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Economic NMPC for a Reversible Solid Oxide Cell.

Sakshi S Naik1, Yufei Zhao2, Douglas Allan3,4

  • 1Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States.

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|January 19, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an economic nonlinear model predictive control (E-NMPC) for reversible solid oxide fuel cells (rSOCs). The E-NMPC optimizes rSOC operation, reducing hydrogen use in fuel cell mode and improving production in electrolysis mode.

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Area of Science:

  • Energy Storage
  • Electrochemical Engineering
  • Control Systems

Background:

  • Reversible solid oxide fuel cells (rSOCs) can switch between fuel cell and electrolysis modes, offering grid flexibility.
  • Optimizing rSOC operation is challenging due to complex, coupled dynamics.
  • Real-time electricity prices necessitate advanced control strategies for economic viability.

Purpose of the Study:

  • To develop and evaluate an economic nonlinear model predictive control (E-NMPC) framework for optimizing rSOC operation.
  • To assess the economic benefits of E-NMPC compared to conventional control methods.
  • To investigate the integration of battery storage with rSOC systems for enhanced operational flexibility.

Main Methods:

  • Development of a detailed rSOC flowsheet model, including balance-of-plant equipment.
  • Application of an E-NMPC strategy to the rSOC model for operational optimization.
  • Simulation and analysis of E-NMPC performance in both fuel cell and electrolysis modes.

Main Results:

  • E-NMPC reduced hydrogen consumption in fuel cell mode while maintaining electricity output.
  • E-NMPC showed marginal improvements in hydrogen production during electrolysis mode.
  • Integration with a battery system enhanced the flexibility of electricity production and consumption targets.

Conclusions:

  • E-NMPC provides an effective strategy for optimizing the economic operation of rSOCs.
  • The proposed framework demonstrates potential for improving efficiency and economic performance in grid-connected rSOC applications.
  • Battery integration further enhances the adaptability of rSOC systems to dynamic grid demands.