A hierarchical resilient economic dispatch strategy for multi-energy system under DoS attacks

The economic dispatch problem (EDP) plays a critical role in achieving efficient and low-carbon operation of multi-energy systems (MES). Distributed optimization algorithms have been widely adopted to solve this problem. However, their reliance on communication networks exposes them to cybersecurity threats, particularly denial-of-service (DoS) attacks, which can disrupt information exchange and degrade system performance. To address this, this paper proposes a resilient distributed optimization algorithm for MES that operates effectively under adverse communication environments. In the proposed method, a cloud-edge-device hierarchical architecture is designed, which integrates multiple independently controlled regional microgrids. With the proposed framework, participants can conduct edge computing through edge intelligent terminals (EITs) to collaboratively optimize operational costs. This framework ensures that distributed optimization algorithms can collaborate seamlessly, even when the system is exposed to DoS attacks. By explicitly considering the coexistence of event-triggered communication and DoS attacks, the framework redefines secure and attack intervals and incorporates switching protocols with second-order information. These features enable the algorithm to maintain convergence and reduce communication burdens, ensuring system performance without relying on initialization. The Lyapunov stability-based theoretical analysis proves that the algorithm achieves exponential convergence to the global optimum under bounded attack frequency and duration, while avoiding Zeno behavior. Simulation results further validate the effectiveness and robustness of the proposed method in securing EDP under adversarial communication environments.