MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043361 A) filed by Sr University, Warangal, Telangana, on April 5, for 'reinforcement learning framework-based dynamic load prediction and demand response optimization system.'
Inventor(s) include Dr. Prateek Nigam; and Durgesh Nandan.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "Reinforcement Learning Framework-Based Dynamic Load Prediction and Demand Response Optimization System ABSTRACT This invention leverages RL algorithms to predict energy load fluctuations in real-time and optimize demand response strategies, ensuring efficient power distribution. Unlike traditional static load forecasting methods, the RL-based system continuously learns and adapts to changing energy consumption patterns by interacting with real-time data from smart meters, sensors, and environmental factors. It can predict demand surges, shifts in consumption, and external influences like weather changes, making it highly adaptable to dynamic grid conditions. The system includes an optimization engine that evaluates real-time grid status, energy prices, and load forecasts, generating tailored demand response schedules that reduce energy waste and enhance grid stability. By effectively managing energy resources, it helps utilities lower operational costs and ensures consumers are provided with optimal energy usage recommendations. Additionally, the RL agent's ability to provide scalable solutions across different consumer types, such as residential, commercial, and industrial users, ensures the flexibility and wide applicability of the system. This invention addresses key challenges in modern power grid management, offering a smarter, more adaptive approach to energy distribution, with a significant impact on reducing costs, improving efficiency, and supporting sustainability efforts."
Disclaimer: Curated by HT Syndication.
