MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202611099794 A) filed by Adarsh Kumar Arya; Dr. K. Sankar; Saurabh Yadav; Dr. G Gayathri; Dr. S. Vidya; Mr. D. Kanmani; Parvathisha Pudugosula; and Dayananda Sagar Academy Of Technology And Management on August 18, 2026, for Ant Colony-Based Process Scheduling And Heat Recovery Optimization In Thermochemical Hydrogen Plants.
Inventors include Adarsh Kumar Arya; Dr. K. Sankar; Saurabh Yadav; Dr. G Gayathri; Dr. S. Vidya; Mr. D. Kanmani; and Parvathisha Pudugosula.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: Ant Colony-Based Process Scheduling and Heat Recovery Optimization in Thermochemical Hydrogen Plants relates to an intelligent process optimization system for improving hydrogen production efficiency, thermal utilization, and operational coordination in thermochemical hydrogen generation facilities. The proposed invention employs an Ant Colony Optimization (ACO) algorithm to dynamically schedule interconnected thermochemical process operations while simultaneously optimizing heat recovery between high-temperature and low-temperature process streams. The system receives process parameters including reactor temperature, pressure, material conversion, heat availability, process duration, energy demand, flow rates, equipment operating states, and hydrogen production requirements from a plurality of sensors and process controllers. An optimization engine constructs alternative process schedules by representing process operations as nodes and feasible transitions as paths, wherein virtual ants explore the scheduling space and update pheromone values according to process efficiency, thermal recovery, production rate, equipment utilization, and energy consumption. A heat recovery optimization module identifies suitable heat sources and heat sinks and determines heat exchanger operating conditions, thermal storage requirements, and heat-transfer priorities. The optimized schedule coordinates thermochemical reaction stages, heating, cooling, gas separation, recycling, and heat recovery operations to reduce avoidable thermal losses and operational idle periods. A predictive control interface continuously compares optimized operating conditions with real-time plant measurements and modifies scheduling decisions when disturbances occur. The invention further provides a multi-objective optimization framework capable of balancing hydrogen production, thermal efficiency, equipment utilization, operating cost, and process stability. By integrating intelligent scheduling with heat recovery optimization, the proposed system provides an adaptive computational framework for improving the energy efficiency, productivity, reliability, and sustainability of thermochemical hydrogen plants.
Disclaimer: Curated by HT Syndication.
