Recent Advances in Machine Learning Applications in Electrical Utility Systems
1 Department of Electrical Engineering, Government College of Engineering, Chandrapur (MH) India 442501.
2 Department of Computer Science, PO Nahata College Bhusawal (MH) India 425201.
3 Department of Mechatronics, Vellore Institute of Technology, Vellore (TN) India 632014.
Review
Open Access Research Journal of Engineering and Technology, 2025, 09(01), 056-064.
Article DOI: 10.53022/oarjet.2025.9.1.0077
Publication history:
Received on 09 July 2025; revised on 17 August; accepted on 20 August 2025
Abstract:
In recent years, the electrical utility industry (EUI) has undergone rapid transformation with the integration of advanced technologies such as artificial intelligence (AI). Among these, machine learning (ML) has emerged as a powerful tool for addressing complex problems in the operation, control, and optimization of modern power systems. This paper presents a comprehensive survey of recent advancements in the application of machine learning techniques within the electrical utility domain, focusing on smart grids, load forecasting, anomaly detection, energy management, and system reliability. By reviewing 20 recent peer-reviewed articles from 2023–2025, we categorize the various ML models, discuss their computational trade-offs, and analyze their effectiveness across different power system applications. This survey identifies current research trends, highlights technical challenges, and outlines promising future directions for ML-based approaches in electrical utilities.
Keywords:
Electrical utility industry; Smart grids; Anomaly detection; Operation; Control; Artificial intelligence
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0