and defense layer. The upper cloud computing layer focuses on multiobjective optimization, aiming to minimize generation cost, line losses, and node voltage deviations in low-carbon conditions. Meanwhile, the lower layers combine control with attack defense strategies. State-feedback control is utilized to regulate the dynamics of the distributed generation (DG), and defense strategies are employed to protect against potential compound attacks (FDI and DoS attacks). The defense strategy employs a dual control law sliding mode observer for attack reconfiguration, complemented by periodic event triggering. Also, the input-to-state stability of the control strategy is demonstrated. To validate the effectiveness of the proposed control strategy, simulations are conducted both on a computer and on the StarSim hardware-in-the-loop (HIL) experimental platform.
Keywords:
Active distribution networks (ADNs)
cloud computing
denial of service (DoS)
economic operation
false data injection (FDI)
low carbon
Journal
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