English

An AI-Enabled Hybrid Cyber-Physical Framework for Adaptive Control in Smart Grids

Machine Learning 2025-12-01 v2

Abstract

Evolving smart grids require flexible and adaptive control methods. A harmonized hybrid cyber-physical framework, which considers both physical and cyber layers and ensures adaptability, is one of the critical challenges to enable sustainable and scalable smart grids. This paper proposes a three-layer (physical, cyber, control) architecture, with an energy management system as the core of the system. Adaptive Dynamic Programming(ADP) and Artificial Intelligence-based optimization techniques are used for sustainability and scalability. The deployment is considered under two contingencies: Cloud Independent and cloud-assisted. They allow us to test the proposed model under a low-latency localized decision scenario and also under a centralized control scenario. The architecture is simulated on a standard IEEE 33-Bus system, yielding positive results. The proposed framework can ensure grid stability, optimize dispatch, and respond to ever-changing grid dynamics.

Keywords

Cite

@article{arxiv.2511.21590,
  title  = {An AI-Enabled Hybrid Cyber-Physical Framework for Adaptive Control in Smart Grids},
  author = {Muhammad Siddique and Sohaib Zafar},
  journal= {arXiv preprint arXiv:2511.21590},
  year   = {2025}
}

Comments

16 pages, 11 figures, IEEEaccess journal

R2 v1 2026-07-01T07:56:36.566Z