Neural Networks in Electrical Engineering Applications: A Review
DOI:
https://doi.org/10.70445/gtst.2.2.2026.219-239Keywords:
Neural networks, Electrical Engineering, Power systems, Control Systems, Machine learning, Deep learning, Renewable EnergyAbstract
Neural networks are an essential component of electrical engineering, as they can model nonlinear, complex and data-driven systems. Here, we review their use in power systems, control systems, electrical machines, power electronics and smart grids. They enhance load prediction, fault diagnosis, stability, motor control and energy management, as well as efficiency and reliability. New techniques like deep learning and hybrid models enhance their use. While facing issues such as data requirements and interpretability, research is making progress. In summary, neural networks play a significant role in creating smart, adaptable and efficient electrical engineering systems.
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