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Enhancing energy management for internet of things enabled smart grids with the LEO-QCGNN approach

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  • Vijayalaxmi, Munisamy
  • Thevamudhan, Prathapan

Abstract

The growing use of renewable energy and Internet of Things (IoT) devices in smart grids introduces challenges in managing variable generation and changing energy demands. This study proposes a novel hybrid energy management approach that combines the Lotus Effect Optimization (LEO) algorithm with a Quantum Complete Graph Neural Network (QCGNN) to enhance battery utilization and minimize energy costs while maintaining system stability. The QCGNN model is used to forecast system performance, while LEO optimizes energy consumption and reduces electricity costs. The proposed model is excluded in MATLAB and benchmarked against optimization techniques including Earthworm Optimization Algorithm (EWOA), Genetic Algorithm (GA) and Grey Wolf Optimization (GWO). Results display the proposed method achieves lower costs over one-day, one-week, and one-year scenarios, with a computation time of 95.31 s, which is less than the existing techniques. It demonstrates better transient response and stability during rapid load and renewable generation changes, highlighting its robustness and practical applicability. This method provides an efficient way to manage energy in IoT-enabled smart grids.

Suggested Citation

  • Vijayalaxmi, Munisamy & Thevamudhan, Prathapan, 2026. "Enhancing energy management for internet of things enabled smart grids with the LEO-QCGNN approach," Renewable Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:renene:v:258:y:2026:i:c:s0960148125026242
    DOI: 10.1016/j.renene.2025.124960
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    References listed on IDEAS

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    1. Silva, Jéssica Alice A. & López, Juan Camilo & Guzman, Cindy Paola & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2023. "An IoT-based energy management system for AC microgrids with grid and security constraints," Applied Energy, Elsevier, vol. 337(C).
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    3. Mansouri, Seyed Amir & Nematbakhsh, Emad & Jordehi, Ahmad Rezaee & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco, 2023. "An interval-based nested optimization framework for deriving flexibility from smart buildings and electric vehicle fleets in the TSO-DSO coordination," Applied Energy, Elsevier, vol. 341(C).
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