Development of a Neural Network Approach to Evaluate Magnetic Losses in Nanocrystalline Transformers

Nanocrystalline transformers play a crucial role in modern power distribution systems due to their high efficiency and superior magnetic properties. However, an accurate evaluation of losses in these transformers is essential for optimizing their performance. The application of neural networks in assessing losses in nanocrystalline transformers was performed in this work. Neural networks, a subset of artificial intelligence, have shown remarkable capabilities in modeling complex systems and predicting outcomes based on input data. By training neural networks with relevant parameters, accurate predictions of losses in nanocrystalline transformers can be achieved. Overall, leveraging neural networks for evaluating losses in nanocrys-talline transformers presents a promising avenue for enhancing transformer design and performance in modern power systems.