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Enhancing Smart Grid Security and Efficiency: AI, Energy Routing, and T&D Innovations (A Review)

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  • Hassam Ishfaq

    (School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, China
    These authors contributed equally to this work.)

  • Sania Kanwal

    (School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, China
    These authors contributed equally to this work.)

  • Sadeed Anwar

    (School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, China
    These authors contributed equally to this work.)

  • Mubarak Abdussalam

    (School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, China
    These authors contributed equally to this work.)

  • Waqas Amin

    (School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621000, China
    These authors contributed equally to this work.)

Abstract

This paper presents an in-depth review of cybersecurity challenges and advanced solutions in modern power-generation systems, with particular emphasis on smart grids. It examines vulnerabilities in devices such as smart meters (SMs), Phasor Measurement Units (PMUs), and Remote Terminal Units (RTUs) to cyberattacks, including False Data Injection Attacks (FDIAs), Denial of Service (DoS), and Replay Attacks (RAs). The study evaluates cutting-edge detection and mitigation techniques, such as Cluster Partition, Fuzzy Broad Learning System (CP-BLS), multimodal deep learning, and autoencoder models, achieving detection accuracies of (up to 99.99%) for FDIA identification. It explores critical aspects of power generation, including resource assessment, environmental and climatic factors, policy and regulatory frameworks, grid and storage integration, and geopolitical and social dimensions. The paper also addresses the transmission and distribution (T&D) system, emphasizing the role of smart-grid technologies and advanced energy-routing strategies that leverage Artificial Neural Networks (ANNs), Generative Adversarial Networks (GANs), and game-theoretic approaches to optimize energy flows and enhance grid stability. Future research directions include high-resolution forecasting, adaptive optimization, and the integration of quantum–AI methods to improve scalability, reliability, and resilience.

Suggested Citation

  • Hassam Ishfaq & Sania Kanwal & Sadeed Anwar & Mubarak Abdussalam & Waqas Amin, 2025. "Enhancing Smart Grid Security and Efficiency: AI, Energy Routing, and T&D Innovations (A Review)," Energies, MDPI, vol. 18(17), pages 1-77, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:17:p:4747-:d:1743362
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