Multi-objective optimization of a hydrogen production through the HyS process powered by solar energy in different scenarios. (3rd May 2018)

• Record Type: Journal Article
• Authors: Liberatore, R.; Bassi, A.; Turchetti, L.; Venturin, M.
• Is Part Of: International journal of hydrogen energy. Volume 43:Number 18(2018)
• Page Start: 8683
• Page End: 8697
• Publication Date: 2018-05-03
• Subjects: Hydrogen -- Thermochemical cycle -- Hybrid sulfur process -- Solar energy -- Multi-objective optimization; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2018.03.109
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Thermochemical or hybrid cycles powered by concentrated solar energy are a very promising way to produce an effective clean hydrogen through the water splitting, in terms of greenhouse gas (GHG) emissions and power production sustainability. SOL2HY2 is an European project focused on this goal. It deepens the so-called HyS process in a closed or partially open version using a proper SO2 depolarized electrolyser, and moreover, it investigates key materials and process solutions, along the entire production chain. However, the identification of the best solution to obtain a suitable hydrogen in terms of cost, efficiency, availability of energy and material, sharing of renewable energy source, continuity of operation in different locations and plant sizes, poses many challenges in terms of flexibility and complexity of the system. In fact, it involves various chemical equipment, different solar and thermal storage technologies, and variable operative conditions with different reaction temperatures and mixture concentrations. Hence it arises the importance to have a tool for the investigation of this system. In this paper, data analysis and multi-objective techniques are used to study and optimize the process under consideration. Several mathematical methods have been exploited to make the best use of the available data, such as Design of Experiments techniques, meta-modeling strategies and genetic algorithms. All these methods have been implemented in the open source environments Scilab and R. Highlights: Multi-objective optimization of a H2 solar production process was analyzed. Closed and partially open HyS cycle was used, depending on SO2 supply for SDE. A CSP, PV, sulfur burner and grid power combination proved to be satisfactory. Sobol and Full factorial DoE as well as Genetic Algorithms are exploited. Green H2 can be at competitive costs, if a correct combination of sources is used.