MUMBAI, India, Nov. 28 -- Intellectual Property India has published a patent application (202531108659 A) filed by Mr. C. Jeeva; and Dr. Ambarisha Mishra, Patna, Bihar, on Nov. 9, for 'adaptive multi-objective mppt controller using hess-tuned neural networks for hybrid renewable energy systems.'
Inventor(s) include Mr. C. Jeeva; and Dr. Ambarisha Mishra.
The application for the patent was published on Nov. 28, under issue no. 48/2025.
According to the abstract released by the Intellectual Property India: "[026] The present invention discloses an Adaptive Multi-Objective Maximum Power Point Tracking (MPPT) Controller designed for hybrid renewable energy systems integrating photovoltaic (PV) panels, wind turbines, and a Hybrid Energy Storage System (HESS) composed of batteries and supercapacitors. The controller employs a HESS-tuned neural network capable of analyzing real-time environmental variables, generator characteristics, and storage conditions to produce optimized MPPT decisions. A novel real-time HESS-tuning module continuously updates neural network weights based on battery State-of-Charge (SOC), State-of-Health (SOH), temperature variations, and supercapacitor transient behavior, ensuring enhanced predictive accuracy and long-term storage protection. A multi-objective optimization layer evaluates competing operational goals-including power maximization, storage longevity, system stability, and thermal safety-and dynamically adjusts control priorities. Through a closed-loop feedback mechanism, the controller rapidly responds to disturbances, minimizes tracking errors, and maintains stable power flow across the hybrid system. The invention provides a highly intelligent, adaptive, and storage-aware MPPT solution that significantly improves energy harvesting efficiency, reduces component degradation, and enhances operational reliability in next-generation renewable energy infrastructures."
Disclaimer: Curated by HT Syndication.
