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Research Papers

Dynamic Behavior of a Solid Oxide Steam Electrolyzer System Using Transient Photovoltaic Generated Power for Renewable Hydrogen Production

[+] Author and Article Information
Alireza Saeedmanesh

Department of Mechanical and Aerospace Engineering,
University of California, Irvine,
Irvine, CA 92697-3975
e-mail: asaeedma@uci.edu

Paolo Colombo

Department of Energy,
Politecnico di Torino,
Torino 10129, Italy
e-mail: paolo.colombo@studenti.polito.it

Dustin McLarty

School of Mechanical and Materials Engineering,
Washington State University,
Pullman, WA 99164-2920
e-mail: dustin.mclarty@wsu.edu

Jack Brouwer

Department of Mechanical and Aerospace Engineering,
University of California, Irvine,
Irvine, CA 92697-3975
e-mail: jbrouwer@uci.edu

1Corresponding author.

Manuscript received October 5, 2018; final manuscript received March 18, 2019; published online April 12, 2019. Assoc. Editor: Soumik Banerjee.

J. Electrochem. En. Conv. Stor. 16(4), 041008 (Apr 12, 2019) (14 pages) Paper No: JEECS-18-1107; doi: 10.1115/1.4043340 History: Received October 05, 2018; Accepted March 23, 2019

This study investigates the dynamic behavior of a solid oxide steam electrolyzer (SOSE) system without an external heat source that uses transient photovoltaic (PV) generated power as an input to produce compressed (to 3 MPa) renewable hydrogen to be injected directly into the natural gas network. A cathode-supported crossflow planar solid oxide electrolysis (SOE) cell is modeled in a quasi-three-dimensional thermo-electrochemical model that spatially and temporally simulates the performance of a unit cell operating dynamically. The stack is composed of 2500 unit cells that are assumed to be assembled into identically operating stacks, creating a 300 kW electrolyzer stack module. For the designed 300 kW SOSE stack (thermoneutral voltage achieved at design steady-state conditions), powered by the dynamic 0–450 kW output of PV systems, thermal management and balancing of all heat supply and cooling demands is required based upon the operating voltage to enable efficient operation and prevent degradation of the SOSE stacks. Dynamic system simulation results show that the SOSE system is capable of following the dynamic PV generated power for a sunny day (maximum PV generated power) and a cloudy day (highly dynamic PV generated power) while the SOSE stack temperature gradient is always maintained below a maximum set point along the stack for both days. The system efficiency based upon lower heating value of the generated hydrogen is between 0–75% and 0–78% with daily hydrogen production of 94 kg and 55 kg for sunny and cloudy days, respectively.

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References

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Figures

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Fig. 1

California renewable curtailment3

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Fig. 2

Schematic of cross-flow SOE unit cell

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Fig. 3

Polarization curves of HiPoD cells [24]

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Fig. 4

SOSE system layout

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Fig. 5

PV generated power for a sunny and a cloudy day

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Fig. 6

Steady-state spatial distribution of (a) Nernst voltage (V), (b) overpotential loss (V), and (c) current density (A/cm2)

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Fig. 7

Steady-state spatial distribution of the molar fraction of (a) steam, (b) hydrogen, (c) oxygen, and (d) nitrogen

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Fig. 8

PV generated power versus stack consumed power (VCell × I × NCell) for a sunny day

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Fig. 9

Cell current density and voltage for a sunny day

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Fig. 10

PEN average temperature and maximum temperature difference along the PEN for a sunny day

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Fig. 11

PEN minimum, average, and maximum temperature for a sunny day

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Fig. 12

Efficiencies for a sunny day

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Fig. 13

Contribution of each component in power consumption for a sunny day

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Fig. 14

Highly endothermic spatial distribution: (a) current density (A/cm2), (b) overpotential loss (V), (c) PEN average temperature (K), and (d) oxygen molar fraction

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Fig. 15

Highly exothermic spatial distribution: (a) current density (A/cm2), (b) overpotential loss (V), (c) PEN average temperature (K), and (d) oxygen molar fraction

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Fig. 16

PV generated power versus stack consumed power (VCell × I × NCell) for a cloudy day

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Fig. 17

Cell current density and voltage for a cloudy day

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Fig. 18

PEN average temperature and maximum temperature difference along the PEN for a cloudy day

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Fig. 19

PEN minimum, average, and maximum temperature for a cloudy day

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Fig. 20

Efficiencies for a cloudy day

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Fig. 21

Contribution of each component in power consumption for a cloudy day

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