Artificial Intelligence in Electrical Systems: A Review of Machine Learning Methods, Applications, and Future Perspectives
TL;DR
This review highlights the role of machine learning techniques, deep learning models, and their applications in various areas such as smart grid, renewable energy prediction, fault detection, energy prediction, and predictive maintenance, and covers benchmark datasets, evaluation platforms, and the performance of AI algorithms.
Abstract
The integration of Artificial Intelligence (AI) has emerged as a crucial technology for making electrical systems intelligent and efficient.AI has been a pivotal technology in making electrical systems intelligent and efficient, enhancing automation, reliability, and decision-making. In this review, the integration of AI within the field of electrical engineering is explored, highlighting the role of machine learning techniques, deep learning models, and their applications in various areas such as smart grid, renewable energy prediction, fault detection, energy prediction, and predictive maintenance. It also covers benchmark datasets, evaluation platforms, and the performance of AI algorithms. In addition, the review identifies key challenges, such as Interpretability of the Models, Data Quality, Security of Data and Computational Complexity, and investigates new trends like Explainable AI, Digital Twins, Federated Learning and Edge AI for future electrical systems.