MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202621105981 A) filed by Ch. Mallareddy; Dr Ganesh Sampatro Patil; A Durga Pavani; Dr. Charul Verma; Chokkalingam P; Dr. Aruna S; Dr. Jayshri Harde; Dr. Nathiya M; Kalakuntla Jyothi; Dilip Mishra; Dr. Irissappane Dhanusu Soubache; and Mohamed Mallick on September 03, 2026, for Machine Learning-Based Framework For Real-Time Solar-Wind-Battery Power Forecasting And Energy Management.
Inventors include Ch. Mallareddy; Dr Ganesh Sampatro Patil; A Durga Pavani; Dr. Charul Verma; Chokkalingam P; Dr. Aruna S; Dr. Jayshri Harde; Dr. Nathiya M; Kalakuntla Jyothi; Dilip Mishra; Dr. Irissappane Dhanusu Soubache; and Mohamed Mallick.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: The present invention discloses the development of a machine learning-driven methodology for real-time prediction and energy management of combined solar, wind, and battery systems. Precise prediction of electricity generation in the renewable sources is essential to enable proper use of energy and achieve the stability of the grid. In order to accomplish this, the suggested method uses sophisticated machine learning models to predict the nonlinear and dynamic nature of solar radiation, wind velocity, and performance of battery storage. Through this process, the energy dispatch and storage can be managed effectively in real time. The method is tested on practical data to verify its effectiveness in forecasting and managing energy efficiently. FIG.1
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