MUMBAI, India, July 24 -- Intellectual Property India has published a patent application (202621063240 A) filed by Mr. Manoj Mohan Kharade; and Dr. Umesh T. Kute on May 19, 2026, for A System And Method For Predictive Power Quality Risk Assessment In Renewable Energy Integrated Power Grids.
Inventors include Mr. Manoj Mohan Kharade; and Dr. Umesh T. Kute.
The application for the patent was published on July 17, 2026, under issue no. 29/2026.
Abstract: The present invention relates to a system and method for predictive power quality risk assessment in renewable energy integrated power grids. The system is configured to acquire renewable energy generation data and electrical load consumption data associated with a power grid, preprocess and condition the acquired data, and forecast future variations in renewable generation and load demand using artificial intelligence-based time-series modelling techniques. The forecasted variations are processed by a power quality risk inference module configured to determine a likelihood or risk level of one or more power quality disturbances, including voltage sag, voltage swell, flicker, harmonic-related instability, transient fluctuation, or combinations thereof. The system is configured to infer such power quality risks prior to occurrence of an actual disturbance event and without requiring direct real-time waveform capture of an already manifested disturbance. The system further comprises an output, alert, and operator support interface configured to generate warning signals, risk indicators, visual outputs, or operator-readable decision support information corresponding to the inferred risk. In certain embodiments, the system may further include a disturbance detection and classification module, an explainable artificial intelligence interpretation module, and an intelligent mitigation and control module, thereby enabling predictive assessment, validation, explanation, and preventive response within a coordinated operational framework. The invention provides early warning of potential power quality disturbances in renewable-integrated power systems, reduces dependency on purely reactive monitoring mechanisms, and supports improved grid stability, operational reliability, and preparedness for smart grids, microgrids, distributed energy networks, and utility-scale renewable integration platforms.
Disclaimer: Curated by HT Syndication.
