Symmetry-Aware Optimized Fuzzy Deep Reinforcement Learning-GRU for Load Balancing in Smart Power Grids

Mohammad Mahdi Mohammad; Mojdeh Sadat Najafi Zadeh; Seyedkian Rezvanjou; Nuria Serrano; F. Hernando-Galego; Diego Martín; José Vicente Álvarez-Bravo

doi:10.3390/sym18020343

Publication record · 2026

Symmetry-Aware Optimized Fuzzy Deep Reinforcement Learning-GRU for Load Balancing in Smart Power Grids

Authors: Mohammad Mahdi Mohammad · Mojdeh Sadat Najafi Zadeh · Seyedkian Rezvanjou · Nuria Serrano · F. Hernando-Galego · Diego Martín · José Vicente Álvarez-Bravo
Year: 2026
Publisher: MDPI
Journal or publication: Symmetry
Google Scholar citations: 8

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CiteScore 2025 (Scopus)5.2

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Top 10% in any categoryYes

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Mathematics (all)36/414 · Q1 · percentile 91 · Top 10%
Physics and Astronomy (miscellaneous)18/88 · Q1 · percentile 80
Computer Science (miscellaneous)63/179 · Q2 · percentile 65
Chemistry (miscellaneous)66/137 · Q2 · percentile 52

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Research summary

A symmetry-aware framework combines fuzzy logic, deep reinforcement learning, GRU temporal modelling and multi-objective optimization for adaptive smart-grid load balancing. Tests on UK-DALE, Pecan Street and REDD examine accuracy, stability, convergence and real-time suitability.

Original description prepared for this website; consult the publication for its authoritative abstract.

DOI 10.3390/sym18020343 ↗ · Open-access version ↗ · View Google Scholar record ↗