Advancing Power Quality in Distribution Grids through AI: Opportunities, Challenges, optimization, and Policy Pathways
Keywords:
Advancing Power Quality, Distribution Grids, Artificial Intelligent, Opportunities, Challenges, Optimization, PolicyAbstract
The rapid evolution of modern distribution grids toward digital, decentralized, and intelligent systems has elevated the importance of Power Quality (PQ) as a fundamental determinant of grid reliability, efficiency, and stability. This article explores how Artificial Intelligence (AI) is revolutionizing PQ management through intelligent monitoring, predictive analytics, and optimization techniques. The article begins by outlining the critical aspects of PQ disturbances, such as voltage sags, harmonics, and flickers, and their growing complexity due to the integration of renewable energy resources, electric vehicles, and nonlinear loads. It then examines the role of Distributed Flexible AC Transmission System (D-FACTS) devices, including Dynamic Voltage Restorers (DVRs) and Distribution STATCOMs (D-STATCOMs), as essential tools for maintaining PQ stability. Furthermore, the article discusses AI’s transformative role in automating event detection, classification, and corrective control using data-driven models and real-time optimization algorithms. The article highlights key opportunities, such as predictive PQ management and self-healing grids, alongside challenges like data privacy, cybersecurity, and regulatory constraints. Finally, the article emphasizes the necessity of robust policy implementation, covering AI governance, standardization, and ethical compliance, to ensure safe, transparent, and sustainable deployment of AI technologies in PQ enhancement.
