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<p>In this paper, a distributed event-based control architecture is proposed to improve the security and environmental performance of cyber-physical smart grids. The strategy concurrently responds to coordinated cyberattacks, such as false data injection (FDI) and denial-of-service (DoS), and incorporates carbon emission trading (CET) into the optimization of the energy dispatch. It constructs a novel event-based resilient consensus algorithm (ERCA), which incorporates attack detection and recovery schemes into a distributed decision-making framework. The algorithm employs a trust-node-based correction strategy and reliable acknowledgment signaling to maintain reliable state estimation and coordination under communication interruptions and data falsification. By incorporating carbon-pricing directly into the local cost functions, the framework enables generation units and responsive loads to achieve economically efficient and low-carbon operation without centralized supervision. Convergence of the proposed method is rigorously established under simultaneous FDI and DoS attacks. Simulation studies on an IEEE 41-bus system confirm that the framework maintains power balance, stabilizes electricity prices, ensures consistency in reported emissions, and reduces overall carbon output, even in the presence of stealthy and disruptive cyber intrusions.</p>

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An event-based resilient consensus algorithm for secure and low-carbon operation of cyber-physical smart grids

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月1日

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  • Bandar Y. Alfaifi,
  • Ammar Alsinai,
  • Hanan Ahmed,
  • Romana Ashfaq,
  • Azmat Ullah Khan Niazi

摘要

In this paper, a distributed event-based control architecture is proposed to improve the security and environmental performance of cyber-physical smart grids. The strategy concurrently responds to coordinated cyberattacks, such as false data injection (FDI) and denial-of-service (DoS), and incorporates carbon emission trading (CET) into the optimization of the energy dispatch. It constructs a novel event-based resilient consensus algorithm (ERCA), which incorporates attack detection and recovery schemes into a distributed decision-making framework. The algorithm employs a trust-node-based correction strategy and reliable acknowledgment signaling to maintain reliable state estimation and coordination under communication interruptions and data falsification. By incorporating carbon-pricing directly into the local cost functions, the framework enables generation units and responsive loads to achieve economically efficient and low-carbon operation without centralized supervision. Convergence of the proposed method is rigorously established under simultaneous FDI and DoS attacks. Simulation studies on an IEEE 41-bus system confirm that the framework maintains power balance, stabilizes electricity prices, ensures consistency in reported emissions, and reduces overall carbon output, even in the presence of stealthy and disruptive cyber intrusions.