10.57647/j.spre.2025.0903.17

A Hybrid Defense Framework for Multi-Area AGC Systems Integrating RBPF-UKF, Noise-Adaptive DRL, and Lightweight Blockchain with Post-Quantum Cryptography

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  • Navid Rashtian1,
  • Alireza Yari*2,
  • Nahid Ardalani,
  • Payam Rabbanifar1,
  • Seyed Javad Mirabedini,
  1. Department of Electrical Engineering, Islamic Azad University, CT.C. (Central Tehran Branch), Tehran, Iran
  2. ICT Research Institute, Tehran, Iran

Received: 2025-05-30

Revised: 2025-07-07

Accepted: 2025-07-26

Published in Issue 2025-09-30

Copyright (c) 2025 Navid Rashtian, Alireza Yari, Nahid Ardalani, Payam Rabbanifar, Seyed Javad Mirabedini (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

How to Cite

Rashtian, N., Yari, A., Ardalani, N., Rabbanifar, P., & Mirabedini, S. J. (2025). A Hybrid Defense Framework for Multi-Area AGC Systems Integrating RBPF-UKF, Noise-Adaptive DRL, and Lightweight Blockchain with Post-Quantum Cryptography. Signal Processing and Renewable Energy (SPRE), 9(3 (September 2025). https://doi.org/10.57647/j.spre.2025.0903.17
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Abstract

 Modern smart grids are facing increasing cyber threats, including False Data Injection (FDI), delays, and combined attacks, which can destabilize multi-area Automatic Generation Control (AGC) systems and lead to cascading blackouts. This study proposes a hybrid defense framework that integrates three advanced components: a Rao-Blackwellized Particle Filter with Unscented Kalman Filter (RBPF-UKF) for precise nonlinear state estimation under non-Gaussian noise, reducing frequency deviation to below 15 MHz within 2.5–4 seconds; a noise-adaptive Deep Reinforcement Learning (DRL) module utilizing a lightweight two-layer MLP, achieving 99% accuracy in detecting FDI, 97% for delays, and 98.5% for combined attacks; and a lightweight Practical Byzantine Fault Tolerance (PBFT) blockchain secured with CRYSTALS-Kyber/Dilithium post-quantum cryptography, ensuring data integrity with a 0.3-second consensus latency. Tested on a five-area IEEE 39-bus system, the framework surpasses traditional methods like LSTMs, DDPG, and Hyperledger Fabric, reducing estimation errors by 60% and meeting standards such as IEC 62443-4-2 and NIST SP 800-208. Its modular design allows seamless integration with legacy SCADA systems. Additionally, FPGA-based acceleration and energy-efficient variants of McEliece cryptography enhance scalability and sustainability in IoT and distributed grid environments. While effective under extreme conditions (0.5–4 seconds latency, 20% packet loss), scaling to ultra-large networks with over 100 nodes remains challenging, which encourages future research into alternative consensus mechanisms, such as DPoS and ABFT.

Keywords

  • False Data Injection,
  • Rao-Blackwellized Particle Filter,
  • Unscented Kalman Filter,
  • Noise-Adaptive Deep Reinforcement Learning,
  • Post-Quantum Cryptography
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