Artificial Intelligence-Driven Strategies for Management in Modern Utility Infrastructures: The Role of AI on Power Quality Management

The evolution of the power grids directly calls for robust and forward-looking strategies that enhance reliability, resilience, and operational efficiency. Recent developments in artificial intelligence (AI) technologies of machine learning (ML) and predictive analytics give the chance for achieving these objectives through harnessing rich data in real-time and as part of an accumulated history, occurring across a utility environment. The present paper serves as a survey that examines a novel holistic approach for AI deployment inside a state-of-the-art utility environment: deploying in regard to one synergic network and each of its components. Such interaction of algorithms with domain knowledge would provide utilities with the capability for predictive maintenance, optimisation of energy distribution, and perfecting outage management processes—all with a minimum of human interaction. In doing so, strategic integration of AI allows real-time assessment of network performance and creates a culture of continuous improvement and innovation. The paper discusses both theoretical and practical aspects of such developments including real use cases, focusing on enabling technologies and organisational preconditions for successful deployment. AI-powered systems can quickly identify events of non-compliance, generate actionable reports, and indicate ways for corrective steps. The potential of AI fused with the indices for asset health, support utilities to accelerate grid modernisation and efficient resource allocation for their infrastructures.