Chhabra, Nishtha and Majumdar, Rudrodip and Ghosh, Tapasi and Subramanyam, T (2026) Integrated Techno-economic Multi-objective Optimization Framework for India’s Green Hydrogen Supply Chain. In: International Conference on Thermo-Fluids and Green Energy Technology (TFGET 2026), 16-18 January 2026, Dr B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab.
![[img]](http://eprints.nias.res.in/style/images/fileicons/text.png) |
Text
Revised_Integrated Techno-economic Multi-objective Optimization Framework for India’s Green Hydrogen Supply Chain.pdf - Published Version Restricted to Repository staff only Download (941kB) |
| Contribution | Name |
|---|
| Abstract: | Green hydrogen has the potential to accelerate India's clean energy transition, but its large-scale deployment depends on an efficient and integrated supply chain. The National Green Hydrogen Mission (NGHM) underscores the need for a coordinated plan across production, storage, and transportation segments. However, these elements are often assessed separately using single-objective metrics, limiting their value for policy formulation and unlocking investment. This paper presents a techno-economic, multi-objective framework for India's Green Hydrogen Supply Chain (GHSC), modelling production, storage, and transport options as an encoded 12-bit binary chromosome covering both dedicated and hybrid pathways. Three objective functions focused on minimizing cost, lifecycle emissions, and energy consumption are optimized simultaneously under constraints for safety, leakage, and renewable energy availability. Using India-specific data, a pilot computational demonstration compares seven states (Gujarat, Kerala, Rajasthan, Karnataka, Andhra Pradesh, Odisha, and Tamil Nadu) to illustrate how variations in renewable energy tariffs and capacity utilization factors (CUFs) shape feasible configurations and Pareto-optimal trade-offs. The results identify regionally differentiated cost-emission-energy trade-offs and the technologies most frequently selected in feasible supply chains. By bridging techno-economic details with regional analysis, the framework offers a replicable tool for Non-dominated Sorting Genetic Algorithm (NSGA)-II and other evolutionary algorithms to inform evidence-based policy, prioritize states for pilot projects, and align long-term roadmaps with the goals set out in the National Green Hydrogen Mission. |
|---|---|
| Item Type: | Conference or Workshop Item (Paper) |
| Subjects: | School of Natural and Engineering Sciences > Energy School of Natural and Engineering Sciences > Energy and Environment |
| Divisions: | Schools > Natural Sciences and Engineering |
| Date Deposited: | 19 Jan 2026 05:49 |
| Last Modified: | 19 Jan 2026 06:00 |
| Official URL: | |
| Related URLs: | |
| Funders: | * |
| Projects: | * |
| DOI: | |
| URI: | http://eprints.nias.res.in/id/eprint/3040 |
Actions (login required)
 |
View Item |
