MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641096426 A) filed by Swarnandhra College Of Engineering And Technology on August 10, 2026, for An Intelligent Ai-Based Adaptive Power Quality Monitoring And Harmonic Mitigation System For Smart Electrical Distribution Networks.
Inventors include Dr. Madhu Valavala; Mr. Bokka Subrahmanyam; Dr Nandhyala Lavanya; Mrs. R E Sulochana Rani; Mr. Jana Murali; Mrs. K K D Bhavani; Mr. Bandaru Bhargav Santhosh; Dr M Surendar; Dr. A Mohan Durga Kumar; and Mr. I. Murali Krishna.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: ABSTRACT OF THE INVENTION: The present invention discloses an Intelligent AI-Based Adaptive Power Quality Monitoring and Harmonic Mitigation System designed for smart electrical distribution networks. The system integrates a distributed array of smart sensor nodes, a central deep-learning analytics engine, modular hybrid active-passive filters, and a synchronized digital twin to achieve continuous, autonomous management of power quality. High-resolution voltage and current measurements are processed at the edge to extract harmonic spectra and transient features, which are securely transmitted to the AI engine. Convolutional and recurrent neural networks identify the sources of harmonic distortion, forecast the evolution of total harmonic distortion, and compute optimal compensation references in real time. Hybrid filter modules combine fixed-tuned passive branches for dominant harmonics with a reduced-rating active inverter stage governed by model-predictive control whose parameters are dynamically updated by the AI engine. A multi-agent coordination layer ensures optimal sharing of compensation effort among geographically dispersed filter units while preventing adverse interactions. The digital twin continuously validates mitigation effectiveness and generates regulatory compliance documentation. Online transfer learning enables the system to adapt to evolving load profiles, renewable generation variability, and network reconfiguration without manual intervention. Cybersecurity is maintained through authenticated encrypted communication and AI-based anomaly detection. Field-representative numerical studies demonstrate rapid reduction of voltage and current THD to levels well within international standards, measurable energy savings, and extension of equipment residual life. The invention thereby provides a scalable, self-optimizing solution that overcomes the limitations of conventional passive filters and fixed- parameter active power filters, delivering a comprehensive platform for the reliable and efficient operation of modern smart grids.
Disclaimer: Curated by HT Syndication.
