Research Projects

SOL2HY2

Solar To Hydrogen Hybrid Cycles

Sector

Energy

Product/Objective

To demonstrate that hydrogen "green" production is possible through the exploitation of solar power.

Project Summary

The FCH JU strategy has identified hydrogen production by water decomposition pathways powered by renewables such as solar energy to be a major component for sustainable and carbon-free hydrogen supply. Solar-powered thermo-chemical cycles are capable to directly transfer concentrated sunlight into chemical energy by a series of chemical and electrochemical reactions, and of these cycles, hybrid-sulphur (HyS) cycle was identified as the most promising one.The challenges in HyS remain mostly in dealing with materials (electrolyser, concentrator, acid decomposer/cracker and plant components) and with the whole process flowsheet optimization, tailored to specific solar input and plant site location. With recent technology level at large-scale hydrogen production concepts hydrogen costs are unlikely to go below 3.0-3.5 €/kg. For smaller scale plant, the costs of hydrogen might be substantially higher.

Innovation

The project focuses on applied, bottle-necks solving, materials research and development and demonstration of the relevant-scale key components of the solar-powered, CO2-free hybrid water splitting cycles, complemented by their advanced modeling and process simulation including conditions and site-specific technical-economical assessment optimization, quantification and benchmarking. For the short-term integration of solar-power sources with new Outotec Open Cycle will be performed. Simplified structure, extra revenues from acid sales and highly efficient co-use of the existing plants may drop hydrogen costs by about 50-75% vs. traditional process designs.

ES Role

EnginSoft will provide MODAO tools and metamodelling methods in order to simulate the full process performances, including elaboration of DoE strategy, data mining and optimisation. EnginSoft will also help SME and R&D performers in modelling issues, simulation of the relevant processes and elaboration of the models. EnginSoft has also the coordination of the project.

Partners

EnginSoft S.p.A., Italy | Aalto University Foundation, Finland | DLR - German Aerospace Authority, Germany | ENEA - Agenzia per le Nuove Tecnologie, l’Energia e lo Sviluppo Economico Sostenibile, Italy | Outotec Corp., Finland | Erbicol S.A., Switzerland | Oy Woikoski AB, Finland.

Funding Scheme

Funding Scheme Collaborative Project | Call identifier FCH-JU-2012-1, SP1-JTI-FCH.2012.2.5: Thermo-electricalchemical processes with solar heat sources

SOL2HY2

Project web site

Visit the website

Duration

36 months

Period

June 2013 – May 2016

Coordinator

EnginSoft Spa

Reference in EnginSoft

Stefano Odorizzi, Carla Baldasso

Partners Number

7

Ask the Expert

Contact us!

Contact our R&D team for any information.

Ask for information

Find out more

Some of our competences in research and technology transfer

Research project

FORSAL

Robotized foundry for the health of the workforce

The robotic equipment developed by the project for grinding, deburring, de-scoring and repairing castings is a first for most ferrous alloy foundries. The direct benefits that can be identified are varied.

Research project

RuBeeCOMP

Components made in composite material, with integrated wireless communication systems capable of operating in environments hostile to radio frequency: systems, manufacturing technologies and product/ process integrated design platform

Production of components made of composite material, equipped with wireless communication systems capable of operating correctly in environments hostile to radio frequency.

Research project

TECNOMED HUB

Multi-OMICS techniques in the medical sciences: AI to support public Health

The overall objective of the TECNOMED-HUB project is to create, in the Piedmont region of Italy, a technology platform to support medical research 4.0, based on the integration of existing multi-omics platforms with self-learning algorithms, data mining, and big data analytics.