A Communication-Aware Clustered Framework for Demand Response Management in 5G-Enabled Smart Grids
Sajjad Rabbani1, Rao Muhammad Asif 1, Heba G. Mohamed2, Adnan Yousaf1,*, Ateeq Ur Rehman3,*
1 Department of Electrical Engineering, Superior University, Lahore, Pakistan
2 Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
3 School of Computing, Gachon University, Seongnam-si, Republic of Korea
* Corresponding Author: Adnan Yousaf. Email: 
; Ateeq Ur Rehman. Email: 
Computers, Materials & Continua https://doi.org/10.32604/cmc.2026.084783
Received 29 April 2026; Accepted 21 July 2026; Published online 10 August 2026
Abstract
The management of demand response (DR) in smart grids increasingly relies on low-latency, reliable, and scalable communication, yet traditional DR signaling methods fail in dense network environments. In this paper, a communication-aware clustered demand response architecture (CCA-DR) for smart grids based on 5G technology is proposed, in which DR users are clustered based on service-area density and assigned to the closest communication-aware cluster. It is linked via directional antenna pairs to reduce cumulative signal attenuation. The model incorporates the properties of the 5G broadband channels, such as path loss, interference, latency, and reliability constraints, into the DR management process. A mechanism of iterative refinement is also used to enhance the cluster structure and communication quality as the load on the cells increases. The proposed framework is compared with four benchmark schemes: Distance-Only clustering, Greedy Antenna selection, Static Clustering, and Unicast DR. The simulation results indicate that the proposed CCA-DR outperforms all baselines across key communication and operational indicators. The proposed approach maintains the lowest average latency, approximately 5–13 ms across normalized cell loads from ρ = 0.1 to ρ = 1.0, remaining below the 20 ms real-time DR threshold. It also achieves lower packet loss, higher SINR, improved user rate, stronger active DR user ratio, better reliability, and stronger fairness than the benchmark schemes. The method also supports the highest user rate, the largest active user ratio of DR (around 0.95), and the best communication reliability. The framework also attains high-quality fairness of DR allocation and high-quality cell-edge SINR. Further sensitivity analysis indicates that stronger incentives lead to greater aggregate DR response in the proposed architecture. The addition of 5G communication awareness to clustering, user assignment, and antenna assignment enhances the effectiveness, resilience, and scalability of DR management in next-generation smart grids.
Keywords
Demand response; communication-aware clustered demand response framework; signal-to-interference noise ratio; 5G
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