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Modelling of a reversible SOC system and validation with experimental data

Reference persons MARTA GANDIGLIO

External reference persons Paolo Marocco (POLITO)
Luca Mastropasqua (UW-Madison)
Jack Brouwer (UCI, University of California Irvine)

Research Groups steps-denerg

Description Topic:
- Development of a zero-dimensional model of the rSOC to capture the electrochemical and thermodynamic processes occurring at the solid oxide cell. The main purpose is to solve for the power, voltage, chemical compositions and mass flows of all species involved in electrolysis and fuel cell modes. In fuel cell mode, the cell level chemistry involves steam reforming of methane, water-gas shift reaction, and electrochemical oxidation of H2. In electrolysis mode, the cell can model both the electrochemical reduction of steam or the co-electrolysis of steam and CO2.
- Experimental data of an rSOC running on different fuel mixtures will be used to validate the model. Experimental campaigns will be performed to understand the transition between fuel cell and electrolysis operation in terms of performance and degradation phenomena. The stack output composition will be monitored via online gas chromatography measurements.
- After completing the stack model, the BoP will be also included to simulate the whole rSOC module (to be later integrated in specific case studies). Balance of plant components will be modelled using a black-box approach that performs mass and energy balances around each unit of operation.
- Application of the model to a specific case study to evaluate the benefits of reversible SOC systems for the integration of natural gas and electricity networks (e.g., electricity and natural gas cost profiles for a specific country, studied both with current variability and also applying higher variations to simulate future scenarios with a higher penetration of intermittent renewable sources).
- POLITO (M. Gandiglio, P. Marocco)
- UW-Madison (L. Mastropasqua)
- UCI (J. Brouwer)
Requirements: good knowledge of dynamic models, autonomy, proactiveness. Good knowledge of English (thesis to be written in English)

Required skills Requirements: good knowledge of dynamic models, autonomy, proactiveness. Good knowledge of English (thesis to be written in English)

Deadline 20/12/2023      PROPONI LA TUA CANDIDATURA

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