Intellectual Property India Publishes Patent Application for 'A Hybrid Data-Driven And Distributionally Robust Optimization Framework For Optimal Sizing Of PV-Bess Microgrids In Uncertain And Data-Scarce Environments' Filed by Ritvik Sharma; Naman Chaudhary; Navendu Shekhar; Nikhil Kumar; Dr. Ashish Dixit; and Dr. Pawan

MUMBAI, India, June 16 -- Intellectual Property India has published a patent application (202611053986 A) filed by Ritvik Sharma; Naman Chaudhary; Navendu Shekhar; Nikhil Kumar; Dr. Ashish Dixit; and Dr. Pawan, Ghaziabad, Uttar Pradesh, on April 28, for 'a hybrid data-driven and distributionally robust optimization framework for optimal sizing of pv-bess microgrids in uncertain and data-scarce environments.'

Inventor(s) include Ritvik Sharma; Naman Chaudhary; Navendu Shekhar; Nikhil Kumar; Dr. Ashish Dixit; and Dr. Pawan.

The application for the patent was published on June 5, under issue no. 23/2026.

According to the abstract released by the Intellectual Property India: "The present invention relates to a hybrid data-driven and distributionally robust optimization framework for optimal sizing of photovoltaic (PV) and battery energy storage system (BESS) based microgrids operating under uncertain and data-scarce environments. The invention integrates machine learning-based forecasting techniques with advanced distributionally robust optimization to address challenges arising from limited historical data, renewable energy intermittency, and load demand variability. A data-driven module is configured to generate predictive models for solar generation and electrical load demand, while an uncertainty quantification module constructs ambiguity sets to represent distributional uncertainty using statistical distance measures. A distributionally robust optimization engine then solves a min-max optimization problem to determine optimal PV and BESS capacities under worst-case scenarios, ensuring system reliability and cost efficiency. The framework further incorporates operational constraints such as energy balance, storage limitations, and battery degradation effects. The invention enables robust microgrid design suitable for rural electrification, remote systems, and disaster-prone environments, thereby improving resilience, reducing cost, and enhancing energy sustainability under highly uncertain conditions."

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