The e-Hydrogen Cost Optimizer is a Python-based user-defined application that combines techno-economic optimization and environmental modeling to evaluate the feasibility and sustainability of green hydrogen production systems. Built with an accessible GUI and modular codebase, the e-Hydrogen Cost Optimizer integrates key components such as photovoltaic (PV) and wind turbine generation,...
This study applies a combination of prospective and time-explicit life cycle assessment (LCA) to evaluate Ocean Alkalinity Enhancement (OAE) via Bipolar Membrane Electrodialysis (BPMED), an emerging carbon dioxide removal (CDR) technology. By combining prospective and time-explicit LCA, we developed a flexible, time- and location oriented LCA framework which captures both evolving background...
Highlights:
- CAIRN (CairnOpen) demo from CEA: brief demonstration of core
capabilities, modular technology components, scenario management,
MILP constraints for sizing/operation, multiple solver back-ends,
time-series I/O, and reproducible exports. - BW2 to CAIRN integration via GUI: a graphical interface links
Brightway2/Activity Browser activities to CAIRN,...
Topic
Hydrogen-based decentralized energy systems (H2-DES) are gaining prominence as potential solutions for local decarbonization of heat and power supply. We realized the life cycle assessment (LCA) of a H2-DES based on a combined heat and power internal combustion engine (ICE-CHP), the LCA being grounded on a techno-economic analysis (TEA) model implemented in OpenModelica. The study...
